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Sample records for artificial techniques controlling

  1. Combining Artificial Intelligence and Robust Techniques with MRAC in Fault Tolerant Control

    OpenAIRE

    Vargas Martínez, Adriana

    2011-01-01

    The investigation of this thesis presents different approaches for Fault Tolerant Control based on Model Reference Adaptive Control, Artificial Neural Networks, PID controller optimized by a Genetic Algorithm, Nonlinear, Robust and Linear Parameter Varying (LPV) control for Linear Time Invariant (LTI), LPV and nonlinear systems. All of the above techniques are integrated in different controller�s structures to prove their ability to accommodate a fault. Modern systems and their challenging op...

  2. Under-Actuated Robot Manipulator Positioning Control Using Artificial Neural Network Inversion Technique

    Directory of Open Access Journals (Sweden)

    Ali T. Hasan

    2012-01-01

    Full Text Available This paper is devoted to solve the positioning control problem of underactuated robot manipulator. Artificial Neural Networks Inversion technique was used where a network represents the forward dynamics of the system trained to learn the position of the passive joint over the working space of a 2R underactuated robot. The obtained weights from the learning process were fixed, and the network was inverted to represent the inverse dynamics of the system and then used in the estimation phase to estimate the position of the passive joint for a new set of data the network was not previously trained for. Data used in this research are recorded experimentally from sensors fixed on the robot joints in order to overcome whichever uncertainties presence in the real world such as ill-defined linkage parameters, links flexibility, and backlashes in gear trains. Results were verified experimentally to show the success of the proposed control strategy.

  3. Leading research on artificial techniques controlling cellular function; Saibo zoshoku seigyo gijutsu no sendo kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1996-03-01

    Advanced research and its applicability were surveyed to apply the advanced functional cells to industry. The basic target was set to develop, produce, control and utilize the functional cells, such as intelligent materials and self-regulation bioreactors. The regulation factors regarding apotosis, which is a process of cell suicide programmed within the cell itself of multicellular organisms, cell cycle and aging/ageless were investigated. Furthermore, the function of regulatory factors was investigated at the protein level. Injection of factors regulating cellular function and tissue engineering required for the regulation of cell proliferation were investigated. Tissue engineering is considered to be the intracellular regulation by gene transduction and the extracellular regulation by culture methods, such as coculture. Analysis methods for cell proliferation and function of living cells were investigated using the probes recognizing molecular structure. Novel biomaterials, artificial organ systems, cellular therapy and useful materials were investigated for utilizing the regulation techniques of cell proliferation. 425 refs., 85 figs., 9 tabs.

  4. Combining Artificial Intelligence and Advanced Techniques in Fault-Tolerant Control

    Directory of Open Access Journals (Sweden)

    A. Vargas-Martínez

    2011-08-01

    Full Text Available We present the integration of artificial intelligence, robust, nonlinear and model reference adaptive control (MRACmethods for fault-tolerant control (FTC. We combine MRAC schemes with classical PID controllers, artificial neuralnetworks (ANNs, genetic algorithms (GAs, H∞ controls and sliding mode controls. Six different schemas areproposed: the first one is an MRAC with an artificial neural network and a PID controller whose parameters weretuned by a GA using Pattern Search Optimization. The second scheme is an MRAC controller with an H∞ control(H∞. The third scheme is an MRAC controller with a sliding mode controller (SMC. The fourth scheme is an MRACcontroller with an ANN. The fifth scheme is an MRAC controller with a PID controller optimized by a GA. Finally, thelast scheme is an MRAC classical control system. The objective of this research is to generate more powerful FTCmethods and compare the performance of above schemes under different fault conditions in sensors and actuators.An industrial heat exchanger process was the test bed for these approaches. Simulation results showed that the useof Pattern Search Optimization and ANNs improved the performance of the FTC scheme because it makes the controlsystem more robust against sensor and actuator faults.

  5. Artificial intelligence techniques in Prolog

    CERN Document Server

    Shoham, Yoav

    1993-01-01

    Artificial Intelligence Techniques in Prolog introduces the reader to the use of well-established algorithmic techniques in the field of artificial intelligence (AI), with Prolog as the implementation language. The techniques considered cover general areas such as search, rule-based systems, and truth maintenance, as well as constraint satisfaction and uncertainty management. Specific application domains such as temporal reasoning, machine learning, and natural language are also discussed.Comprised of 10 chapters, this book begins with an overview of Prolog, paying particular attention to Prol

  6. Application of Artificial Intelligence Techniques for the Control of the Asynchronous Machine

    Directory of Open Access Journals (Sweden)

    F. Khammar

    2016-01-01

    Full Text Available The induction machine is experiencing a growing success for two decades by gradually replacing the DC machines and synchronous in many industrial applications. This paper is devoted to the study of advanced methods applied to the command of the asynchronous machine in order to obtain a system of control of high performance. While the criteria for response time, overtaking, and static error can be assured by the techniques of conventional control, the criterion of robustness remains a challenge for researchers. This criterion can be satisfied only by applying advanced techniques of command. After mathematical modeling of the asynchronous machine, it defines the control strategies based on the orientation of the rotor flux. The results of the different simulation tests highlight the properties of robustness of algorithms proposed and suggested to compare the different control strategies.

  7. Diagnostics and Control of Natural Gas-Fired furnaces via Flame Image Analysis using Machine Vision & Artificial Intelligence Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Shahla Keyvan

    2005-12-01

    A new approach for the detection of real-time properties of flames is used in this project to develop improved diagnostics and controls for natural gas fired furnaces. The system utilizes video images along with advanced image analysis and artificial intelligence techniques to provide virtual sensors in a stand-alone expert shell environment. One of the sensors is a flame sensor encompassing a flame detector and a flame analyzer to provide combustion status. The flame detector can identify any burner that has not fired in a multi-burner furnace. Another sensor is a 3-D temperature profiler. One important aspect of combustion control is product quality. The 3-D temperature profiler of this on-line system is intended to provide a tool for a better temperature control in a furnace to improve product quality. In summary, this on-line diagnostic and control system offers great potential for improving furnace thermal efficiency, lowering NOx and carbon monoxide emissions, and improving product quality. The system is applicable in natural gas-fired furnaces in the glass industry and reheating furnaces used in steel and forging industries.

  8. Discrete PID Tuning Using Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Petr DOLEŽEL

    2009-06-01

    Full Text Available PID controllers are widely used in industry these days due to their useful properties such as simple tuning or robustness. While they are applicable to many control problems, they can perform poorly in some applications. Highly nonlinear system control with constrained manipulated variable can be mentioned as an example. The point of the paper is to string together convenient qualities of conventional PID control and progressive techniques based on Artificial Intelligence. Proposed control method should deal with even highly nonlinear systems. To be more specific, there is described new method of discrete PID controller tuning in this paper. This method tunes discrete PID controller parameters online through the use of genetic algorithm and neural model of controlled system in order to control successfully even highly nonlinear systems. After method description and some discussion, there is performed control simulation and comparison to one chosen conventional control method.

  9. Artificial Neural Network-based Technique for Operation Process Control of a Technical Object

    Directory of Open Access Journals (Sweden)

    Stanislaw Duer

    2009-05-01

    Full Text Available This paper presents a method to control an operation process of a complex technical object, a radr system, using trivalent diagnostic information. Also, a general diagram of the complex technical object has been presented, and its internal structure has been described. A diagnostic analysis has been conducted, as a result of which, sets of the functional elements of the object and its diagnostic signals have been determined. Also, the methodology for the diagnostic examination of the technical system has been presented. The result is a functional and diagnostic model, which constituted the basis for initial diagnostic information, which is provided by the sets of information concerning the elements of the basic modules and their output signals. The theoretical results obtained in the present study have been verified in practice on a radar system. The radar system in question is a complex and reparable technical object. It belongs to the group of technical equipment for which a short time of shutdowns is required (an ineffective use of the object. A DIAG computer program was used in the diagnosis process of the radar system. The final results obtained through computations conducted by the DIAG software have been presented in the Table 1.Defence Science Journal, 2009, 59(3, pp.305-313, DOI:http://dx.doi.org/10.14429/dsj.59.1526

  10. Artificial intelligence techniques for rational decision making

    CERN Document Server

    Marwala, Tshilidzi

    2014-01-01

    Develops insights into solving complex problems in engineering, biomedical sciences, social science and economics based on artificial intelligence. Some of the problems studied are in interstate conflict, credit scoring, breast cancer diagnosis, condition monitoring, wine testing, image processing and optical character recognition. The author discusses and applies the concept of flexibly-bounded rationality which prescribes that the bounds in Nobel Laureate Herbert Simon's bounded rationality theory are flexible due to advanced signal processing techniques, Moore's Law and artificial intellig

  11. Clinical techniques of artificial insemination in dogs.

    Science.gov (United States)

    Makloski, Chelsea L

    2012-05-01

    This article provides an overview of the current breeding techniques used in small animal reproduction today with an emphasis on artificial insemination techniques such as transvaginal and transcervical insemination as well as surgical deposition of semen in the uterus and oviduct. Breeding management and ovulation timing will be mentioned but are discussed in further detail in another article in this issue.

  12. Air Quality Forecasting through Different Statistical and Artificial Intelligence Techniques

    Science.gov (United States)

    Mishra, D.; Goyal, P.

    2014-12-01

    Urban air pollution forecasting has emerged as an acute problem in recent years because there are sever environmental degradation due to increase in harmful air pollutants in the ambient atmosphere. In this study, there are different types of statistical as well as artificial intelligence techniques are used for forecasting and analysis of air pollution over Delhi urban area. These techniques are principle component analysis (PCA), multiple linear regression (MLR) and artificial neural network (ANN) and the forecasting are observed in good agreement with the observed concentrations through Central Pollution Control Board (CPCB) at different locations in Delhi. But such methods suffers from disadvantages like they provide limited accuracy as they are unable to predict the extreme points i.e. the pollution maximum and minimum cut-offs cannot be determined using such approach. Also, such methods are inefficient approach for better output forecasting. But with the advancement in technology and research, an alternative to the above traditional methods has been proposed i.e. the coupling of statistical techniques with artificial Intelligence (AI) can be used for forecasting purposes. The coupling of PCA, ANN and fuzzy logic is used for forecasting of air pollutant over Delhi urban area. The statistical measures e.g., correlation coefficient (R), normalized mean square error (NMSE), fractional bias (FB) and index of agreement (IOA) of the proposed model are observed in better agreement with the all other models. Hence, the coupling of statistical and artificial intelligence can be use for the forecasting of air pollutant over urban area.

  13. Artificial Intrusion Detection Techniques: A Survey

    Directory of Open Access Journals (Sweden)

    Ashutosh Gupta

    2014-08-01

    Full Text Available Networking has become the most integral part of our cyber society. Everyone wants to connect themselves with each other. With the advancement of network technology, we find this most vulnerable to breach and take information and once information reaches to the wrong hands it can do terrible things. During recent years, number of attacks on networks have been increased which drew the attention of many researchers on this field. There have been many researches on intrusion detection lately. Many methods have been devised which are really very useful but they can only detect the attacks which already took place. These methods will always fail whenever there is a foreign attack which is not famous or which is new to the networking world. In order to detect new intrusions in the network, researchers have devised artificial intelligence technique for Intrusion detection prevention system. In this paper we are going to cover what types evolutionary techniques have been devised and their significance and modification.

  14. Volume Measurement in Solid Objects Using Artificial Vision Technique

    Science.gov (United States)

    Cordova-Fraga, T.; Martinez-Espinosa, J. C.; Bernal, J.; Huerta-Franco, R.; Sosa-Aquino, M.; Vargas-Luna, M.

    2004-09-01

    A simple system using artificial vision technique for measuring the volume of solid objects is described. The system is based on the acquisition of an image sequence of the object while it is rotating on an automated mechanism controlled by a PC. Volumes of different objects such as a sphere, a cylinder and also a carrot were measured. The proposed algorithm was developed in environment LabView 6.1. This technique can be very useful when it is applied to measure the human body for evaluating its body composition.

  15. Application of Artificial Intelligence Techniques in Unmanned Aerial Vehicle Flight

    Science.gov (United States)

    Bauer, Frank H. (Technical Monitor); Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in Artificial Intelligence (AI) at Nova southeastern University and as an adjunct to a project at NASA Goddard Space Flight Center's Wallops Flight Facility for a resilient, robust, and intelligent UAV flight control system. A method is outlined which allows a base level application for applying an AI method, Fuzzy Logic, to aspects of Control Logic for UAV flight. One element of UAV flight, automated altitude hold, has been implemented and preliminary results displayed. A low cost approach was taken using freeware, gnu, software, and demo programs. The focus of this research has been to outline some of the AI techniques used for UAV flight control and discuss some of the tools used to apply AI techniques. The intent is to succeed with the implementation of applying AI techniques to actually control different aspects of the flight of an UAV.

  16. Artificial Breeding Techniques of Whitmania pigra

    Institute of Scientific and Technical Information of China (English)

    Zhao; Nan; Xu; Ziliang

    2014-01-01

    The artificial breeding technology for juvenile of Whitmania pigra was introduced in the paper,including selection of sites and water quality,construction of spawning pool,hatching pool and escape proof facilities,key technology of leech selection,feeding,cocoon hatching,juvenile feeding and management.

  17. Operation optimization of distributed generation using artificial intelligent techniques

    Directory of Open Access Journals (Sweden)

    Mahmoud H. Elkazaz

    2016-06-01

    Full Text Available Future smart grids will require an observable, controllable and flexible network architecture for reliable and efficient energy delivery. The use of artificial intelligence and advanced communication technologies is essential in building a fully automated system. This paper introduces a new technique for online optimal operation of distributed generation (DG resources, i.e. a hybrid fuel cell (FC and photovoltaic (PV system for residential applications. The proposed technique aims to minimize the total daily operating cost of a group of residential homes by managing the operation of embedded DG units remotely from a control centre. The target is formed as an objective function that is solved using genetic algorithm (GA optimization technique. The optimal settings of the DG units obtained from the optimization process are sent to each DG unit through a fully automated system. The results show that the proposed technique succeeded in defining the optimal operating points of the DGs that affect directly the total operating cost of the entire system.

  18. FPGA controlled artificial vascular system

    Directory of Open Access Journals (Sweden)

    Laqua D.

    2015-09-01

    Full Text Available Monitoring the oxygen saturation of an unborn child is an invasive procedure, so far. Transabdominal fetal pulse oximetry is a promising method under research, used to estimate the oxygen saturation of a fetus noninvasively. Due to the nature of the method, the fetal information needs to be extracted from a mixed signal. To properly evaluate signal processing algorithms, a phantom modeling fetal and maternal blood circuits and tissue layers is necessary. This paper presents an improved hardware concept for an artificial vascular system, utilizing an FPGA based CompactRIO System from National Instruments. The experimental model to simulate the maternal and fetal blood pressure curve consists of two identical hydraulic circuits. Each of these circuits consists of a pre-pressure system and an artificial vascular system. Pulse curves are generated by proportional valves, separating these two systems. The dilation of the fetal and maternal artificial vessels in tissue substitutes is measured by transmissive and reflective photoplethysmography. The measurement results from the pressure sensors and the transmissive optical sensors are visualized to show the functionality of the pulse generating systems. The trigger frequency for the maternal valve was set to 1 per second, the fetal valve was actuated at 0.7 per second for validation. The reflective curve, capturing pulsations of the fetal and maternal circuit, was obtained with a high power LED (905 nm as light source. The results show that the system generates pulse curves, similar to its physiological equivalent. Further, the acquired reflective optical signal is modulated by the alternating diameter of the tubes of both circuits, allowing for tests of signal processing algorithms.

  19. Simulation Techniques and Prosthetic Approach Towards Biologically Efficient Artificial Sense Organs- An Overview

    CERN Document Server

    Neogi, Biswarup; Mukherjee, Soumyajit; Das, Achintya; Tibarewala, D N

    2011-01-01

    An overview of the applications of control theory to prosthetic sense organs including the senses of vision, taste and odor is being presented in this paper. Simulation aspect nowadays has been the centre of research in the field of prosthesis. There have been various successful applications of prosthetic organs, in case of natural biological organs dis-functioning patients. Simulation aspects and control modeling are indispensible for knowing system performance, and to generate an original approach of artificial organs. This overview focuses mainly on control techniques, by far a theoretical overview and fusion of artificial sense organs trying to mimic the efficacies of biologically active sensory organs. Keywords: virtual reality, prosthetic vision, artificial

  20. APPLYING ARTIFICIAL INTELLIGENCE TECHNIQUES TO HUMAN-COMPUTER INTERFACES

    DEFF Research Database (Denmark)

    Sonnenwald, Diane H.

    1988-01-01

    A description is given of UIMS (User Interface Management System), a system using a variety of artificial intelligence techniques to build knowledge-based user interfaces combining functionality and information from a variety of computer systems that maintain, test, and configure customer telephone...... and data networks. Three artificial intelligence (AI) techniques used in UIMS are discussed, namely, frame representation, object-oriented programming languages, and rule-based systems. The UIMS architecture is presented, and the structure of the UIMS is explained in terms of the AI techniques....

  1. Electronic artificial hand controlled by reconstructed digit

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    Objecive: To treat the loss of part of the forearm with a multi-dimension-freedom electronic artificial hand,which is controlled by a reconstructed finger transplanted from the second toe to the forearm stump.Methods: The female patient was 19 years old, whose right hand and wrist were crushed into pieces by machine at work and her forearm was amputated at the level of 8 cm proximal to the wrist. The second toe of her left foot was transplanted to reconstruct the digit onto the stump of her forearm. Two months after the transplantation, the patient was transferred to the rehabilitation center for further rehabilitation training, which consisted of: training for adaptation to weight bearing, testing and training of sensibility to weight. testing and training for stability of the hand, and testing and training for the controlling function of the reconstructed digit. Results: The transplanted toe survived well. After rehabilitation the reconstructed digit functioned well. In testing the performance under control mandate, the accuracy rate of the electronic artificial hand was 100%.Conclusions: A 100% accuracy rate of the electronic artificial hand can be achieved by transplantation of the toe onto the stump of the forearm. It provides a useful pathway and an example for improvement of control accuracy of a multiple-freedom electronic artificial hand and reduction of false action.

  2. Artificial Intelligence based technique for BTS placement

    Science.gov (United States)

    Alenoghena, C. O.; Emagbetere, J. O.; Aibinu, A. M.

    2013-12-01

    The increase of the base transceiver station (BTS) in most urban areas can be traced to the drive by network providers to meet demand for coverage and capacity. In traditional network planning, the final decision of BTS placement is taken by a team of radio planners, this decision is not fool proof against regulatory requirements. In this paper, an intelligent based algorithm for optimal BTS site placement has been proposed. The proposed technique takes into consideration neighbour and regulation considerations objectively while determining cell site. The application will lead to a quantitatively unbiased evaluated decision making process in BTS placement. An experimental data of a 2km by 3km territory was simulated for testing the new algorithm, results obtained show a 100% performance of the neighbour constrained algorithm in BTS placement optimization. Results on the application of GA with neighbourhood constraint indicate that the choices of location can be unbiased and optimization of facility placement for network design can be carried out.

  3. Performance of artificial neural networks and genetical evolved artificial neural networks unfolding techniques

    Energy Technology Data Exchange (ETDEWEB)

    Ortiz R, J. M. [Escuela Politecnica Superior, Departamento de Electrotecnia y Electronica, Avda. Menendez Pidal s/n, Cordoba (Spain); Martinez B, M. R.; Vega C, H. R. [Universidad Autonoma de Zacatecas, Unidad Academica de Estudios Nucleares, Calle Cipres No. 10, Fracc. La Penuela, 98068 Zacatecas (Mexico); Gallego D, E.; Lorente F, A. [Universidad Politecnica de Madrid, Departamento de Ingenieria Nuclear, ETSI Industriales, C. Jose Gutierrez Abascal 2, 28006 Madrid (Spain); Mendez V, R.; Los Arcos M, J. M.; Guerrero A, J. E., E-mail: morvymm@yahoo.com.m [CIEMAT, Laboratorio de Metrologia de Radiaciones Ionizantes, Avda. Complutense 22, 28040 Madrid (Spain)

    2011-02-15

    With the Bonner spheres spectrometer neutron spectrum is obtained through an unfolding procedure. Monte Carlo methods, Regularization, Parametrization, Least-squares, and Maximum Entropy are some of the techniques utilized for unfolding. In the last decade methods based on Artificial Intelligence Technology have been used. Approaches based on Genetic Algorithms and Artificial Neural Networks (Ann) have been developed in order to overcome the drawbacks of previous techniques. Nevertheless the advantages of Ann still it has some drawbacks mainly in the design process of the network, vg the optimum selection of the architectural and learning Ann parameters. In recent years the use of hybrid technologies, combining Ann and genetic algorithms, has been utilized to. In this work, several Ann topologies were trained and tested using Ann and Genetically Evolved Artificial Neural Networks in the aim to unfold neutron spectra using the count rates of a Bonner sphere spectrometer. Here, a comparative study of both procedures has been carried out. (Author)

  4. Chromatic changes to artificial irises produced using different techniques

    Science.gov (United States)

    Bannwart, Lisiane Cristina; Goiato, Marcelo Coelho; dos Santos, Daniela Micheline; Moreno, Amália; Pesqueira, Aldiéris Alves; Haddad, Marcela Filié; Andreotti, Agda Marobo; de Medeiros, Rodrigo Antonio

    2013-05-01

    Ocular prostheses are important determinants of their users' aesthetic recovery and self-esteem. Because of use, ocular prostheses longevity is strongly affected by instability of the iris color due to polymerization. The goal of this study is to examine how the color of the artificial iris button is affected by different techniques of artificial wear and by the application of varnish following polymerization of the colorless acrylic resin that covers the colored paint. We produce 60 samples (n=10) according to the wear technique applied: conventional technique without varnish (PE); conventional technique with varnish (PEV); technique involving a prefabricated cap without varnish (CA); technique involving a prefabricated cap with varnish (CAV); technique involving inverted painting without varnish (PI); and technique involving inverted painting with varnish (PIV). Color readings using a spectrophotometer are taken before and after polymerization. We submitted the data obtained to analyses of variance and Tukey's test (P<0.05). The color test shows significant changes after polymerization in all groups. The PE and PI techniques have clinically acceptable values of ΔE, independent of whether we apply varnish to protect the paint. The PI technique produces the least color change, whereas the PE and CA techniques significantly improve color stability.

  5. Artificial Intelligence for Controlling Robotic Aircraft

    Science.gov (United States)

    Krishnakumar, Kalmanje

    2005-01-01

    A document consisting mostly of lecture slides presents overviews of artificial-intelligence-based control methods now under development for application to robotic aircraft [called Unmanned Aerial Vehicles (UAVs) in the paper] and spacecraft and to the next generation of flight controllers for piloted aircraft. Following brief introductory remarks, the paper presents background information on intelligent control, including basic characteristics defining intelligent systems and intelligent control and the concept of levels of intelligent control. Next, the paper addresses several concepts in intelligent flight control. The document ends with some concluding remarks, including statements to the effect that (1) intelligent control architectures can guarantee stability of inner control loops and (2) for UAVs, intelligent control provides a robust way to accommodate an outer-loop control architecture for planning and/or related purposes.

  6. Solving Systems of Equations with Techniques from Artificial Intelligence

    Directory of Open Access Journals (Sweden)

    Irina Maria Terfaloaga

    2015-07-01

    Full Text Available A frequent problem in numerical analysis is solving the systems of equations. That problem has generated in time a great interest among mathematicians and computer scientists, as evidenced by the large number of numerical methods developed. Besides the classical numerical methods, in the last years were proposed methods inspired by techniques from artificial intelligence. Hybrid methods have been also proposed along the time [15, 19]. The goal of this study is to make a survey of methods inspired from artificial intelligence for solving systems of equations

  7. An integrated multivariable artificial pancreas control system.

    Science.gov (United States)

    Turksoy, Kamuran; Quinn, Lauretta T; Littlejohn, Elizabeth; Cinar, Ali

    2014-05-01

    The objective was to develop a closed-loop (CL) artificial pancreas (AP) control system that uses continuous measurements of glucose concentration and physiological variables, integrated with a hypoglycemia early alarm module to regulate glucose concentration and prevent hypoglycemia. Eleven open-loop (OL) and 9 CL experiments were performed. A multivariable adaptive artificial pancreas (MAAP) system was used for the first 6 CL experiments. An integrated multivariable adaptive artificial pancreas (IMAAP) system consisting of MAAP augmented with a hypoglycemia early alarm system was used during the last 3 CL experiments. Glucose values and physical activity information were measured and transferred to the controller every 10 minutes and insulin suggestions were entered to the pump manually. All experiments were designed to be close to real-life conditions. Severe hypoglycemic episodes were seen several times during the OL experiments. With the MAAP system, the occurrence of severe hypoglycemia was decreased significantly (P < .01). No hypoglycemia was seen with the IMAAP system. There was also a significant difference (P < .01) between OL and CL experiments with regard to percentage of glucose concentration (54% vs 58%) that remained within target range (70-180 mg/dl). Integration of an adaptive control and hypoglycemia early alarm system was able to keep glucose concentration values in target range in patients with type 1 diabetes. Postprandial hypoglycemia and exercise-induced hypoglycemia did not occur when this system was used. Physical activity information improved estimation of the blood glucose concentration and effectiveness of the control system.

  8. Controlling Functional Group Architecture in Artificial Cells

    Science.gov (United States)

    2015-07-02

    further enable enzyme encapsulation to improve the efficiency of light-driven hydrogen fuel production. 5. Changes in key personnel, if applicable : -None ...Controlling Functional Group Architecture in Artificial Cells 5a. CONTRACT NUMBER W9132T-14-2-0002 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...cycloadditions to modify reactive groups within the phospholipid membrane structure and how the nature of the reactive elements, the copper catalyst

  9. A quality by design approach using artificial intelligence techniques to control the critical quality attributes of ramipril tablets manufactured by wet granulation.

    Science.gov (United States)

    Aksu, Buket; Paradkar, Anant; de Matas, Marcel; Özer, Özgen; Güneri, Tamer; York, Peter

    2013-02-01

    Quality by design (QbD) is an essential part of the modern approach to pharmaceutical quality. This study was conducted in the framework of a QbD project involving ramipril tablets. Preliminary work included identification of the critical quality attributes (CQAs) and critical process parameters (CPPs) based on the quality target product profiles (QTPPs) using the historical data and risk assessment method failure mode and effect analysis (FMEA). Compendial and in-house specifications were selected as QTPPs for ramipril tablets. CPPs that affected the product and process were used to establish an experimental design. The results thus obtained can be used to facilitate definition of the design space using tools such as design of experiments (DoE), the response surface method (RSM) and artificial neural networks (ANNs). The project was aimed at discovering hidden knowledge associated with the manufacture of ramipril tablets using a range of artificial intelligence-based software, with the intention of establishing a multi-dimensional design space that ensures consistent product quality. At the end of the study, a design space was developed based on the study data and specifications, and a new formulation was optimized. On the basis of this formulation, a new laboratory batch formulation was prepared and tested. It was confirmed that the explored formulation was within the design space.

  10. Measuring strategic control in artificial grammar learning.

    Science.gov (United States)

    Norman, Elisabeth; Price, Mark C; Jones, Emma

    2011-12-01

    In response to concerns with existing procedures for measuring strategic control over implicit knowledge in artificial grammar learning (AGL), we introduce a more stringent measurement procedure. After two separate training blocks which each consisted of letter strings derived from a different grammar, participants either judged the grammaticality of novel letter strings with respect to only one of these two grammars (pure-block condition), or had the target grammar varying randomly from trial to trial (novel mixed-block condition) which required a higher degree of conscious flexible control. Random variation in the colour and font of letters was introduced to disguise the nature of the rule and reduce explicit learning. Strategic control was observed both in the pure-block and mixed-block conditions, and even among participants who did not realise the rule was based on letter identity. This indicated detailed strategic control in the absence of explicit learning.

  11. Inspection of an artificial heart by the neutron radiography technique

    CERN Document Server

    Pugliesi, R; Andrade, M L G; Menezes, M O; Pereira, M A S; Maizato, M J S

    1999-01-01

    The neutron radiography technique was employed to inspect an artificial heart prototype which is being developed to provide blood circulation for patients expecting heart transplant surgery. The radiographs have been obtained by the direct method with a gadolinium converter screen along with the double coated Kodak-AA emulsion film. The artificial heart consists of a flexible plastic membrane located inside a welded metallic cavity, which is employed for blood pumping purposes. The main objective of the present inspection was to identify possible damages in this plastic membrane, produced during the welding process of the metallic cavity. The obtained radiographs were digitized as well as analysed in a PC and the improved images clearly identify several damages in the plastic membrane, suggesting changes in the welding process.

  12. Artificial proprioceptive feedback for myoelectric control.

    Science.gov (United States)

    Pistohl, Tobias; Joshi, Deepak; Ganesh, Gowrishankar; Jackson, Andrew; Nazarpour, Kianoush

    2015-05-01

    The typical control of myoelectric interfaces, whether in laboratory settings or real-life prosthetic applications, largely relies on visual feedback because proprioceptive signals from the controlling muscles are either not available or very noisy. We conducted a set of experiments to test whether artificial proprioceptive feedback, delivered noninvasively to another limb, can improve control of a two-dimensional myoelectrically-controlled computer interface. In these experiments, participants were required to reach a target with a visual cursor that was controlled by electromyogram signals recorded from muscles of the left hand, while they were provided with an additional proprioceptive feedback on their right arm by moving it with a robotic manipulandum. Provision of additional artificial proprioceptive feedback improved the angular accuracy of their movements when compared to using visual feedback alone but did not increase the overall accuracy quantified with the average distance between the cursor and the target. The advantages conferred by proprioception were present only when the proprioceptive feedback had similar orientation to the visual feedback in the task space and not when it was mirrored, demonstrating the importance of congruency in feedback modalities for multi-sensory integration. Our results reveal the ability of the human motor system to learn new inter-limb sensory-motor associations; the motor system can utilize task-related sensory feedback, even when it is available on a limb distinct from the one being actuated. In addition, the proposed task structure provides a flexible test paradigm by which the effectiveness of various sensory feedback and multi-sensory integration for myoelectric prosthesis control can be evaluated.

  13. Implementation and Validation of Artificial Intelligence Techniques for Robotic Surgery

    Directory of Open Access Journals (Sweden)

    Aarshay Jain

    2014-03-01

    Full Text Available The primary focus of this study is implementation of Artificial Intelligence (AI technique for developing an inverse kinematics solution for the Raven-IITM surgical research robot [1]. First, the kinematic model of the Raven-IITM robot was analysed along with the proposed analytical solution [2] for inverse kinematics problem. Next, The Artificial Neural Network (ANN techniques was implemented. The training data for the same was careful selected by keeping manipulability constraints in mind. Finally, the results were verified using elliptical trajectories. The originally proposed analytical solution was found to be computationally inefficient, gave multiple solutions and its existence necessitates the use of the Standard Raven-IITM Tool [2]. The solution devised using ANN technique gave a single solution which was thirteen times faster than the original solution. Moreover, it is generic in nature and can be used for any type of tool. Thus, a novel solution for solving the inverse kinematics problem of the Raven-II surgical robot was formulated and confirmed.

  14. Artificial intelligence techniques for scheduling Space Shuttle missions

    Science.gov (United States)

    Henke, Andrea L.; Stottler, Richard H.

    1994-01-01

    Planning and scheduling of NASA Space Shuttle missions is a complex, labor-intensive process requiring the expertise of experienced mission planners. We have developed a planning and scheduling system using combinations of artificial intelligence knowledge representations and planning techniques to capture mission planning knowledge and automate the multi-mission planning process. Our integrated object oriented and rule-based approach reduces planning time by orders of magnitude and provides planners with the flexibility to easily modify planning knowledge and constraints without requiring programming expertise.

  15. An Artificial Neural Network Control System for Spacecraft Attitude Stabilization

    Science.gov (United States)

    1990-06-01

    NAVAL POSTGRADUATE SCHOOL Monterey, California ’-DTIC 0 ELECT f NMARO 5 191 N S, U, THESIS B . AN ARTIFICIAL NEURAL NETWORK CONTROL SYSTEM FOR...NO. NO. NO ACCESSION NO 11. TITLE (Include Security Classification) AN ARTIFICIAL NEURAL NETWORK CONTROL SYSTEM FOR SPACECRAFT ATTITUDE STABILIZATION...obsolete a U.S. G v pi.. iim n P.. oiice! toog-eo.5s43 i Approved for public release; distribution is unlimited. AN ARTIFICIAL NEURAL NETWORK CONTROL

  16. Artificial intelligence techniques for embryo and oocyte classification.

    Science.gov (United States)

    Manna, Claudio; Nanni, Loris; Lumini, Alessandra; Pappalardo, Sebastiana

    2013-01-01

    One of the most relevant aspects in assisted reproduction technology is the possibility of characterizing and identifying the most viable oocytes or embryos. In most cases, embryologists select them by visual examination and their evaluation is totally subjective. Recently, due to the rapid growth in the capacity to extract texture descriptors from a given image, a growing interest has been shown in the use of artificial intelligence methods for embryo or oocyte scoring/selection in IVF programmes. This work concentrates the efforts on the possible prediction of the quality of embryos and oocytes in order to improve the performance of assisted reproduction technology, starting from their images. The artificial intelligence system proposed in this work is based on a set of Levenberg-Marquardt neural networks trained using textural descriptors (the local binary patterns). The proposed system was tested on two data sets of 269 oocytes and 269 corresponding embryos from 104 women and compared with other machine learning methods already proposed in the past for similar classification problems. Although the results are only preliminary, they show an interesting classification performance. This technique may be of particular interest in those countries where legislation restricts embryo selection. One of the most relevant aspects in assisted reproduction technology is the possibility of characterizing and identifying the most viable oocytes or embryos. In most cases, embryologists select them by visual examination and their evaluation is totally subjective. Recently, due to the rapid growth in our capacity to extract texture descriptors from a given image, a growing interest has been shown in the use of artificial intelligence methods for embryo or oocyte scoring/selection in IVF programmes. In this work, we concentrate our efforts on the possible prediction of the quality of embryos and oocytes in order to improve the performance of assisted reproduction technology

  17. Development of a Car Racing Simulator Game Using Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Marvin T. Chan

    2015-01-01

    Full Text Available This paper presents a car racing simulator game called Racer, in which the human player races a car against three game-controlled cars in a three-dimensional environment. The objective of the game is not to defeat the human player, but to provide the player with a challenging and enjoyable experience. To ensure that this objective can be accomplished, the game incorporates artificial intelligence (AI techniques, which enable the cars to be controlled in a manner that mimics natural driving. The paper provides a brief history of AI techniques in games, presents the use of AI techniques in contemporary video games, and discusses the AI techniques that were implemented in the development of Racer. A comparison of the AI techniques implemented in the Unity platform with traditional AI search techniques is also included in the discussion.

  18. SMS Spam Filtering Technique Based on Artificial Immune System

    Directory of Open Access Journals (Sweden)

    Tarek M Mahmoud

    2012-03-01

    Full Text Available The Short Message Service (SMS have an important economic impact for end users and service providers. Spam is a serious universal problem that causes problems for almost all users. Several studies have been presented, including implementations of spam filters that prevent spam from reaching their destination. Nave Bayesian algorithm is one of the most effective approaches used in filtering techniques. The computational power of smart phones are increasing, making increasingly possible to perform spam filtering at these devices as a mobile agent application, leading to better personalization and effectiveness. The challenge of filtering SMS spam is that the short messages often consist of few words composed of abbreviations and idioms. In this paper, we propose an anti-spam technique based on Artificial Immune System (AIS for filtering SMS spam messages. The proposed technique utilizes a set of some features that can be used as inputs to spam detection model. The idea is to classify message using trained dataset that contains Phone Numbers, Spam Words, and Detectors. Our proposed technique utilizes a double collection of bulk SMS messages Spam and Ham in the training process. We state a set of stages that help us to build dataset such as tokenizer, stop word filter, and training process. Experimental results presented in this paper are based on iPhone Operating System (iOS. The results applied to the testing messages show that the proposed system can classify the SMS spam and ham with accurate compared with Nave Bayesian algorithm.

  19. Intrusion Detection Systems Based on Artificial Intelligence Techniques in Wireless Sensor Networks

    OpenAIRE

    2013-01-01

    Intrusion detection system (IDS) is regarded as the second line of defense against network anomalies and threats. IDS plays an important role in network security. There are many techniques which are used to design IDSs for specific scenario and applications. Artificial intelligence techniques are widely used for threats detection. This paper presents a critical study on genetic algorithm, artificial immune, and artificial neural network (ANN) based IDSs techniques used in wireless sensor netw...

  20. Continuous Control Artificial Potential Function Methods and Optimal Control

    Science.gov (United States)

    2014-03-27

    Method, namely r̈VDSVAPF = −K̇SKR∇φ−KSK̇R∇φ−KSKRH(φ)ṙ −KD (KSKR∇φ+ ṙ) . The above dynamics are very nonlinear due to the trigonometric functions (inside...constraints (on KS and θ) and the deletion of trigonometric functions . The suspected reasons for the larger computa- tional expense are twofold. First, this...Continuous Control Artificial Potential Function Methods and Optimal Control THESIS R. Andrew Fields, Civ, USAF AFIT-ENY-14-M-20 DEPARTMENT OF THE

  1. Parameter tuning of PVD process based on artificial intelligence technique

    Science.gov (United States)

    Norlina, M. S.; Diyana, M. S. Nor; Mazidah, P.; Rusop, M.

    2016-07-01

    In this study, an artificial intelligence technique is proposed to be implemented in the parameter tuning of a PVD process. Due to its previous adaptation in similar optimization problems, genetic algorithm (GA) is selected to optimize the parameter tuning of the RF magnetron sputtering process. The most optimized parameter combination obtained from GA's optimization result is expected to produce the desirable zinc oxide (ZnO) thin film from the sputtering process. The parameters involved in this study were RF power, deposition time and substrate temperature. The algorithm was tested to optimize the 25 datasets of parameter combinations. The results from the computational experiment were then compared with the actual result from the laboratory experiment. Based on the comparison, GA had shown that the algorithm was reliable to optimize the parameter combination before the parameter tuning could be done to the RF magnetron sputtering machine. In order to verify the result of GA, the algorithm was also been compared to other well known optimization algorithms, which were, particle swarm optimization (PSO) and gravitational search algorithm (GSA). The results had shown that GA was reliable in solving this RF magnetron sputtering process parameter tuning problem. GA had shown better accuracy in the optimization based on the fitness evaluation.

  2. Macrocell path loss prediction using artificial intelligence techniques

    Science.gov (United States)

    Usman, Abraham U.; Okereke, Okpo U.; Omizegba, Elijah E.

    2014-04-01

    The prediction of propagation loss is a practical non-linear function approximation problem which linear regression or auto-regression models are limited in their ability to handle. However, some computational Intelligence techniques such as artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFISs) have been shown to have great ability to handle non-linear function approximation and prediction problems. In this study, the multiple layer perceptron neural network (MLP-NN), radial basis function neural network (RBF-NN) and an ANFIS network were trained using actual signal strength measurement taken at certain suburban areas of Bauchi metropolis, Nigeria. The trained networks were then used to predict propagation losses at the stated areas under differing conditions. The predictions were compared with the prediction accuracy of the popular Hata model. It was observed that ANFIS model gave a better fit in all cases having higher R2 values in each case and on average is more robust than MLP and RBF models as it generalises better to a different data.

  3. Advanced Wavefront Control Techniques

    Energy Technology Data Exchange (ETDEWEB)

    Olivier, S S; Brase, J M; Avicola, K; Thompson, C A; Kartz, M W; Winters, S; Hartley, R; Wihelmsen, J; Dowla, F V; Carrano, C J; Bauman, B J; Pennington, D M; Lande, D; Sawvel, R M; Silva, D A; Cooke, J B; Brown, C G

    2001-02-21

    Programs at LLNL that involve large laser systems--ranging from the National Ignition Facility to new tactical laser weapons--depend on the maintenance of laser beam quality through precise control of the optical wavefront. This can be accomplished using adaptive optics, which compensate for time-varying aberrations that are often caused by heating in a high-power laser system. Over the past two decades, LLNL has developed a broad capability in adaptive optics technology for both laser beam control and high-resolution imaging. This adaptive optics capability has been based on thin deformable glass mirrors with individual ceramic actuators bonded to the back. In the case of high-power lasers, these adaptive optics systems have successfully improved beam quality. However, as we continue to extend our applications requirements, the existing technology base for wavefront control cannot satisfy them. To address this issue, this project studied improved modeling tools to increase our detailed understanding of the performance of these systems, and evaluated novel approaches to low-order wavefront control that offer the possibility of reduced cost and complexity. We also investigated improved beam control technology for high-resolution wavefront control. Many high-power laser systems suffer from high-spatial-frequency aberrations that require control of hundreds or thousands of phase points to provide adequate correction. However, the cost and size of current deformable mirrors can become prohibitive for applications requiring more than a few tens of phase control points. New phase control technologies are becoming available which offer control of many phase points with small low-cost devices. The goal of this project was to expand our wavefront control capabilities with improved modeling tools, new devices that reduce system cost and complexity, and extensions to high spatial and temporal frequencies using new adaptive optics technologies. In FY 99, the second year of

  4. The Thoratec system implanted as a modified total artificial heart: the Bad Oeynhausen technique.

    Science.gov (United States)

    Arusoglu, Latif; Reiss, Nils; Morshuis, Michiel; Schoenbrodt, Michael; Hakim-Meibodi, Kavous; Gummert, Jan

    2010-12-01

    The CardioWest™ total artificial heart (SynCardia Systems, Tuscon, AZ, USA) is the only FDA-approved total artificial heart determined as a bridge to human heart transplantation for patients dying of biventricular heart failure. Implantation provides immediate hemodynamic restoration and clinical stabilization, leading to end-organ recovery and thus eventually allowing cardiac transplantation. Occasionally, implantation of a total artificial heart is not feasible for anatomical reasons. For this patient group, we have developed an alternative technique using the paracorporeal Thoratec biventricular support system (Thoratec, Pleasanton, CA, USA) as a modified total artificial heart. A detailed description of the implantation technique is presented.

  5. Statistical Techniques for Project Control

    CERN Document Server

    Badiru, Adedeji B

    2012-01-01

    A project can be simple or complex. In each case, proven project management processes must be followed. In all cases of project management implementation, control must be exercised in order to assure that project objectives are achieved. Statistical Techniques for Project Control seamlessly integrates qualitative and quantitative tools and techniques for project control. It fills the void that exists in the application of statistical techniques to project control. The book begins by defining the fundamentals of project management then explores how to temper quantitative analysis with qualitati

  6. Electrowetting-controlled bio-inspired artificial iridophores

    Science.gov (United States)

    Manakasettharn, Supone; Taylor, J. Ashley; Krupenkin, Tom

    2011-10-01

    Many marine organisms have evolved complex optical mechanisms of dynamic skin color control that allow them to drastically change their visual appearance. In particular, cephalopods have developed especially effective dynamic color control mechanism based on the mechanical actuation of the micro-scale optical structures, which produce either variable degrees of area coverage by a given color (chromatophores) or variations in spatial orientation of the reflective and diffractive surfaces (iridophores). In this work we describe the design, fabrication and characterization of electrowetting-controlled bio-inspired artificial iridophores. The developed iridophores geometrically resemble microflowers with flexible reflective petals. The microflowers are fabricated on a silicon substrate using surface micromachining techniques. After fabrication a small droplet of conductive liquid is deposited at the center of each microflower. This causes the flower petals to partially wrap around the droplet forming a structure similar to capillary origami. The dynamic control over the degree of wrapping is achieved by applying a voltage differential between the conductive core of the petals and the droplet. The applied voltage causes dynamic contact angle change between the droplet and each of the petals due to the electrowetting effect. We have characterized mechanical and optical properties of the microstructures and discuss their electrowetting-based actuation. These experimental results are in good agreement with a 3D theoretical model based on electrocapillarity and elasticity theory. This work forms the basis for a broad range of novel optical devices.

  7. Artificial Neural Networks Based Modeling and Control of Continuous Stirred Tank Reactor

    Directory of Open Access Journals (Sweden)

    R. S.M.N. Malar

    2009-01-01

    Full Text Available Continuous Stirred Tank Reactor (CSTR is one of the common reactors in chemical plant. Problem statement: Developing a model incorporating the nonlinear dynamics of the system warrants lot of computation. An efficient control of the product concentration can be achieved only through accurate model. Approach: In this study, attempts were made to alleviate the above mentioned problem using “Artificial Intelligence” (AI techniques. One of the AI techniques namely Artificial Neural Networks (ANN was used to model the CSTR incorporating its non-linear characteristics. Two nonlinear models based control strategies namely internal model control and direct inverse control were designed using the neural networks and applied to the control of isothermal CSTR. Results: The simulation results for the above control schemes with set point tracking were presented. Conclusion: Results indicated that neural networks can learn accurate models and give good non-linear control when model equations are not known.

  8. An Efficient Technique to Implement Similarity Measures in Text Document Clustering using Artificial Neural Networks Algorithm

    Directory of Open Access Journals (Sweden)

    K. Selvi

    2014-12-01

    Full Text Available Pattern recognition, envisaging supervised and unsupervised method, optimization, associative memory and control process are some of the diversified troubles that can be resolved by artificial neural networks. Problem identified: Of late, discovering the required information in massive quantity of data is the challenging tasks. The model of similarity evaluation is the central element in accomplishing a perceptive of variables and perception that encourage behavior and mediate concern. This study proposes Artificial Neural Networks algorithms to resolve similarity measures. In order to apply singular value decomposition the frequency of word pair is established in the given document. (1 Tokenization: The splitting up of a stream of text into words, phrases, signs, or other significant parts is called tokenization. (2 Stop words: Preceding or succeeding to processing natural language data, the words that are segregated is called stop words. (3 Porter stemming: The main utilization of this algorithm is as part of a phrase normalization development that is characteristically completed while setting up in rank recovery technique. (4 WordNet: The compilation of lexical data base for the English language is called as WordNet Based on Artificial Neural Networks, the core part of this study work extends n-gram proposed algorithm. All the phonemes, syllables, letters, words or base pair corresponds in accordance to the application. Future work extends the application of this same similarity measures in various other neural network algorithms to accomplish improved results.

  9. Myoelectric control of artificial limb inspired by quantum information processing

    Science.gov (United States)

    Siomau, Michael; Jiang, Ning

    2015-03-01

    Precise and elegant coordination of a prosthesis across many degrees of freedom represents a significant challenge to efficient rehabilitation of people with limb deficiency. Processing the electrical neural signals collected from the surface of the remnant muscles of the stump is a common way to initiate and control the different movements available to the artificial limb. Based on the assumption that there are distinguishable and repeatable signal patterns among different types of muscular activation, the problem of prosthesis control reduces to one of pattern recognition. Widely accepted classical methods for pattern recognition, however, cannot provide simultaneous and proportional control of the artificial limb. Here we show that, in principle, quantum information processing of the neural signals allows us to overcome the above-mentioned difficulties, suggesting a very simple scheme for myoelectric control of artificial limb with advanced functionalities.

  10. Artificial Intelligence Theory and Reconfigurable Control Systems.

    Science.gov (United States)

    1984-06-30

    IEEE Transactions on Automatic Control , Vol...AC-iS, No. 1, Feb 1970. 5. Sklansky, J., "Learning Systems for Automatic Control", IEEE = Transactions on Automatic Control , Vol...34A Gerfcale itellihoode Raio ,-. ~Aproc tohemesecio and Ca Suis nwEtimat eeion" (: Jump in-Linea & -,"Ŗ. Systems", IEEE Transactions on Automatic Control ,

  11. Techniques of Image Processing Based on Artificial Neural Networks

    Institute of Scientific and Technical Information of China (English)

    LI Wei-qing; WANG Qun; WANG Cheng-biao

    2006-01-01

    This paper presented an online quality inspection system based on artificial neural networks. Chromatism classification and edge detection are two difficult problems in glass steel surface quality inspection. Two artificial neural networks were made and the two problems were solved. The one solved chromatism classification. Hue,saturation and their probability of three colors, whose appearing probabilities were maximum in color histogram,were selected as input parameters, and the number of output node could be adjusted with the change of requirement. The other solved edge detection. In this neutral network, edge detection of gray scale image was able to be tested with trained neural networks for a binary image. It prevent the difficulty that the number of needed training samples was too large if gray scale images were directly regarded as training samples. This system is able to be applied to not only glass steel fault inspection but also other product online quality inspection and classification.

  12. Myoelectric Control of Artificial Limb by Quantum Information Processing

    CERN Document Server

    Siomau, Michael

    2013-01-01

    Precise and elegant coordination of a prosthesis across many degrees of freedom is highly desired for rehabilitation of people with limb deficiency. Processing the electrical neural signals, collected from the surface of the remnant muscles of the stump, is a common way to activate certain function of the artificial limb. Based on the assumption that there are distinguishable and repeatable signal patterns among different types of muscular activation, the problem of the prosthesis control reduces to the pattern recognition. Widely accepted classical methods for pattern recognition, however, can not provide simultaneous and proportional control of the artificial limb. Here we show that quantum information processing of the neural signals allows us to overcome above difficulties suggesting a very simple scheme for myoelectric control of artificial limb with advanced functionalities.

  13. Study on optimization control method based on artificial neural network

    Institute of Scientific and Technical Information of China (English)

    FU Hua; SUN Shao-guang; XU Zhen-Iiang

    2005-01-01

    In the goal optimization and control optimization process the problems with common artificial neural network algorithm are unsure convergence, insufficient post-training network precision, and slow training speed, in which partial minimum value question tends to occur. This paper conducted an in-depth study on the causes of the limitations of the algorithm, presented a rapid artificial neural network algorithm, which is characterized by integrating multiple algorithms and by using their complementary advantages. The salient feature of the method is self-organization, which can effectively prevent the optimized results from tending to be partial minimum values. Overall optimization can be achieved with this method, goal function can be searched for in overall scope. With optimization control of coal mine ventilator as a practical application, the paper proves that by integrating multiple artificial neural network algorithms, best control optimization and goal optimized can be achieved.

  14. Modeling of the height control system using artificial neural networks

    Directory of Open Access Journals (Sweden)

    A. R Tahavvor

    2016-09-01

    action. The mechanical parts were computer-generated by engineering software in assembled, exploded and standard two-dimensional drawing required for the manufacturing process. Carrier and framework of control unit and actuator mainly designed to have the capability to support and hold the hardware and sensor assembly in an easy mountable fashion. This arrangement performed feasibility of the movement and allocating of control unit along the travel length of belt above the conveyor unit. In this work a multilayer perceptron network with different training algorithm was used and it is found that the backpropagation algorithm with Levenberge-Marquardt learning rule was the best choice for this analysis because of the accurate and faster training procedure. The Levenberg-Marquardt algorithm was an iterative technique that locates the minimum of a multivariate function that was expressed as the sum of squares of nonlinear real-valued functions. It has become a standard technique for non-linear least-squares problems, widely adopted in a broad spectrum of disciplines. LM can be thought of as a combination of steepest descent and the Gauss-Newton method. When the current solution was far from the correct one, the algorithm behaves like a steepest descent method: slow, but guaranteed to converge. When the current solution is close to the correct solution, it becomes a Gauss-Newton method. The Levenberg algorithm is: 1. Do an update as directed by the rule above. 2. Evaluate the error at the new parameter vector. 3. If the error has increased as a result the update, then retract the step (i.e. reset the weights to their previous values and increase l by a factor of 10 or some such significant factor, then goes to (1 and try an update again. 4. If the error has decreased as a result of the update, then accept the step (i.e. keep the weights at their new values and decrease l by a factor of 10 or so. Results and Discussion The study of multi artificial neural network learning

  15. Control system for an artificial heart

    Science.gov (United States)

    Gebben, V. D.; Webb, J. A., Jr.

    1970-01-01

    Inexpensive industrial pneumatic components are combined to produce control system to drive sac-type heart-assistance blood pump with controlled pulsatile pressure that makes pump rate of flow sensitive to venous /atrial/ pressure, while stroke is centered about set operating point and pump is synchronized with natural heart.

  16. Control system for solar tracking based on artificial vision; Sistema de control para seguimiento solar basado en vision artificial

    Energy Technology Data Exchange (ETDEWEB)

    Pacheco Ramirez, Jesus Horacio; Anaya Perez, Maria Elena; Benitez Baltazar, Victor Hugo [Universidad de onora, Hermosillo, Sonora (Mexico)]. E-mail: jpacheco@industrial.uson.mx; meanaya@industrial.uson.mx; vbenitez@industrial.uson.mx

    2010-11-15

    This work shows how artificial vision feedback can be applied to control systems. The control is applied to a solar panel in order to track the sun position. The algorithms to calculate the position of the sun and the image processing are developed in LabView. The responses obtained from the control show that it is possible to use vision for a control scheme in closed loop. [Spanish] El presente trabajo muestra la manera en la cual un sistema de control puede ser retroalimentado mediante vision artificial. El control es aplicado en un panel solar para realizar el seguimiento del sol a lo largo del dia. Los algoritmos para calcular la posicion del sol y para el tratamiento de la imagen fueron desarrollados en LabView. Las respuestas obtenidas del control muestran que es posible utilizar vision para un esquema de control en lazo cerrado.

  17. ARTIFICIAL INTELLIGENCE PLANNING TECHNIQUES FOR ADAPTIVE VIRTUAL COURSE CONSTRUCTION

    Directory of Open Access Journals (Sweden)

    NÉSTOR DARÍO DUQUE

    2011-01-01

    Full Text Available El artículo tiene como objetivo proponer un modelo de planificación para la adaptación de cursos virtuales, basado en técnicas de inteligencia artificial, en particular usando el enfoque de sistema multi-agente (SMA y métodos de planificación en inteligencia artificial. El diseño y la implementación por medio de un SMA pedagógico y la definición de un framework para especificar la estrategia de adaptación permiten incorporar diversos enfoques pedagógicos y tecnológicos, de acuerdo a los puntos de vista del equipo de trabajo, lo cual resulta en una implementación e instalación concreta. Se incorpora un novedoso pre-planificador que permite la transparencia y la neutralidad en el modelo propuesto y también ofrece soporte para traducir los elementos del curso a las especificaciones de un problema de planificación. La última sección muestra la plataforma experimental SICAD + (Sistema Inteligente de Cursos ADaptativos, a través de un enfoque multiagente, que valida el modelo propuesto.

  18. Artificial Intelligence Techniques for Automatic Screening of Amblyogenic Factors

    Science.gov (United States)

    Van Eenwyk, Jonathan; Agah, Arvin; Giangiacomo, Joseph; Cibis, Gerhard

    2008-01-01

    Purpose To develop a low-cost automated video system to effectively screen children aged 6 months to 6 years for amblyogenic factors. Methods In 1994 one of the authors (G.C.) described video vision development assessment, a digitizable analog video-based system combining Brückner pupil red reflex imaging and eccentric photorefraction to screen young children for amblyogenic factors. The images were analyzed manually with this system. We automated the capture of digital video frames and pupil images and applied computer vision and artificial intelligence to analyze and interpret results. The artificial intelligence systems were evaluated by a tenfold testing method. Results The best system was the decision tree learning approach, which had an accuracy of 77%, compared to the “gold standard” specialist examination with a “refer/do not refer” decision. Criteria for referral were strabismus, including microtropia, and refractive errors and anisometropia considered to be amblyogenic. Eighty-two percent of strabismic individuals were correctly identified. High refractive errors were also correctly identified and referred 90% of the time, as well as significant anisometropia. The program was less correct in identifying more moderate refractive errors, below +5 and less than −7. Conclusions Although we are pursuing a variety of avenues to improve the accuracy of the automated analysis, the program in its present form provides acceptable cost benefits for detecting ambylogenic factors in children aged 6 months to 6 years. PMID:19277222

  19. Comparison of Artificial Intelligence Techniques for river flow forecasting

    Directory of Open Access Journals (Sweden)

    M. Firat

    2008-01-01

    Full Text Available The use of Artificial Intelligence methods is becoming increasingly common in the modeling and forecasting of hydrological and water resource processes. In this study, applicability of Adaptive Neuro Fuzzy Inference System (ANFIS and Artificial Neural Network (ANN methods, Generalized Regression Neural Networks (GRNN and Feed Forward Neural Networks (FFNN, and Auto-Regressive (AR models for forecasting of daily river flow is investigated and Seyhan River and Cine River was chosen as case study area. For the Seyhan River, the forecasting models are established using combinations of antecedent daily river flow records. On the other hand, for the Cine River, daily river flow and rainfall records are used in input layer. For both stations, the data sets are divided into three subsets, training, testing and verification data set. The river flow forecasting models having various input structures are trained and tested to investigate the applicability of ANFIS and ANN and AR methods. The results of all models for both training and testing are evaluated and the best fit input structures and methods for both stations are determined according to criteria of performance evaluation. Moreover the best fit forecasting models are also verified by verification set which was not used in training and testing processes and compared according to criteria. The results demonstrate that ANFIS model is superior to the GRNN and FFNN forecasting models, and ANFIS can be successfully applied and provide high accuracy and reliability for daily river flow forecasting.

  20. Voice-Controlled Artificial Handspeak System

    Directory of Open Access Journals (Sweden)

    Carlo Fonda

    2014-01-01

    Full Text Available A man-machine interaction project is described which aims to establish an automated voice to sign language translator for communication with the deaf using integrated open technologies. The first prototype consists of a robotic hand designed with OpenSCAD and manufactured with a low-cost 3D printer ─which smoothly reproduces the alphabet of the sign language controlled by voice only. The core automation comprises an Arduino UNO controller used to activate a set of servo motors that follow instructions from a Raspberry Pi mini-computer having installed the open source speech recognition engine Julius. We discuss its features, limitations and possible future developments.

  1. Power system stabilizers based on modern control techniques

    Energy Technology Data Exchange (ETDEWEB)

    Malik, O.P.; Chen, G.P.; Zhang, Y.; El-Metwally, K. [Calgary Univ., AB (Canada). Dept. of Electrical and Computer Engineering

    1994-12-31

    Developments in digital technology have made it feasible to develop and implement improved controllers based on sophisticated control techniques. Power system stabilizers based on adaptive control, fuzzy logic and artificial networks are being developed. Each of these control techniques possesses unique features and strengths. In this paper, the relative performance of power systems stabilizers based on adaptive control, fuzzy logic and neural network, both in simulation studies and real time tests on a physical model of a power system, is presented and compared to that of a fixed parameter conventional power system stabilizer. (author) 16 refs., 45 figs., 3 tabs.

  2. Improved Space Surveillance Network (SSN) Scheduling using Artificial Intelligence Techniques

    Science.gov (United States)

    Stottler, D.

    There are close to 20,000 cataloged manmade objects in space, the large majority of which are not active, functioning satellites. These are tracked by phased array and mechanical radars and ground and space-based optical telescopes, collectively known as the Space Surveillance Network (SSN). A better SSN schedule of observations could, using exactly the same legacy sensor resources, improve space catalog accuracy through more complementary tracking, provide better responsiveness to real-time changes, better track small debris in low earth orbit (LEO) through efficient use of applicable sensors, efficiently track deep space (DS) frequent revisit objects, handle increased numbers of objects and new types of sensors, and take advantage of future improved communication and control to globally optimize the SSN schedule. We have developed a scheduling algorithm that takes as input the space catalog and the associated covariance matrices and produces a globally optimized schedule for each sensor site as to what objects to observe and when. This algorithm is able to schedule more observations with the same sensor resources and have those observations be more complementary, in terms of the precision with which each orbit metric is known, to produce a satellite observation schedule that, when executed, minimizes the covariances across the entire space object catalog. If used operationally, the results would be significantly increased accuracy of the space catalog with fewer lost objects with the same set of sensor resources. This approach inherently can also trade-off fewer high priority tasks against more lower-priority tasks, when there is benefit in doing so. Currently the project has completed a prototyping and feasibility study, using open source data on the SSN's sensors, that showed significant reduction in orbit metric covariances. The algorithm techniques and results will be discussed along with future directions for the research.

  3. Voice-Controlled Artificial Handspeak System

    Directory of Open Access Journals (Sweden)

    Jonathan Gatti

    2014-04-01

    Full Text Available A man-machine interaction project is described whic h aims to establish an automated voice to sign language translator for communication with the deaf using integrated open technologies. The first prototype consists of a robotic hand designed with OpenSCAD and manufactured with a low-cost 3D printer which smoothly reproduces the alphabet of the sign language controlled by voice only. The core automation comprises an Arduino UNO controller used to activate a set of servo motors that follow instructions from a Raspberry Pi mini-computer havi ng installed the open source speech recognition eng ine Julius. We discuss its features, limitations and po ssible future developmen

  4. Moderate hypothermia technique for chronic implantation of a total artificial heart in calves.

    Science.gov (United States)

    Karimov, Jamshid H; Grady, Patrick; Sinkewich, Martin; Sunagawa, Gengo; Dessoffy, Raymond; Byram, Nicole; Moazami, Nader; Fukamachi, Kiyotaka

    2017-02-25

    The benefit of whole-body hypothermia in preventing ischemic injury during cardiac surgical operations is well documented. However, application of hypothermia during in vivo total artificial heart implantation has not become widespread because of limited understanding of the proper techniques and restrictions implied by constitutional and physiological characteristics specific to each animal model. Similarly, the literature on hypothermic set-up in total artificial heart implantation has also been limited. Herein we present our experience using hypothermia in bovine models implanted with the Cleveland Clinic continuous-flow total artificial heart.

  5. Color regeneration from reflective color sensor using an artificial intelligent technique.

    Science.gov (United States)

    Saracoglu, Ömer Galip; Altural, Hayriye

    2010-01-01

    A low-cost optical sensor based on reflective color sensing is presented. Artificial neural network models are used to improve the color regeneration from the sensor signals. Analog voltages of the sensor are successfully converted to RGB colors. The artificial intelligent models presented in this work enable color regeneration from analog outputs of the color sensor. Besides, inverse modeling supported by an intelligent technique enables the sensor probe for use of a colorimetric sensor that relates color changes to analog voltages.

  6. The Sensitive Artificial Listner: an induction technique for generating emotionally coloured conversation

    NARCIS (Netherlands)

    Douglas-Cowie, Ellen; Cowie, Roddy; Cox, Cate; Amier, Noam; Heylen, Dirk; Devillers, L.; Martin, J.-C.; Cowie, R.; Douglas-Cowie, E.; Batliner, A.

    2008-01-01

    The aim of the paper is to document and share an induction technique (The Sensitive Artificial Listener) that generates data that can be both tractable and reasonably naturalistic. The technique focuses on conversation between a human and an agent that either is or appears to be a machine. It is des

  7. A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system

    OpenAIRE

    Mohamed, Ahmed F.; Mahdi M. Elarini; Othman, Ahmed M.

    2014-01-01

    One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) whic...

  8. A Review and Performance Investigation of NPCC Based UPQC by Using Various Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Venkata Rami Reddy K

    2017-03-01

    Full Text Available This paper presents a comprehensive review and performance investigation of Neutral Point Clamped Converter (NPCC based Unified Power Quality Conditioner (UPQC by using Artificial Intelligent (AI techniques. A Novel application of various levels of Diode Clamped Multi-Level Inverters [DCMLI] with Anti Phase Opposition and Disposition (APOD Pulse Width Modulation (PWM Scheme to Unified Power Quality Conditioner (UPQC. The Power Quality problem became a burning issues since the starting of high voltage AC transmission system. Hence, in this article it has been discussed to mitigate the PQ issues in high voltage AC systems through a three phase four wire Unified Power Quality Conditioner (UPQC under non-linear loads. The emphasised PQ problems such as voltage and current harmonics along with voltage sags and swells have also been discussed with improved performance. Also, it proposes to control the DCMLI based UPQC through conventional control schemes. Thus application of these control technique makes the system performance in par with the standards and also compared with existing system. The simulation results based on MATLAB/Simulink are discussed in detail to support the concept developed in the paper.

  9. The design and artificial realization of a controller of pulse coupling feedback

    Institute of Scientific and Technical Information of China (English)

    Lü Ling; Guo Zhi-An; Luan Ling; Zou Cheng-Ye; Zhao Hong-Yan

    2006-01-01

    In this paper a controller of pulse coupling feedback (PCF) is designed to control chaotic systems. Control principles and the technique to select the feedback coefficients are introduced. This controller is theoretically studied with a three dimensional (3D) chaotic system. The artificial simulation results show that the chaotic system can be stabilized to different periodic orbits by using the PCF method, and the number of the periodic orbits are 2n ×3mp (n and m are integers). Therefore, this control method is effective and practical.

  10. DIRECT TORQUE CONTROL FOR INDUCTION MOTOR USING INTELLIGENT TECHNIQUES

    Directory of Open Access Journals (Sweden)

    R.Toufouti

    2007-09-01

    Full Text Available In this paper, we propose two approach intelligent techniques of improvement of Direct Torque Control (DTC of Induction motor such as fuzzy logic (FL and artificial neural network (ANN, applied in switching select voltage vector .The comparison with conventional direct torque control (DTC, show that the use of the DTC_FL and DTC_ANN, reduced the torque, stator flux, and current ripples. The validity of the proposed methods is confirmed by the simulative results.

  11. Artificial endocrine controller for power management in robotic systems.

    Science.gov (United States)

    Sauzé, Colin; Neal, Mark

    2013-12-01

    The robots that operate autonomously for extended periods in remote environments are often limited to gather only small amounts of power through photovoltaic solar panels. Such limited power budgets make power management critical to the success of the robot's mission. Artificial endocrine controllers, inspired by the mammalian endocrine system, have shown potential as a method for managing competing demands, gradually switching between behaviors, synchronizing behavior with external events, and maintaining a stable internal state of the robot. This paper reports the results obtained using these methods to manage power in an autonomous sailing robot. Artificial neural networks are used for sail and rudder control, while an artificial endocrine controller modulates the magnitude of actuator movements in response to battery or sunlight levels. Experiments are performed both in simulation and using a real robot. In simulation a 13-fold reduction in median power consumption is achieved; in the robot this is reduced to a twofold reduction because of the limitations of the simulation model. Additional simulations of a long term mission demonstrate the controller's ability to make gradual behavioral transitions and to synchronize behaviors with diurnal and seasonal changes in sunlight levels.

  12. The Sensitive Artificial Listner: an induction technique for generating emotionally coloured conversation

    OpenAIRE

    Douglas-Cowie, Ellen; Cowie, Roddy; Cox, Cate; Amier, Noam; Heylen, Dirk; Devillers, L.; Martin, J.-C.; Cowie, R; Douglas-Cowie, E.; Batliner, A.

    2008-01-01

    The aim of the paper is to document and share an induction technique (The Sensitive Artificial Listener) that generates data that can be both tractable and reasonably naturalistic. The technique focuses on conversation between a human and an agent that either is or appears to be a machine. It is designed to capture a broad spectrum of emotional states, expressed in ‘emotionally coloured discourse’ of the type likely to be displayed in everyday conversation. The technique is based on the obser...

  13. Artificial cervical disc replacement: Principles, types and techniques

    Directory of Open Access Journals (Sweden)

    Sekhon L

    2005-01-01

    Full Text Available Cervical arthroplasty after anterior decompression with insertion of a prosthetic total disc replacement has been suggested as an alternate to anterior cervical fusion. Currently there are four cervical arthroplasty devices available on the market whose results in clinical use have been reported. Each device varies in terms of materials, range of motion, insertion technique and constraint. It is not known which device is ideal. Early studies suggest that in the short term, the complication rate and efficacy is no worse than fusion surgery. Long-term results have not yet been reported. This review examines the current prostheses available on the market as well as discussing issues regarding indications and technique. Pitfalls are discussed and early experiences reviewed. In time, it is hoped that a refinement of cervical arthroplasty occurs in terms of both materials and design as well as in terms of indications and clinical outcomes as spinal surgeons enter a new era of the management of cervical spine disease.

  14. Design And Analysis Of Artificial Neural Network Based Controller For Speed Control Of Induction Motor Using D T C

    Directory of Open Access Journals (Sweden)

    Kusuma Gottapu

    2014-04-01

    Full Text Available This paper presents an improved version of direct torque control (DTC based on Artificial Neural Network technique used for flux position estimation and sector selection. This controller mainly reduces the torque and flux ripples. Direct torque control of induction motor drive has quick torque response without complex orientation transformation and inner loop current control. The major problem associated with DTC drive is the high torque ripples. The important point in ANN based DTC is the right selection of voltage vector. This project presents simple structured neural network for flux position estimation and sector selection for induction motor. The Levenberg-Marquardt back propagation technique has been used to train the neural networks. The simple structure network facilitates a short training and processing times. The neural network based controller is found to be a very useful technique to obtain high performance speed control.

  15. Validating a UAV artificial intelligence control system using an autonomous test case generator

    Science.gov (United States)

    Straub, Jeremy; Huber, Justin

    2013-05-01

    The validation of safety-critical applications, such as autonomous UAV operations in an environment which may include human actors, is an ill posed problem. To confidence in the autonomous control technology, numerous scenarios must be considered. This paper expands upon previous work, related to autonomous testing of robotic control algorithms in a two dimensional plane, to evaluate the suitability of similar techniques for validating artificial intelligence control in three dimensions, where a minimum level of airspeed must be maintained. The results of human-conducted testing are compared to this automated testing, in terms of error detection, speed and testing cost.

  16. Color Regeneration from Reflective Color Sensor Using an Artificial Intelligent Technique

    Directory of Open Access Journals (Sweden)

    Hayriye Altural

    2010-09-01

    Full Text Available A low-cost optical sensor based on reflective color sensing is presented. Artificial neural network models are used to improve the color regeneration from the sensor signals. Analog voltages of the sensor are successfully converted to RGB colors. The artificial intelligent models presented in this work enable color regeneration from analog outputs of the color sensor. Besides, inverse modeling supported by an intelligent technique enables the sensor probe for use of a colorimetric sensor that relates color changes to analog voltages.

  17. Autonomous Defensive Space Control via On-Board Artificial Neural Networks

    Science.gov (United States)

    2007-04-01

    AUTONOMOUS DEFENSIVE SPACE CONTROL VIA ON-BOARD ARTIFICIAL NEURAL NETWORKS Michael T. Manor, Major, USAF April 2007...TITLE AND SUBTITLE Sutonomous Defensive Space Control via On-Board Artificial Neural Networks 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM...11 HOW ARTIFICIAL NEURAL NETWORKS WORK

  18. ADVANTAGES OF ARTIFICIAL REPRODUCTION TECHNIQUES FOR WHITE-CLAWED CRAYFISH (AUSTROPOTAMOBIUS PALLIPES LEREBOULLET

    Directory of Open Access Journals (Sweden)

    CARRAL J. M.

    2003-04-01

    Full Text Available With the aim of preserving and increasing endangered stocks of white-clawed crayfish, research on juvenile production has been carried out. Advantages in application of newly developed techniques of egg storage, transport and artificial incubation techniques are discussed. Eggs can be removed from maternal pleopods during the early stages of embryonic development and placed in artificial incubation devices. This practice avoids egg losses caused by aggressive contacts, female disease or death and the production of stage-2 juveniles in different batches by means of temperature manipulation. Furthermore transmission of pathogens from broodstocks to offspring can be minimised. Egg storage and transport have some advantages in the artificial reproduction of crayfish. Firstly, embryonic development continues under storage conditions and thus water and human effort can be saved during this period. Temperature plays an important role on both efficiency rates and duration of embryogenesis. Secondly, egg transport could facilitate restocking programs, as there is no need to move berried females to other habitats. To sum up, the combined use of artificial incubation and storage/transport techniques could have important applications to the development of astacid crayfish culture.

  19. Formation Control of Robotic Swarm Using Bounded Artificial Forces

    Directory of Open Access Journals (Sweden)

    Long Qin

    2013-01-01

    Full Text Available Formation control of multirobot systems has drawn significant attention in the recent years. This paper presents a potential field control algorithm, navigating a swarm of robots into a predefined 2D shape while avoiding intermember collisions. The algorithm applies in both stationary and moving targets formation. We define the bounded artificial forces in the form of exponential functions, so that the behavior of the swarm drove by the forces can be adjusted via selecting proper control parameters. The theoretical analysis of the swarm behavior proves the stability and convergence properties of the algorithm. We further make certain modifications upon the forces to improve the robustness of the swarm behavior in the presence of realistic implementation considerations. The considerations include obstacle avoidance, local minima, and deformation of the shape. Finally, detailed simulation results validate the efficiency of the proposed algorithm, and the direction of possible futrue work is discussed in the conclusions.

  20. Exercise, Insulin Absorption Rates, and Artificial Pancreas Control

    Science.gov (United States)

    Frank, Spencer; Hinshaw, Ling; Basu, Rita; Basu, Ananda; Szeri, Andrew J.

    2016-11-01

    Type 1 Diabetes is characterized by an inability of a person to endogenously produce the hormone insulin. Because of this, insulin must be injected - usually subcutaneously. The size of the injected dose and the rate at which the dose reaches the circulatory system have a profound effect on the ability to control glucose excursions, and therefore control of diabetes. However, insulin absorption rates via subcutaneous injection are variable and depend on a number of factors including tissue perfusion, physical activity (vasodilation, increased capillary throughput), and other tissue geometric and physical properties. Exercise may also have a sizeable effect on the rate of insulin absorption, which can potentially lead to dangerous glucose levels. Insulin-dosing algorithms, as implemented in an artificial pancreas controller, should account accurately for absorption rate variability and exercise effects on insulin absorption. The aforementioned factors affecting insulin absorption will be discussed within the context of both fluid mechanics and data driven modeling approaches.

  1. Formation control of robotic swarm using bounded artificial forces.

    Science.gov (United States)

    Qin, Long; Zha, Yabing; Yin, Quanjun; Peng, Yong

    2013-01-01

    Formation control of multirobot systems has drawn significant attention in the recent years. This paper presents a potential field control algorithm, navigating a swarm of robots into a predefined 2D shape while avoiding intermember collisions. The algorithm applies in both stationary and moving targets formation. We define the bounded artificial forces in the form of exponential functions, so that the behavior of the swarm drove by the forces can be adjusted via selecting proper control parameters. The theoretical analysis of the swarm behavior proves the stability and convergence properties of the algorithm. We further make certain modifications upon the forces to improve the robustness of the swarm behavior in the presence of realistic implementation considerations. The considerations include obstacle avoidance, local minima, and deformation of the shape. Finally, detailed simulation results validate the efficiency of the proposed algorithm, and the direction of possible futrue work is discussed in the conclusions.

  2. Colonization of Lutzomyia shannoni (Diptera: Psychodidae) utilizing an artificial blood feeding technique.

    Science.gov (United States)

    Mann, Rajinder S; Kaufman, Phillip E

    2010-12-01

    Laboratory colonization of hematophagous insects must include an efficient method of blood feeding, preferably by artificial means. Strict rules for obtaining animal use permits, extensive animal maintenance costs, and indirect anesthesia effects on animal health warrant the development of an artificial membrane feeding technique for sand fly colonization in laboratories. An attempt was made to colonize Lutzomyia shannoni using an artificial blood feeding membrane to replace the use of live animals commonly used for sand fly blood-feeding purposes. Lutzomyia shannoni readily fed through a pig intestine membrane exposed at an angle of 45°. However, it did not feed through a chicken skin membrane. Olfactory attractants were unable to improve blood-feeding efficiency. Plaster of Paris was the most suitable oviposition substrate. Female L. shannoni adults laid no eggs on moist sand substrate. Sand fly adults held in groups of ten or more laid higher numbers of eggs than did individually maintained sand flies. Inclusion of the L. longipalpis oviposition hormone dodecanoic acid or the presence of previously laid eggs did not stimulate L. shannoni oviposition. The average L. shannoni egg, larval, and pupal duration were 9.3, 36.7, and 17.8 days, respectively. The addition of a 20% sugar solution improved adult female longevity. Females survived longer (14.8 days) than males (11.9 days). Lutzomyia shannoni was successfully colonized in the laboratory for up to four generations using this artificial membrane technique.

  3. Building the artificial neural network environment : Artificial Neural Networks in plane control

    OpenAIRE

    Naumetc, Daniil

    2017-01-01

    These days Artificial Neural Networks have penetrated into all digital technologies that surround us. Mostly every online service like Facebook, Google, Instagram are using Artificial Intelligence to build better service for their users. Google Self-Driving Car Project that started several years ago already have results as driverless cars already moving on the streets of California. Artificial Intelligence makes a breakthrough in Medicine as well. Such programs already successfully find disea...

  4. Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands

    Science.gov (United States)

    Santello, Marco; Bianchi, Matteo; Gabiccini, Marco; Ricciardi, Emiliano; Salvietti, Gionata; Prattichizzo, Domenico; Ernst, Marc; Moscatelli, Alessandro; Jörntell, Henrik; Kappers, Astrid M. L.; Kyriakopoulos, Kostas; Albu-Schäffer, Alin; Castellini, Claudio; Bicchi, Antonio

    2016-07-01

    The term 'synergy' - from the Greek synergia - means 'working together'. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project "The Hand Embodied" (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies.

  5. Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands.

    Science.gov (United States)

    Santello, Marco; Bianchi, Matteo; Gabiccini, Marco; Ricciardi, Emiliano; Salvietti, Gionata; Prattichizzo, Domenico; Ernst, Marc; Moscatelli, Alessandro; Jörntell, Henrik; Kappers, Astrid M L; Kyriakopoulos, Kostas; Albu-Schäffer, Alin; Castellini, Claudio; Bicchi, Antonio

    2016-07-01

    The term 'synergy' - from the Greek synergia - means 'working together'. The concept of multiple elements working together towards a common goal has been extensively used in neuroscience to develop theoretical frameworks, experimental approaches, and analytical techniques to understand neural control of movement, and for applications for neuro-rehabilitation. In the past decade, roboticists have successfully applied the framework of synergies to create novel design and control concepts for artificial hands, i.e., robotic hands and prostheses. At the same time, robotic research on the sensorimotor integration underlying the control and sensing of artificial hands has inspired new research approaches in neuroscience, and has provided useful instruments for novel experiments. The ambitious goal of integrating expertise and research approaches in robotics and neuroscience to study the properties and applications of the concept of synergies is generating a number of multidisciplinary cooperative projects, among which the recently finished 4-year European project "The Hand Embodied" (THE). This paper reviews the main insights provided by this framework. Specifically, we provide an overview of neuroscientific bases of hand synergies and introduce how robotics has leveraged the insights from neuroscience for innovative design in hardware and controllers for biomedical engineering applications, including myoelectric hand prostheses, devices for haptics research, and wearable sensing of human hand kinematics. The review also emphasizes how this multidisciplinary collaboration has generated new ways to conceptualize a synergy-based approach for robotics, and provides guidelines and principles for analyzing human behavior and synthesizing artificial robotic systems based on a theory of synergies.

  6. Production of genetically and developmentally modified seaweeds: Exploiting the potential of artificial selection techniques

    Directory of Open Access Journals (Sweden)

    Bénédicte eCharrier

    2015-03-01

    Full Text Available Plant feedstock with specific, modified developmental features has been a quest for centuries. Since the development and spread of agriculture, there has been a desire for plants producing disproportionate — or more abundant and more nutritional — biomass that meet human needs better than their native counterparts. Seaweed aquaculture, targeted for human consumption and the production of various raw materials, is a rapidly expanding field and its stakeholders have increasing vested interest for cost-effective and lucrative seaweed cultivation processes. Thus, scientific research on seaweed development is particularly timely: the potential for expansion of seaweed cultivation depends on the sector’s capacity to produce seaweeds with modified morphological features (e.g. thicker blades, higher growth rates or delayed (or even no fertility. Here, we review the various technical approaches used to modify development in macroalgae, which have attracted little attention from developmental biologists to date. Because seaweed (or marine macroalgae anatomy is much less complex than that of land plants and because seaweeds belong to three different eukaryotic phyla, the mechanisms controlling their morphogenesis are key to understanding their development. Here, we present efficient sources of developmentally and genetically modified seaweeds — somatic variants, artificial hybrids and mutants — as well as the future potential of these techniques.

  7. Production of genetically and developmentally modified seaweeds: exploiting the potential of artificial selection techniques.

    Science.gov (United States)

    Charrier, Bénédicte; Rolland, Elodie; Gupta, Vishal; Reddy, C R K

    2015-01-01

    Plant feedstock with specific, modified developmental features has been a quest for centuries. Since the development and spread of agriculture, there has been a desire for plants producing disproportionate-or more abundant and more nutritional-biomass that meet human needs better than their native counterparts. Seaweed aquaculture, targeted for human consumption and the production of various raw materials, is a rapidly expanding field and its stakeholders have increasing vested interest for cost-effective and lucrative seaweed cultivation processes. Thus, scientific research on seaweed development is particularly timely: the potential for expansion of seaweed cultivation depends on the sector's capacity to produce seaweeds with modified morphological features (e.g., thicker blades), higher growth rates or delayed (or even no) fertility. Here, we review the various technical approaches used to modify development in macroalgae, which have attracted little attention from developmental biologists to date. Because seaweed (or marine macroalgae) anatomy is much less complex than that of land plants and because seaweeds belong to three different eukaryotic phyla, the mechanisms controlling their morphogenesis are key to understanding their development. Here, we present efficient sources of developmentally and genetically modified seaweeds-somatic variants, artificial hybrids and mutants-as well as the future potential of these techniques.

  8. Current topics in glycemic control by wearable artificial pancreas or bedside artificial pancreas with closed-loop system.

    Science.gov (United States)

    Hanazaki, Kazuhiro; Munekage, Masaya; Kitagawa, Hiroyuki; Yatabe, Tomoaki; Munekage, Eri; Shiga, Mai; Maeda, Hiromichi; Namikawa, Tsutomu

    2016-09-01

    The incidence of diabetes is increasing at an unprecedented pace and has become a serious health concern worldwide during the last two decades. Despite this, adequate glycemic control using an artificial pancreas has not been established, although the 21st century has seen rapid developments in this area. Herein, we review current topics in glycemic control for both the wearable artificial pancreas for type 1 and type 2 diabetic patients and the bedside artificial pancreas for surgical diabetic patients. In type 1 diabetic patients, nocturnal hypoglycemia associated with insulin therapy remains a serious problem that could be addressed by the recent development of a wearable artificial pancreas. This smart phone-like device, comprising a real-time, continuous glucose monitoring system and insulin pump system, could potentially significantly reduce nocturnal hypoglycemia compared with conventional glycemic control. Of particular interest in this space are the recent inventions of a low-glucose suspend feature in the portable systems that automatically stops insulin delivery 2 h following a glucose sensor value artificial pancreas with the closed-loop system has also proved safe and effective for not only avoiding hypoglycemia, but also for reducing blood glucose level variability resulting in good surgical outcomes. We hope that a more sophisticated artificial pancreas with closed-loop system will now be taken up for routine use worldwide, providing enormous relief for patients suffering from uncontrolled hyperglycemia, hypoglycemia, and/or variability in blood glucose concentrations.

  9. Artificial Intelligent Control for a Novel Advanced Microwave Biodiesel Reactor

    Energy Technology Data Exchange (ETDEWEB)

    Wali, W A; Hassan, K H; Cullen, J D; Al-Shamma' a, A I; Shaw, A; Wylie, S R, E-mail: w.wali@2009.ljmu.ac.uk [Built Environment and Sustainable Technologies Institute (BEST), School of the Built Environment, Faculty of Technology and Environment Liverpool John Moores University, Byrom Street, Liverpool L3 3AF (United Kingdom)

    2011-08-17

    Biodiesel, an alternative diesel fuel made from a renewable source, is produced by the transesterification of vegetable oil or fat with methanol or ethanol. In order to control and monitor the progress of this chemical reaction with complex and highly nonlinear dynamics, the controller must be able to overcome the challenges due to the difficulty in obtaining a mathematical model, as there are many uncertain factors and disturbances during the actual operation of biodiesel reactors. Classical controllers show significant difficulties when trying to control the system automatically. In this paper we propose a comparison of artificial intelligent controllers, Fuzzy logic and Adaptive Neuro-Fuzzy Inference System(ANFIS) for real time control of a novel advanced biodiesel microwave reactor for biodiesel production from waste cooking oil. Fuzzy logic can incorporate expert human judgment to define the system variables and their relationships which cannot be defined by mathematical relationships. The Neuro-fuzzy system consists of components of a fuzzy system except that computations at each stage are performed by a layer of hidden neurons and the neural network's learning capability is provided to enhance the system knowledge. The controllers are used to automatically and continuously adjust the applied power supplied to the microwave reactor under different perturbations. A Labview based software tool will be presented that is used for measurement and control of the full system, with real time monitoring.

  10. Artificial Intelligent Control for a Novel Advanced Microwave Biodiesel Reactor

    Science.gov (United States)

    Wali, W. A.; Hassan, K. H.; Cullen, J. D.; Al-Shamma'a, A. I.; Shaw, A.; Wylie, S. R.

    2011-08-01

    Biodiesel, an alternative diesel fuel made from a renewable source, is produced by the transesterification of vegetable oil or fat with methanol or ethanol. In order to control and monitor the progress of this chemical reaction with complex and highly nonlinear dynamics, the controller must be able to overcome the challenges due to the difficulty in obtaining a mathematical model, as there are many uncertain factors and disturbances during the actual operation of biodiesel reactors. Classical controllers show significant difficulties when trying to control the system automatically. In this paper we propose a comparison of artificial intelligent controllers, Fuzzy logic and Adaptive Neuro-Fuzzy Inference System(ANFIS) for real time control of a novel advanced biodiesel microwave reactor for biodiesel production from waste cooking oil. Fuzzy logic can incorporate expert human judgment to define the system variables and their relationships which cannot be defined by mathematical relationships. The Neuro-fuzzy system consists of components of a fuzzy system except that computations at each stage are performed by a layer of hidden neurons and the neural network's learning capability is provided to enhance the system knowledge. The controllers are used to automatically and continuously adjust the applied power supplied to the microwave reactor under different perturbations. A Labview based software tool will be presented that is used for measurement and control of the full system, with real time monitoring.

  11. Breast Cancer Diagnosis using Artificial Neural Networks with Extreme Learning Techniques

    Directory of Open Access Journals (Sweden)

    Chandra Prasetyo Utomo

    2014-07-01

    Full Text Available Breast cancer is the second cause of dead among women. Early detection followed by appropriate cancer treatment can reduce the deadly risk. Medical professionals can make mistakes while identifying a disease. The help of technology such as data mining and machine learning can substantially improve the diagnosis accuracy. Artificial Neural Networks (ANN has been widely used in intelligent breast cancer diagnosis. However, the standard Gradient-Based Back Propagation Artificial Neural Networks (BP ANN has some limitations. There are parameters to be set in the beginning, long time for training process, and possibility to be trapped in local minima. In this research, we implemented ANN with extreme learning techniques for diagnosing breast cancer based on Breast Cancer Wisconsin Dataset. Results showed that Extreme Learning Machine Neural Networks (ELM ANN has better generalization classifier model than BP ANN. The development of this technique is promising as intelligent component in medical decision support systems.

  12. Globally controlled artificial semiconducting molecules as quantum computers

    CERN Document Server

    Tribollet, J

    2005-01-01

    Quantum computers are expected to be considerably more efficient than classical computers for the execution of some specific tasks. The difficulty in the practical implementation of thoose computers is to build a microscopic quantum system that can be controlled at a larger mesoscopic scale. Here I show that vertical lines of donor atoms embedded in an appropriate Zinc Oxide semiconductor structure can constitute artificial molecules that are as many copy of the same quantum computer. In this scalable architecture, each unit of information is encoded onto the electronic spin of a donor. Contrary to most existing practical proposals, here the logical operations only require a global control of the spins by electromagnetic pulses. Ensemble measurements simplify the readout. With appropriate improvement of its growth and doping methods, Zinc Oxide could be a good semiconductor for the next generation of computers.

  13. The use of artificial intelligence techniques to improve the multiple payload integration process

    Science.gov (United States)

    Cutts, Dannie E.; Widgren, Brian K.

    1992-01-01

    A maximum return of science and products with a minimum expenditure of time and resources is a major goal of mission payload integration. A critical component then, in successful mission payload integration is the acquisition and analysis of experiment requirements from the principal investigator and payload element developer teams. One effort to use artificial intelligence techniques to improve the acquisition and analysis of experiment requirements within the payload integration process is described.

  14. Method and apparatus for optimizing operation of a power generating plant using artificial intelligence techniques

    Science.gov (United States)

    Wroblewski, David; Katrompas, Alexander M.; Parikh, Neel J.

    2009-09-01

    A method and apparatus for optimizing the operation of a power generating plant using artificial intelligence techniques. One or more decisions D are determined for at least one consecutive time increment, where at least one of the decisions D is associated with a discrete variable for the operation of a power plant device in the power generating plant. In an illustrated embodiment, the power plant device is a soot cleaning device associated with a boiler.

  15. Genetically Controlled Fusion, Exocytosis and Fission of Artificial Vesicles

    DEFF Research Database (Denmark)

    Bönzli, Eva; Hadorn, Maik; De Lucrezia, Davide

    Artificial vesicles represent ideal candidates as a model for artificial cells. It was shown that artificial genetic programs and the required cellular machinery (cell-free expression systems) can be incorporated into vesicles and allow the synthesis of proteins. Vesicles were shown to fuse...

  16. Back stepping-Based-PID-Controller Designed for an Artificial Pancreas model

    Directory of Open Access Journals (Sweden)

    ShaimaMahmou Mahdi

    2011-01-01

    Full Text Available Artificial pancreas is simulated to handle Type I diabetic patients under intensive care by automatically controlling the insulin infusion rate. A Backstepping technique is used to apply the effect of PID controller to blood glucose level since there is no direct relation between insulin infusion (the manipulated variable and glucose level in Bergman’s system model subjected to an oral glucose tolerance test by applying a meal translated into a disturbance. Backstepping technique is usually recommended to stabilize and control the states of Bergman's class of nonlinear systems. The results showed a very satisfactory behavior of glucose deviation to a sudden rise represented by the meal that increase the blood glucose

  17. Modelling and analysis of ozone concentration by artificial intelligent techniques for estimating air quality

    Science.gov (United States)

    Taylan, Osman

    2017-02-01

    High ozone concentration is an important cause of air pollution mainly due to its role in the greenhouse gas emission. Ozone is produced by photochemical processes which contain nitrogen oxides and volatile organic compounds in the lower atmospheric level. Therefore, monitoring and controlling the quality of air in the urban environment is very important due to the public health care. However, air quality prediction is a highly complex and non-linear process; usually several attributes have to be considered. Artificial intelligent (AI) techniques can be employed to monitor and evaluate the ozone concentration level. The aim of this study is to develop an Adaptive Neuro-Fuzzy inference approach (ANFIS) to determine the influence of peripheral factors on air quality and pollution which is an arising problem due to ozone level in Jeddah city. The concentration of ozone level was considered as a factor to predict the Air Quality (AQ) under the atmospheric conditions. Using Air Quality Standards of Saudi Arabia, ozone concentration level was modelled by employing certain factors such as; nitrogen oxide (NOx), atmospheric pressure, temperature, and relative humidity. Hence, an ANFIS model was developed to observe the ozone concentration level and the model performance was assessed by testing data obtained from the monitoring stations established by the General Authority of Meteorology and Environment Protection of Kingdom of Saudi Arabia. The outcomes of ANFIS model were re-assessed by fuzzy quality charts using quality specification and control limits based on US-EPA air quality standards. The results of present study show that the ANFIS model is a comprehensive approach for the estimation and assessment of ozone level and is a reliable approach to produce more genuine outcomes.

  18. Detection of drugs and explosives using neutron computerized tomography and artificial intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Ferreira, F.J.O. [Instituto de Engenharia Nuclear, Cidade Universitaria, Rio de Janeiro, CEP 21945-970, Caixa Postal 68550 (Brazil)], E-mail: fferreira@ien.gov.br; Crispim, V.R.; Silva, A.X. [DNC/Poli, PEN COPPE CT, UFRJ Universidade Federal do Rio de Janeiro, CEP 21941-972, Caixa Postal 68509, Rio de Janeiro (Brazil)

    2010-06-15

    In this study the development of a methodology to detect illicit drugs and plastic explosives is described with the objective of being applied in the realm of public security. For this end, non-destructive assay with neutrons was used and the technique applied was the real time neutron radiography together with computerized tomography. The system is endowed with automatic responses based upon the application of an artificial intelligence technique. In previous tests using real samples, the system proved capable of identifying 97% of the inspected materials.

  19. A NOVEL ARTIFICIAL HYDROCARBON NETWORKS BASED SPACE VECTOR PULSE WIDTH MODULATION CONTROLLER FOR INDUCTION MOTORS

    Directory of Open Access Journals (Sweden)

    Hiram Ponce

    2014-01-01

    Full Text Available Most of machine-operated industrial processes implement electric machinery as their work sources, implying the necessary improvement of control techniques and power electronics drivers. Many years have passed since the control conflicts related to induction motors have been overcome through torque-flux control techniques so their advantages over direct current motors have made them to be the most common electric actuator found behind industrial automation. In fact, induction motors can be easily operated using a Direct Torque Control (DTC. Since, it is based on a hysteresis control of the torque and flux errors, its performance is characterized by a quick reaching of the set point, but also a high ripple on both torque and flux. In order to enhance that technique, this study introduces a novel hybrid fuzzy controller with artificial hydrocarbon networks (FMC that is used in a Space Vector Pulse Width Modulation (SVPWM technique, so-called FMC-SVPWM-DTC. In fact, this study describes the proposal and its design method. Experimental results over a velocity-torque cascade topology proved that the proposed FMC-SVPWM-DTC responses highly effective almost suppressing rippling in torque and flux. It also performed a faster speed response than in a conventional DTC. In that sense, the proposed FMC-SVPWM-DTC can be used an alternative approach for controlling induction motors.

  20. Control strategies for afterload reduction with an artificial vasculature device.

    Science.gov (United States)

    Giridharan, Guruprasad A; Cheng, Rolando Chip; Glower, Jacob S; Ewert, Daniel L; Sobieski, Michael A; Slaughter, Mark S; Koenig, Steven C

    2012-01-01

    Ventricular assist devices (VADs) have been used successfully as a bridge to transplant in heart failure patients by unloading ventricular volume and restoring the circulation. An artificial vasculature device (AVD) is being developed that may better facilitate myocardial recovery than VAD by controlling the afterload experienced by the native heart and controlling the pulsatile energy entering into the arterial system from the device, potentially reconditioning the arterial system properties. The AVD is a valveless, 80 ml blood chamber with a servo-controlled pusher plate connected to the ascending aorta by a vascular graft. Control algorithms for the AVD were developed to maintain any user-defined systemic input impedance (IM) including resistance, elastance, and inertial components. Computer simulation and mock circulation models of the cardiovascular system were used to test the efficacy of two control strategies for the AVD: 1) average impedance position control (AIPC)-to maintain an average value of resistance during left ventricular (LV) systole and 2) instantaneous impedance force feedback (IIFF) and position control (IIPC)-to maintain a desired value or profile of resistance and compliance. Computer simulations and mock loop tests were performed to predict resulting cardiovascular pressures, volumes, flows, and the resistance and compliance experienced by the native LV during ejection for simulated normal, failing, and recovering LV. These results indicate that the LV volume and pressure decreased, and the LV stroke volume increased with decreasing IM, resulting in an increased ejection fraction. Although the AIPC algorithm is more stable and can tolerate higher levels of sensor errors and noise, the IIFF and IIPC control algorithms are better suited to maintain any instantaneous IM or an IM profile. The developed AVD impedance control algorithms may be implemented with current VADs to promote myocardial recovery and facilitate weaning.

  1. Smart Collections: Can Artificial Intelligence Tools and Techniques Assist with Discovering, Evaluating and Tagging Digital Learning Resources?

    Science.gov (United States)

    Leibbrandt, Richard; Yang, Dongqiang; Pfitzner, Darius; Powers, David; Mitchell, Pru; Hayman, Sarah; Eddy, Helen

    2010-01-01

    This paper reports on a joint proof of concept project undertaken by researchers from the Flinders University Artificial Intelligence Laboratory in partnership with information managers from the Education Network Australia (edna) team at Education Services Australia to address the question of whether artificial intelligence techniques could be…

  2. Controlled Magnetic Reversal and Frustration in Artificial Quasicrystals

    Science.gov (United States)

    Bhat, Vinayak

    2014-03-01

    Recent studies of ferromagnetic (FM) antidot arrays have been restricted to simple periodic lattices (square, triangular, etc.). We have fabricated artificial FM quasicrystals (AFQ), which are aperiodic antidot lattices that are self-similar, retain definite rotational symmetry, and consist of a multiply-connected network of permalloy film segments. We focus on Penrose P2 tilings (P2T) constructed from film segments of two lengths (d1 = 810 nm -1618 nm, d2 = 500 nm - 1 μ m), width W ~ 100 nm, and thickness t = 25 nm. Static and dynamic magnetizations were studied using DC magnetometry, broadband (BB) FMR, and micromagnetic simulations (MS). Reproducible ``knee'' anomalies observed in the hysteretic, low-field DC magnetization M(H,T) signal a series of abrupt transitions between ordered magnetization textures, concluding in a smooth evolution into a saturated state. Numerous FMR mode signatures quantitatively reproduce in opposite DC field sweeps in the near-saturated regime, which suggests pinning of the magnetization parallel to the AD edges and confinement of domain walls at P2T vertices control segment polarization and reversal. Novel ``asymmetric'' modes, defined by their presence on only one side of the field origin in a given sweep, are observed only in the reversal regime, and accompany knee anomalies in M(H,T). MS agree with experimental DC hysteresis loops and FMR spectra, and indicate that systematic control of magnetic reversal and domain wall motion can be achieved via tiling design, offering a new paradigm of magnonic quasicrystals. AFQ also behave as novel artificial spin ice systems that exhibit non-stochastic switching due to their aperiodicity and inequivalent pattern vertices. MS indicate pinned Dirac monopoles and confined magnetic avalanches exist in AFQ. Research supported by U.S. DoE Grant DE-FG02-97ER45653 and NSF Grant EPS-0814194.

  3. An artificial pancreas for automated blood glucose control in patients with Type 1 diabetes.

    Science.gov (United States)

    Schmidt, Signe; Boiroux, Dimitri; Ranjan, Ajenthen; Jørgensen, John Bagterp; Madsen, Henrik; Nørgaard, Kirsten

    2015-01-01

    Automated glucose control in patients with Type 1 diabetes is much-coveted by patients, relatives and healthcare professionals. It is the expectation that a system for automated control, also know as an artificial pancreas, will improve glucose control, reduce the risk of diabetes complications and markedly improve patient quality of life. An artificial pancreas consists of portable devices for glucose sensing and insulin delivery which are controlled by an algorithm residing on a computer. The technology is still under development and currently no artificial pancreas is commercially available. This review gives an introduction to recent progress, challenges and future prospects within the field of artificial pancreas research.

  4. Ripple reduction control of the undulation pump total artificial heart.

    Science.gov (United States)

    Saito, Itsuro; Chinzei, Tsuneo; Mochizuki, Shuichi; Abe, Yusuke; Isoyama, Takashi; Iwasaki, Kiyotaka; Suzuki, Takafumi; Karita, Tatsuro; Ono, Toshiya; Kouno, Akimasa; Ishimaru, Mitsuhiko; Baba, Atsushi; Ozeki, Toshinaga; Tohyama, Takahiro; Kobayashi Si, Shin-ichi; Imachi, Kou

    2002-01-01

    An undulation pump total artificial heart (UPTAH) in which the revolutions of the motor are converted to undulation motion of a disk has been developed. In an experiment, a goat using the UPTAH survived for 54 days. However, a large ripple was observed in the device's output pressure and flow waveform. In calculating the spectrum of the ripple, we found that the ripple mainly comprised 2 frequency sine waves: 1 having the same frequency as and 1 having double the frequency of the motor revolutions. To reduce the ripple, 2 sine waves, 1 having the same frequency as and 1 having double the frequency of the motor revolutions, were provided to the motor current to modulate the pulse width of the pulse width modulation controlling the motor revolutions. This ripple control method reduced the pressure ripple by 90% in a mock circulation and by 70% in animal experiments. These results revealed that the ripple generated in the UPTAH could be controlled through the use of motor control software.

  5. [The research on linear control of pneumatic artificial muscles used in medical robots].

    Science.gov (United States)

    Lin, Linang-ming; Tian, She-ping; Yan, Guo-zheng

    2002-01-01

    This paper presents the properties of Pneumatic artificial muscles and its application in medical robots. The linear model construction and minimum predictive error control algorithm for artificial muscles are discussed here too. This paper provides the experimental results of linear adaptive control, which show the control algorithm has certain applicable value.

  6. Improved object segmentation using Markov random fields, artificial neural networks, and parallel processing techniques

    Science.gov (United States)

    Foulkes, Stephen B.; Booth, David M.

    1997-07-01

    Object segmentation is the process by which a mask is generated which identifies the area of an image which is occupied by an object. Many object recognition techniques depend on the quality of such masks for shape and underlying brightness information, however, segmentation remains notoriously unreliable. This paper considers how the image restoration technique of Geman and Geman can be applied to the improvement of object segmentations generated by a locally adaptive background subtraction technique. Also presented is how an artificial neural network hybrid, consisting of a single layer Kohonen network with each of its nodes connected to a different multi-layer perceptron, can be used to approximate the image restoration process. It is shown that the restoration techniques are very well suited for parallel processing and in particular the artificial neural network hybrid has the potential for near real time image processing. Results are presented for the detection of ships in SPOT panchromatic imagery and the detection of vehicles in infrared linescan images, these being a fair representation of the wider class of problem.

  7. Glyphosate detection by voltammetric techniques. A comparison between statistical methods and an artificial neural network

    OpenAIRE

    2012-01-01

    Glyphosate quantification methods are complex and expensive, and its control in natural water bodies is getting more important year after year. In order to find a new system that facilitates the detection of glyphosate, we present a comparison between two models to predict glyphosate concentration in aqueous dissolutions. One of them is done by an artificial neural network (ANN) embedded in a microcontroller and the other one is done by statistic methods (Partial Least Squares) in a computer...

  8. Cooperative Traffic Control based on the Artificial Bee Colony

    Directory of Open Access Journals (Sweden)

    Jinjian Li

    2016-12-01

    Full Text Available This paper studies the traffic control problem in an isolated intersection without traffic lights and phase, because the right-of-way is distributed to each vehicle individually based on connection of the Vehicle-to-Infrastructure (V2I, and the compatible streams are dynamically combined according to the arrival vehicles in each traffic flows. The control objective in the proposed algorithm is to minimize the time delay, which is defined as the difference between the travel time in real state and that in free flow state. In order to realize this target, a cooperative control structure with a two-way communications is proposed. First of all, once the vehicle enters the communication zone, it sends its information to the intersection. Then the passing sequence is optimized in the intersection with the heuristic algorithm of the Artificial Bee Colony, based on the arrival interval of the vehicles. At last, each vehicle plans its speed profile to meet the received passing sequence by V2I. The simulation results show that each vehicle can finish the entire travel trip with a near free flow speed in the proposed method.

  9. Consistently Trained Artificial Neural Network for Automatic Ship Berthing Control

    Directory of Open Access Journals (Sweden)

    Y.A. Ahmed

    2015-09-01

    Full Text Available In this paper, consistently trained Artificial Neural Network controller for automatic ship berthing is discussed. Minimum time course changing manoeuvre is utilised to ensure such consistency and a new concept named ‘virtual window’ is introduced. Such consistent teaching data are then used to train two separate multi-layered feed forward neural networks for command rudder and propeller revolution output. After proper training, several known and unknown conditions are tested to judge the effectiveness of the proposed controller using Monte Carlo simulations. After getting acceptable percentages of success, the trained networks are implemented for the free running experiment system to judge the network’s real time response for Esso Osaka 3-m model ship. The network’s behaviour during such experiments is also investigated for possible effect of initial conditions as well as wind disturbances. Moreover, since the final goal point of the proposed controller is set at some distance from the actual pier to ensure safety, therefore a study on automatic tug assistance is also discussed for the final alignment of the ship with actual pier.

  10. Atmospheric controls on Puerto Rico precipitation using artificial neural networks

    Science.gov (United States)

    Ramseyer, Craig A.; Mote, Thomas L.

    2016-10-01

    The growing need for local climate change scenarios has given rise to a wide range of empirical climate downscaling techniques. One of the most critical decisions in these methodologies is the selection of appropriate predictor variables for the downscaled surface predictand. A systematic approach to selecting predictor variables should be employed to ensure that the most important variables are utilized for the study site where the climate change scenarios are being developed. Tropical study areas have been far less examined than mid- and high-latitudes in the climate downscaling literature. As a result, studies analyzing optimal predictor variables for tropics are limited. The objectives of this study include developing artificial neural networks for six sites around Puerto Rico to develop nonlinear functions between 37 atmospheric predictor variables and local rainfall. The relative importance of each predictor is analyzed to determine the most important inputs in the network. Randomized ANNs are produced to determine the statistical significance of the relative importance of each predictor variable. Lower tropospheric moisture and winds are shown to be the most important variables at all sites. Results show inter-site variability in u- and v-wind importance depending on the unique geographic situation of the site. Lower tropospheric moisture and winds are physically linked to variability in sea surface temperatures (SSTs) and the strength and position of the North Atlantic High Pressure cell (NAHP). The changes forced by anthropogenic climate change in regional SSTs and the NAHP will impact rainfall variability in Puerto Rico.

  11. Artificial Intelligence Techniques for the Estimation of Direct Methanol Fuel Cell Performance

    Science.gov (United States)

    Hasiloglu, Abdulsamet; Aras, Ömür; Bayramoglu, Mahmut

    2016-04-01

    Artificial neural networks and neuro-fuzzy inference systems are well known artificial intelligence techniques used for black-box modelling of complex systems. In this study, Feed-forward artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are used for modelling the performance of direct methanol fuel cell (DMFC). Current density (I), fuel cell temperature (T), methanol concentration (C), liquid flow-rate (q) and air flow-rate (Q) are selected as input variables to predict the cell voltage. Polarization curves are obtained for 35 different operating conditions according to a statistically designed experimental plan. In modelling study, various subsets of input variables and various types of membership function are considered. A feed -forward architecture with one hidden layer is used in ANN modelling. The optimum performance is obtained with the input set (I, T, C, q) using twelve hidden neurons and sigmoidal activation function. On the other hand, first order Sugeno inference system is applied in ANFIS modelling and the optimum performance is obtained with the input set (I, T, C, q) using sixteen fuzzy rules and triangular membership function. The test results show that ANN model estimates the polarization curve of DMFC more accurately than ANFIS model.

  12. Role of Artificial Intelligence Techniques (Automatic Classifiers) in Molecular Imaging Modalities in Neurodegenerative Diseases.

    Science.gov (United States)

    Cascianelli, Silvia; Scialpi, Michele; Amici, Serena; Forini, Nevio; Minestrini, Matteo; Fravolini, Mario Luca; Sinzinger, Helmut; Schillaci, Orazio; Palumbo, Barbara

    2017-01-01

    Artificial Intelligence (AI) is a very active Computer Science research field aiming to develop systems that mimic human intelligence and is helpful in many human activities, including Medicine. In this review we presented some examples of the exploiting of AI techniques, in particular automatic classifiers such as Artificial Neural Network (ANN), Support Vector Machine (SVM), Classification Tree (ClT) and ensemble methods like Random Forest (RF), able to analyze findings obtained by positron emission tomography (PET) or single-photon emission tomography (SPECT) scans of patients with Neurodegenerative Diseases, in particular Alzheimer's Disease. We also focused our attention on techniques applied in order to preprocess data and reduce their dimensionality via feature selection or projection in a more representative domain (Principal Component Analysis - PCA - or Partial Least Squares - PLS - are examples of such methods); this is a crucial step while dealing with medical data, since it is necessary to compress patient information and retain only the most useful in order to discriminate subjects into normal and pathological classes. Main literature papers on the application of these techniques to classify patients with neurodegenerative disease extracting data from molecular imaging modalities are reported, showing that the increasing development of computer aided diagnosis systems is very promising to contribute to the diagnostic process.

  13. A scenario for a genetically controlled fission of artificial vesicles

    DEFF Research Database (Denmark)

    Bönzli, Eva; Hadorn, Maik; Jørgensen, Mikkel Girke

    2011-01-01

    Artificial vesicles have been used for decades as model systems of biological cells to investigate scientific questions in simulacra. In recent years, the significance of artificial vesicles further increased because they represent ideal candidates to become the building block of a de novo...... construction of a cell in a bottom-up manner. Numerous efforts to build an artificial cell that bridge the living and non-living world will most presumably represent one of the main goals of science in the 21st century. It was shown that artificial genetic programs and the required cellular machinery can...... be incorporated into vesicles, and therefore allow the synthesis of a large number of proteins (Noireaux et al. 2005). However, vesicle fission remains one of the upcoming challenges in the artificial cell project (Noireaux et al. 2011). So far, vesicle fission is implemented by applying mechanical stress...

  14. Prediction of volume fractions in three-phase flows using nuclear technique and artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Marques Salgado, Cesar [Instituto de Engenharia Nuclear, DIRA/IEN/CNEN, Rio de Janeiro, CEP.: 21945-970-Caixa Postal 68550 (Brazil)], E-mail: otero@ien.gov.br; Brandao, Luis E.B. [Instituto de Engenharia Nuclear, DIRA/IEN/CNEN, Rio de Janeiro, CEP.: 21945-970-Caixa Postal 68550 (Brazil); Schirru, Roberto [Universidade Federal do Rio de Janeiro, PEN/COPPE-DNC/EE-CT, Rio de Janeiro, CEP.: 21941-972-Caixa Postal 68509 (Brazil); Pereira, Claudio M.N.A. [Instituto de Engenharia Nuclear, DIRA/IEN/CNEN, Rio de Janeiro, CEP.: 21945-970-Caixa Postal 68550 (Brazil); Silva, Ademir Xavier da [Universidade Federal do Rio de Janeiro, PEN/COPPE-DNC/EE-CT, Rio de Janeiro, CEP.: 21941-972-Caixa Postal 68509 (Brazil); Ramos, Robson [Instituto de Engenharia Nuclear, DIRA/IEN/CNEN, Rio de Janeiro, CEP.: 21945-970-Caixa Postal 68550 (Brazil)

    2009-10-15

    This work presents methodology based on nuclear technique and artificial neural network for volume fraction predictions in annular, stratified and homogeneous oil-water-gas regimes. Using principles of gamma-ray absorption and scattering together with an appropriate geometry, comprised of three detectors and a dual-energy gamma-ray source, it was possible to obtain data, which could be adequately correlated to the volume fractions of each phase by means of neural network. The MCNP-X code was used in order to provide the training data for the network.

  15. Temperature Control System Using Fuzzy Logic Technique

    Directory of Open Access Journals (Sweden)

    Isizoh A N

    2012-06-01

    Full Text Available Fuzzy logic technique is an innovative technology used in designing solutions for multi-parameter and non-linear control models for the definition of a control strategy. As a result, it delivers solutions faster than the conventional control design techniques. This paper thus presents a fuzzy logic based-temperature control system, which consists of a microcontroller, temperature sensor, and operational amplifier, Analogue to Digital Converter, display interface circuit and output interface circuit. It contains a design approach that uses fuzzy logic technique to achieve a controlled temperature output function.

  16. Global Control of the Furuta Pendulum Using Artificial Neural Networks and Feedback of State Variables

    Directory of Open Access Journals (Sweden)

    Luisa F. Escobar-Dávila

    2013-06-01

    Full Text Available This paper presents the mathematical modeling of the Furuta Pendu-lum by power functions, taking into account the non linear own dynamics of the physical systems and considering the existing couplings between the electric and mechanic devices. A control process based on feedback of state variables (FSV for the equilibrium point is developed and two topics for the non linear zone are addressed. First of all, functions are implemented to represent the energetic states of the plant in a global way and the operation regions are established (“Swing up” zone, and later Artificial Neural Networks (ANN are employed to simulate the behavior of the energy functions. Finally, it is presented the combination between the control techniques, considering the own constrains of the actuators and sensors used, besides of this, a study is done in a simulated environment of the physical phenomena that may disturb system behavior, and the capacity, sensitivity and robustness of the controller is verified.

  17. NONLINEAR MODELING AND CONTROLLING OF ARTIFICIAL MUSCLE SYSTEM USING NEURAL NETWORKS

    Institute of Scientific and Technical Information of China (English)

    Tian Sheping; Ding Guoqing; Yan Detian; Lin Liangming

    2004-01-01

    The pneumatic artificial muscles are widely used in the fields of medical robots,etc.Neural networks are applied to modeling and controlling of artificial muscle system.A single-joint artificial muscle test system is designed.The recursive prediction error (RPE) algorithm which yields faster convergence than back propagation (BP) algorithm is applied to train the neural networks.The realization of RPE algorithm is given.The difference of modeling of artificial muscles using neural networks with different input nodes and different hidden layer nodes is discussed.On this basis the nonlinear control scheme using neural networks for artificial muscle system has been introduced.The experimental results show that the nonlinear control scheme yields faster response and higher control accuracy than the traditional linear control scheme.

  18. Techniques of Ultrasound Cavitation Control

    Directory of Open Access Journals (Sweden)

    S. P. Skvortsov

    2015-01-01

    Full Text Available The control methods of ultrasonic cavitation applied now within the range from 20 kHz to 80 kHz use either control of ultrasound source parameters (amplitude, acoustic power, etc. or control of one of the cavitation effects (erosion of materials, sonoluminescence, power of acoustic noise, etc.. These methods provide effective management of technological processes, however, make it impossible to relate the estimated effect with parameters of pulsations of cavitation bubbles. This is, mainly, due to influence of a number of uncontrollable parameters, in particular, such as temperature, composition of liquid, gas content, etc. as well as because of the difficulty to establish interrelation between the estimated effect and parameters of pulsations. As a result, in most cases it is difficult to compare controlled parameters of ultrasonic cavitation among themselves, and quantitative characteristics of processes become depending on the type of ultrasonic installation and conditions of their measurement.In this regard, methods to determine parameters of bubble pulsations through sounding a cavitation area by low-intensity laser radiation or to record cavitation noise sub-harmonics reflecting dynamics of changing radius of cavitation bubbles are of interest. The method of optical sounding, via the analysis of spectral components of a scattered signal recorded by a photo-detector, allows us to define a phase of the bubbles collapse with respect to the sound wave and a moving speed of the bubbles wall, as well as to estimate a cavitation index within the light beam section.The method to record sub-harmonicas of cavitation noise allows us to define parameters of pulsations, average for cavitation areas.The above methods allow us both to study mechanisms of cavitation action and to form quantitative criteria of its efficiency based on the physical processes, rather than their consequences and are convenient for arranging a feedback in the units using

  19. Integrating Nanostructured Artificial Receptors with Whispering Gallery Mode Optical Microresonators via Inorganic Molecular Imprinting Techniques.

    Science.gov (United States)

    Hammond, G Denise; Vojta, Adam L; Grant, Sheila A; Hunt, Heather K

    2016-06-15

    The creation of label-free biosensors capable of accurately detecting trace contaminants, particularly small organic molecules, is of significant interest for applications in environmental monitoring. This is achieved by pairing a high-sensitivity signal transducer with a biorecognition element that imparts selectivity towards the compound of interest. However, many environmental pollutants do not have corresponding biorecognition elements. Fortunately, biomimetic chemistries, such as molecular imprinting, allow for the design of artificial receptors with very high selectivity for the target. Here, we perform a proof-of-concept study to show how artificial receptors may be created from inorganic silanes using the molecular imprinting technique and paired with high-sensitivity transducers without loss of device performance. Silica microsphere Whispering Gallery Mode optical microresonators are coated with a silica thin film templated by a small fluorescent dye, fluorescein isothiocyanate, which serves as our model target. Oxygen plasma degradation and solvent extraction of the template are compared. Extracted optical devices are interacted with the template molecule to confirm successful sorption of the template. Surface characterization is accomplished via fluorescence and optical microscopy, ellipsometry, optical profilometry, and contact angle measurements. The quality factors of the devices are measured to evaluate the impact of the coating on device sensitivity. The resulting devices show uniform surface coating with no microstructural damage with Q factors above 10⁶. This is the first report demonstrating the integration of these devices with molecular imprinting techniques, and could lead to new routes to biosensor creation for environmental monitoring.

  20. Integrating Nanostructured Artificial Receptors with Whispering Gallery Mode Optical Microresonators via Inorganic Molecular Imprinting Techniques

    Directory of Open Access Journals (Sweden)

    G. Denise Hammond

    2016-06-01

    Full Text Available The creation of label-free biosensors capable of accurately detecting trace contaminants, particularly small organic molecules, is of significant interest for applications in environmental monitoring. This is achieved by pairing a high-sensitivity signal transducer with a biorecognition element that imparts selectivity towards the compound of interest. However, many environmental pollutants do not have corresponding biorecognition elements. Fortunately, biomimetic chemistries, such as molecular imprinting, allow for the design of artificial receptors with very high selectivity for the target. Here, we perform a proof-of-concept study to show how artificial receptors may be created from inorganic silanes using the molecular imprinting technique and paired with high-sensitivity transducers without loss of device performance. Silica microsphere Whispering Gallery Mode optical microresonators are coated with a silica thin film templated by a small fluorescent dye, fluorescein isothiocyanate, which serves as our model target. Oxygen plasma degradation and solvent extraction of the template are compared. Extracted optical devices are interacted with the template molecule to confirm successful sorption of the template. Surface characterization is accomplished via fluorescence and optical microscopy, ellipsometry, optical profilometry, and contact angle measurements. The quality factors of the devices are measured to evaluate the impact of the coating on device sensitivity. The resulting devices show uniform surface coating with no microstructural damage with Q factors above 106. This is the first report demonstrating the integration of these devices with molecular imprinting techniques, and could lead to new routes to biosensor creation for environmental monitoring.

  1. TECHNIQUES ABOUT DIRECT OPTIMIZING CONTROL OF GREEN SAND QUALITY*

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    Green sand casting is still a main method in the world at present and it is very significant to develop the technology of controlling green sand quality. A new concept, from contents test to contents control, is advanced. In order to realize the new idea, a new method to on-line test active clay and moisture of green sand - double powers energizing alternately (DPEA) method is put forwards. The principle of the new method is to energize standard sand sample with AC and DC powers and to test the electric parameters, and then, to calculate active clay and moisture of green sand by using artificial neural network (ANN). Based on this new method, a direct optimizing system for controlling green sand quality is developed. Techniques about testing and controlling methods, hardware and software are discussed.

  2. The Changeless Technique Researches for City Flood Control and Reduced the Disaster

    Institute of Scientific and Technical Information of China (English)

    Chen Gangyi; OuYang Bolin; Xia Fan

    2006-01-01

    The make use of the stir kinetic energy conservation law, the theories and chaogeless technique build up for city flood control. Pass the system energy conversion or deliver with contain of second circulation, carry out city flood control and reduced the disaster that develops the artificial lake. It is advantageous to the improvement city ecosystem environment and resources of water that is missing.

  3. Brushless DC Motor Drive during Speed Regulation with Artificial Neural Network Controller

    OpenAIRE

    Sakshi Solanki

    2016-01-01

    Brushless DC motor, at this moment is extensively used being many industrial functions due to the different features like high efficiency and dynamic response and high speed range. This paper is proposing a technology named as Artificial Neural Network controller to control the speed of the brushless DC motor. Here the paper contributes an analysis of performance Artificial Neural Network controller. Because it is difficult to handle by the use of conventional PID controller as BL...

  4. Artificial intelligence techniques used in respiratory sound analysis--a systematic review.

    Science.gov (United States)

    Palaniappan, Rajkumar; Sundaraj, Kenneth; Sundaraj, Sebastian

    2014-02-01

    Artificial intelligence (AI) has recently been established as an alternative method to many conventional methods. The implementation of AI techniques for respiratory sound analysis can assist medical professionals in the diagnosis of lung pathologies. This article highlights the importance of AI techniques in the implementation of computer-based respiratory sound analysis. Articles on computer-based respiratory sound analysis using AI techniques were identified by searches conducted on various electronic resources, such as the IEEE, Springer, Elsevier, PubMed, and ACM digital library databases. Brief descriptions of the types of respiratory sounds and their respective characteristics are provided. We then analyzed each of the previous studies to determine the specific respiratory sounds/pathology analyzed, the number of subjects, the signal processing method used, the AI techniques used, and the performance of the AI technique used in the analysis of respiratory sounds. A detailed description of each of these studies is provided. In conclusion, this article provides recommendations for further advancements in respiratory sound analysis.

  5. Deairing Techniques for Double-Ended Centrifugal Total Artificial Heart Implantation.

    Science.gov (United States)

    Karimov, Jamshid H; Horvath, David J; Byram, Nicole; Sunagawa, Gengo; Grady, Patrick; Sinkewich, Martin; Moazami, Nader; Sale, Shiva; Golding, Leonard A R; Fukamachi, Kiyotaka

    2016-09-22

    The unique device architecture of the Cleveland Clinic continuous-flow total artificial heart (CFTAH) requires dedicated and specific air-removal techniques during device implantation in vivo. These procedures comprise special surgical techniques and intraoperative manipulations, as well as engineering design changes and optimizations to the device itself. The current study evaluated the optimal air-removal techniques during the Cleveland Clinic double-ended centrifugal CFTAH in vivo implants (n = 17). Techniques and pump design iterations consisted of developing a priming method for the device and the use of built-in deairing ports in the early cases (n = 5). In the remaining cases (n = 12), deairing ports were not used. Dedicated air-removal ports were not considered an essential design requirement, and such ports may represent an additional risk for pump thrombosis. Careful passive deairing was found to be an effective measure with a centrifugal pump of this design. In this report, the techniques and design changes that were made during this CFTAH development program to enable effective residual air removal and prevention of air embolism during in vivo device implantation are explained.

  6. Soft Computing Techniques for Process Control Applications

    Directory of Open Access Journals (Sweden)

    Rahul Malhotra

    2011-09-01

    Full Text Available Technological innovations in soft computing techniques have brought automation capabilities to new levelsof applications. Process control is an important application of any industry for controlling the complexsystem parameters, which can greatly benefit from such advancements. Conventional control theory isbased on mathematical models that describe the dynamic behaviour of process control systems. Due to lackin comprehensibility, conventional controllers are often inferior to the intelligent controllers. Softcomputing techniques provide an ability to make decisions and learning from the reliable data or expert’sexperience. Moreover, soft computing techniques can cope up with a variety of environmental and stabilityrelated uncertainties. This paper explores the different areas of soft computing techniques viz. Fuzzy logic,genetic algorithms and hybridization of two and abridged the results of different process control casestudies. It is inferred from the results that the soft computing controllers provide better control on errorsthan conventional controllers. Further, hybrid fuzzy genetic algorithm controllers have successfullyoptimized the errors than standalone soft computing and conventional techniques.

  7. Decentralized RBFNN Type-2 Fuzzy Sliding Mode Controller for Robot Manipulator Driven by Artificial Muscles

    Directory of Open Access Journals (Sweden)

    Rezoug Amar

    2012-11-01

    Full Text Available In the few last years, investigations in neural networks, fuzzy systems and their combinations become attractive research areas for modeling and controlling of uncertain systems. In this paper, we propose a new robust controller based on the integration of a Radial Base Function Neural Network (RBFNN and an Interval Type‐2 Fuzzy Logic (IT2FLC for robot manipulator actuated by pneumatic artificial muscles (PAM. The proposed approach was synthesized for each joint using Sliding Mode Control (SMC and named Radial Base Function Neural Network Type‐2 Fuzzy Sliding Mode Control (RBFT2FSMC. Several objectives can be accomplished using this control scheme such as: avoiding difficult modeling, attenuating the chattering effect of the SMC, reducing the rules number of the fuzzy control, guaranteeing the stability and the robustness of the system, and finally handling the uncertainties of the system. The proposed control approach is synthesized and the stability of the robot using this controller was analyzed using Lyapunov theory. In order to demonstrate the efficiency of the RBFT2FSMC compared to other control technique, simulations experiments were performed using linear model with parameters uncertainties obtained after identification stage. Results show the superiority of the proposed approach compared to RBFNN\tType‐1 Fuzzy SMC. Finally, an experimental study of the proposed approach was presented using 2‐ DOF robot.

  8. A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system.

    Science.gov (United States)

    Mohamed, Ahmed F; Elarini, Mahdi M; Othman, Ahmed M

    2014-05-01

    One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC). The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC) which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA) optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt.

  9. A new technique based on Artificial Bee Colony Algorithm for optimal sizing of stand-alone photovoltaic system

    Directory of Open Access Journals (Sweden)

    Ahmed F. Mohamed

    2014-05-01

    Full Text Available One of the most recent optimization techniques applied to the optimal design of photovoltaic system to supply an isolated load demand is the Artificial Bee Colony Algorithm (ABC. The proposed methodology is applied to optimize the cost of the PV system including photovoltaic, a battery bank, a battery charger controller, and inverter. Two objective functions are proposed: the first one is the PV module output power which is to be maximized and the second one is the life cycle cost (LCC which is to be minimized. The analysis is performed based on measured solar radiation and ambient temperature measured at Helwan city, Egypt. A comparison between ABC algorithm and Genetic Algorithm (GA optimal results is done. Another location is selected which is Zagazig city to check the validity of ABC algorithm in any location. The ABC is more optimal than GA. The results encouraged the use of the PV systems to electrify the rural sites of Egypt.

  10. An Analysis of the Performance of Artificial Neural Network Technique for Stock Market Forecasting

    Directory of Open Access Journals (Sweden)

    Dr. Ashutosh Kumar Bhatt

    2010-09-01

    Full Text Available In this paper, we showed a method to forecast the daily stock price using neural networks and the result of the Neural Network forecast is compared with the Statistical forecasting result. Stock price prediction is one of the emerging field in neural network forecastingarea. This paper also presents the Neural Networks ability to forecast the daily Stock Market Prices. Stock market prediction is very difficult since it depends on several known and unknown factors while the Artificial Neural Network is a popular technique for the stock market Forecasting. The Neural Network is based on the conceptof ‘Learn by Example’. In this paper, Neural Networks and Statistical techniques are employed to model and forecast the daily stock market prices and then the results of these two models are compared. The forecasting ability of these two models is accessed using MAPE, MSE and RMSE. The results show that Neural Networks, when trained with sufficient data, proper inputs and with proper architecture, can predict the stock market prices very well. Statistical technique though well built but their forecasting ability is reduced as the series become complex. Therefore, Neural Networks can be used as an better alternative technique for forecasting the daily stock market prices.

  11. Augmented Nonlinear Controller for Maximum Power-Point Tracking with Artificial Neural Network in Grid-Connected Photovoltaic Systems

    OpenAIRE

    2016-01-01

    Photovoltaic (PV) systems have non-linear characteristics that generate maximum power at one particular operating point. Environmental factors such as irradiance and temperature variations greatly affect the maximum power point (MPP). Diverse offline and online techniques have been introduced for tracking the MPP. Here, to track the MPP, an augmented-state feedback linearized (AFL) non-linear controller combined with an artificial neural network (ANN) is proposed. This approach linearizes the...

  12. ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL

    Institute of Scientific and Technical Information of China (English)

    2002-01-01

    An artificial neural network(ANN) and a self-adjusting fuzzy logic controller(FLC) for modeling and control of gas tungsten arc welding(GTAW) process are presented. The discussion is mainly focused on the modeling and control of the weld pool depth with ANN and the intelligent control for weld seam tracking with FLC. The proposed neural network can produce highly complex nonlinear multi-variable model of the GTAW process that offers the accurate prediction of welding penetration depth. A self-adjusting fuzzy controller used for seam tracking adjusts the control parameters on-line automatically according to the tracking errors so that the torch position can be controlled accurately.

  13. Evolving Spiking Neural Networks for Control of Artificial Creatures

    Directory of Open Access Journals (Sweden)

    Arash Ahmadi

    2013-10-01

    Full Text Available To understand and analysis behavior of complicated and intelligent organisms, scientists apply bio-inspired concepts including evolution and learning to mathematical models and analyses. Researchers utilize these perceptions in different applications, searching for improved methods andapproaches for modern computational systems. This paper presents a genetic algorithm based evolution framework in which Spiking Neural Network (SNN of artificial creatures are evolved for higher chance of survival in a virtual environment. The artificial creatures are composed ofrandomly connected Izhikevich spiking reservoir neural networks using population activity rate coding. Inspired by biological neurons, the neuronal connections are considered with different axonal conduction delays. Simulations results prove that the evolutionary algorithm has thecapability to find or synthesis artificial creatures which can survive in the environment successfully.

  14. An artificial pancreas for automated blood glucose control in patients with Type 1 diabetes

    DEFF Research Database (Denmark)

    Schmidt, Signe; Boiroux, Dimitri; Ranjan, Ajenthen;

    2015-01-01

    Automated glucose control in patients with Type 1 diabetes is much-coveted by patients, relatives and healthcare professionals. It is the expectation that a system for automated control, also know as an artificial pancreas, will improve glucose control, reduce the risk of diabetes complications a....... This review gives an introduction to recent progress, challenges and future prospects within the field of artificial pancreas research....

  15. Advanced Control Techniques with Fuzzy Logic

    Science.gov (United States)

    2014-06-01

    AFRL-RQ-WP-TR-2014-0175 ADVANCED CONTROL TECHNIQUES WITH FUZZY LOGIC James E. Combs Structural Validation Branch Aerospace Vehicles...TECHNIQUES WITH FUZZY LOGIC 5a. CONTRACT NUMBER In-house 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 62201F 6. AUTHOR(S) James E. Combs...unlimited. 13. SUPPLEMENTARY NOTES PA Case Number: 88ABW-2014-3281; Clearance Date: 09 Jul 2014. 14. ABSTRACT Research on the Fuzzy Logic control

  16. Automatic Level Control for Video Cameras towards HDR Techniques

    Directory of Open Access Journals (Sweden)

    de With PeterHN

    2010-01-01

    Full Text Available We give a comprehensive overview of the complete exposure processing chain for video cameras. For each step of the automatic exposure algorithm we discuss some classical solutions and propose their improvements or give new alternatives. We start by explaining exposure metering methods, describing types of signals that are used as the scene content descriptors as well as means to utilize these descriptors. We also discuss different exposure control types used for the control of lens, integration time of the sensor, and gain control, such as a PID control, precalculated control based on the camera response function, and propose a new recursive control type that matches the underlying image formation model. Then, a description of commonly used serial control strategy for lens, sensor exposure time, and gain is presented, followed by a proposal of a new parallel control solution that integrates well with tone mapping and enhancement part of the image pipeline. Parallel control strategy enables faster and smoother control and facilitates optimally filling the dynamic range of the sensor to improve the SNR and an image contrast, while avoiding signal clipping. This is archived by the proposed special control modes used for better display and correct exposure of both low-dynamic range and high-dynamic range images. To overcome the inherited problems of limited dynamic range of capturing devices we discuss a paradigm of multiple exposure techniques. Using these techniques we can enable a correct rendering of difficult class of high-dynamic range input scenes. However, multiple exposure techniques bring several challenges, especially in the presence of motion and artificial light sources such as fluorescent lights. In particular, false colors and light-flickering problems are described. After briefly discussing some known possible solutions for the motion problem, we focus on solving the fluorescence-light problem. Thereby, we propose an algorithm for

  17. Pursing Contamination Detection on Aircraft CFRP Surfaces By Artificial Olfaction Techniques

    Science.gov (United States)

    De Vito, Saverio; Massera, Ettore; Fattoruso, Grazia; Miglietta, Maria Lucia; Di Francia, Girolamo

    2011-09-01

    Carbon Fiber Reinforced Polymer (CFRP) structures can be easily bonded via adhesive assembly procedures but their cleanliness is of fundamental importance to ensure the strength of the adhesive bonding. Actually, surface contamination by several aeronautics fluids eventually results in weak or kissing bonds. The goal of our research work is to investigate solid state chemical sensors and artificial olfaction techniques (AO) for the detection of CFRP surface contamination by aeronautic fluids. This result will allow the implementation of an instrumental NDT procedure for CFRP surface cleanliness assessment prior to bonding. Herein, results of our first experimental setup, based on the use of an array of polymer sensors for the detection of aeronautic fluids contamination, are presented.

  18. Artificial intelligence for the modeling and control of combustion processes: a review

    Energy Technology Data Exchange (ETDEWEB)

    Soteris A. Kalogirou, [Higher Technical Institute, Nicosia (Cyprus). Department of Mechanical Engineering

    2003-07-01

    Artificial intelligence (AI) systems are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems, and once trained can perform prediction and generalization at high speed. They have been used in diverse applications in control, robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimization, signal processing, and social/psychological sciences. They are particularly useful in system modeling such as in implementing complex mappings and system identification. AI systems comprise areas like, expert systems, artificial neural networks, genetic algorithms, fuzzy logic and various hybrid systems, which combine two or more techniques. The major objective of this paper is to illustrate how AI techniques might play an important role in modeling and prediction of the performance and control of combustion process. The paper outlines an understanding of how AI systems operate by way of presenting a number of problems in the different disciplines of combustion engineering. The various applications of AI are presented in a thematic rather than a chronological or any other order. Problems presented include two main areas: combustion systems and internal combustion (IC) engines. Combustion systems include boilers, furnaces and incinerators modeling and emissions prediction, whereas, IC engines include diesel and spark ignition engines and gas engines modeling and control. Results presented in this paper, are testimony to the potential of AI as a design tool in many areas of combustion engineering. 109 refs., 31 figs., 11 tabs.

  19. Artificial intelligence for the modeling and control of combustion processes: a review

    Energy Technology Data Exchange (ETDEWEB)

    Kalogirou, S.A. [Higher Technical Inst., Nicosia, Cyprus (Greece). Dept. of Mechanical Engineering

    2003-07-01

    Artificial intelligence (AI) systems are widely accepted as a technology offering an alternative way to tackle complex and ill-defined problems. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with non-linear problems, and once trained can perform prediction and generalization at high speed. They have been used in diverse applications in control, robotics, pattern recognition, forecasting, medicine, power systems, manufacturing, optimization, signal processing, and social/psychological sciences. They are particularly useful in system modeling such as in implementing complex mappings and system identification. Al systems comprise areas like, expert systems, artificial neural networks, genetic algorithms, fuzzy logic and various hybrid systems, which combine two or more techniques. The major objective of this paper is to illustrate how Al techniques might play an important role in modeling and prediction of the performance and control of combustion process. The paper outlines an understanding of how AI systems operate by way of presenting a number of problems in the different disciplines of combustion engineering. The various applications of AI are presented in a thematic rather than a chronological or any other order. Problems presented include two main areas: combustion systems and internal combustion (IC) engines. Combustion systems include boilers, furnaces and incinerators modeling and emissions prediction, whereas, IC engines include diesel and spark ignition engines and gas engines modeling and control. Results presented in this paper, are testimony to the potential of Al as a design tool in many areas of combustion engineering. (author)

  20. Tracking Control of a Leg Rehabilitation Machine Driven by Pneumatic Artificial Muscles Using Composite Fuzzy Theory

    Directory of Open Access Journals (Sweden)

    Ming-Kun Chang

    2014-01-01

    Full Text Available It is difficult to achieve excellent tracking performance for a two-joint leg rehabilitation machine driven by pneumatic artificial muscles (PAMs because the system has a coupling effect, highly nonlinear and time-varying behavior associated with gas compression, and the nonlinear elasticity of bladder containers. This paper therefore proposes a T-S fuzzy theory with supervisory control in order to overcome the above problems. The T-S fuzzy theory decomposes the model of a nonlinear system into a set of linear subsystems. In this manner, the controller in the T-S fuzzy model is able to use simple linear control techniques to provide a systematic framework for the design of a state feedback controller. Then the LMI Toolbox of MATLAB can be employed to solve linear matrix inequalities (LMIs in order to determine controller gains based on the Lyapunov direct method. Moreover, the supervisory control can overcome the coupling effect for a leg rehabilitation machine. Experimental results show that the proposed controller can achieve excellent tracking performance, and guarantee robustness to system parameter uncertainties.

  1. Controlling pneumatic artificial muscles in exoskeletons with surface electromyography

    NARCIS (Netherlands)

    Groenhuis, Vincent; Chandrapal, Mervin; Stramigioli, Stefano; Chen, XiaoQi

    2014-01-01

    Powered exoskeletons are gaining more interest in the last few years, as useful devices to provide assistance to elderly and disabled people. Many different types of powered exoskeletons have been studied in the past. In this research paper, a soft lower limb exoskeleton driven by pneumatic artifici

  2. Implementations of artificial neural networks using current-mode pulse width modulation technique.

    Science.gov (United States)

    El-Masry, E I; Yang, H K; Yakout, M A

    1997-01-01

    The use of a current-mode pulse width modulation (CM-PWM) technique to implement analog artificial neural networks (ANNs) is presented. This technique can be used to efficiently implement the weighted summation operation (WSO) that are required in the realization of a general ANN. The sigmoidal transformation is inherently performed by the nonlinear transconductance amplifier, which is a key component in the current integrator used in the realization of WSO. The CM-PWM implementation results in a minimum silicon area, and therefore is suitable for very large scale neural systems. Other pronounced features of the CM-PWM implementation are its easy programmability, electronically adjustable gains of neurons, and modular structures. In this paper, all the current-mode CMOS circuits (building blocks) required for the realization of CM-PWM ANNs are presented and simulated. Four modules for modular design of ANNs are introduced. Also, it is shown that the CM-PWM technique is an efficient method for implementing discrete-time cellular neural networks (DT-CNNs). Two application examples are given: a winner-take-all circuit and a connected component detector.

  3. Assisted Reproductive Techniques in Farm Animal - From Artificial Insemination to Nanobiotechnology

    Directory of Open Access Journals (Sweden)

    O P Verma

    2012-10-01

    Full Text Available It has become evident that advances in farm animal reproduction have become increasingly dependent on advance scientific research in addition to an understanding of the physiological processes involved in reproduction. The use of assisted reproductive techniques (ART has helped owners to produce offspring from valuable farm animals that were considered infertile using standard breeding techniques. This chapter constitutes an update of recent developments in the field of assisted reproduction includes Artificial insemination, Embryo transfer, in vitro fertilization, embryo cryopreservation, Sexing of semen and embryos, cloning, transgenesis, stem cell technology, embryo genomics, micro and nanotechnology has been included. Recently in some of these fields remarkable progress has been made. None the less, imperfections are remaining and sustained efforts will be required to optimize existing and invent new technologies. Before referring an animal for an ART, the practitioner should be able to identify the underlying cause of subfertility of that animal. Knowing the complexity as well as the risks of these techniques, enables practitioners to refer a sub-fertile animal to the least complex and most appropriate and successful ART that can overcome specific causes of infertility. [Vet. World 2012; 5(5.000: 301-310

  4. Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques.

    Directory of Open Access Journals (Sweden)

    Hazlee Azil Illias

    Full Text Available It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN and particle swarm optimisation (PSO techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works.

  5. Transformer Incipient Fault Prediction Using Combined Artificial Neural Network and Various Particle Swarm Optimisation Techniques.

    Science.gov (United States)

    Illias, Hazlee Azil; Chai, Xin Rui; Abu Bakar, Ab Halim; Mokhlis, Hazlie

    2015-01-01

    It is important to predict the incipient fault in transformer oil accurately so that the maintenance of transformer oil can be performed correctly, reducing the cost of maintenance and minimise the error. Dissolved gas analysis (DGA) has been widely used to predict the incipient fault in power transformers. However, sometimes the existing DGA methods yield inaccurate prediction of the incipient fault in transformer oil because each method is only suitable for certain conditions. Many previous works have reported on the use of intelligence methods to predict the transformer faults. However, it is believed that the accuracy of the previously proposed methods can still be improved. Since artificial neural network (ANN) and particle swarm optimisation (PSO) techniques have never been used in the previously reported work, this work proposes a combination of ANN and various PSO techniques to predict the transformer incipient fault. The advantages of PSO are simplicity and easy implementation. The effectiveness of various PSO techniques in combination with ANN is validated by comparison with the results from the actual fault diagnosis, an existing diagnosis method and ANN alone. Comparison of the results from the proposed methods with the previously reported work was also performed to show the improvement of the proposed methods. It was found that the proposed ANN-Evolutionary PSO method yields the highest percentage of correct identification for transformer fault type than the existing diagnosis method and previously reported works.

  6. Supervised Online Adaptive Control of Inverted Pendulum System Using ADALINE Artificial Neural Network with Varying System Parameters and External Disturbance

    Directory of Open Access Journals (Sweden)

    Sudeep Sharma

    2012-07-01

    Full Text Available Generalized Adaptive Linear Element (GADALINE Artificial Neural Network (ANN as an Artificial Intelligence (AI technique is used in this paper to online adaptive control of a Non-linear Inverted Pendulum (IP system. The ANN controller is designed with specifications as: network type is three (Input, Hidden and Output layered Feed-Forward Network (FFN, training is done by Widrow-Hoffs delta rule or Least Mean Square algorithm (LMS, that updates weight and bias states to minimize the error function. The research is focused on how to adapt the control actions to solve the problem of “parameter variations”. The method is applied to the Nonlinear IP model with the application of some uncertainties, and the experimental results show that the system responds very well to handle those uncertainties.

  7. Active load control techniques for wind turbines.

    Energy Technology Data Exchange (ETDEWEB)

    van Dam, C.P. (University of California, Davis, CA); Berg, Dale E.; Johnson, Scott J. (University of California, Davis, CA)

    2008-07-01

    This report provides an overview on the current state of wind turbine control and introduces a number of active techniques that could be potentially used for control of wind turbine blades. The focus is on research regarding active flow control (AFC) as it applies to wind turbine performance and loads. The techniques and concepts described here are often described as 'smart structures' or 'smart rotor control'. This field is rapidly growing and there are numerous concepts currently being investigated around the world; some concepts already are focused on the wind energy industry and others are intended for use in other fields, but have the potential for wind turbine control. An AFC system can be broken into three categories: controls and sensors, actuators and devices, and the flow phenomena. This report focuses on the research involved with the actuators and devices and the generated flow phenomena caused by each device.

  8. Sensorless Direct Power Control of Induction Motor Drive Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Abolfazl Halvaei Niasar

    2015-01-01

    Full Text Available This paper proposes the design of sensorless induction motor drive based on direct power control (DPC technique. It is shown that DPC technique enjoys all advantages of pervious methods such as fast dynamic and ease of implementation, without having their problems. To reduce the cost of drive and enhance the reliability, an effective sensorless strategy based on artificial neural network (ANN is developed to estimate rotor’s position and speed of induction motor. Developed sensorless scheme is a new model reference adaptive system (MRAS speed observer for direct power control induction motor drives. The proposed MRAS speed observer uses the current model as an adaptive model. The neural network has been then designed and trained online by employing a back propagation network (BPN algorithm. The estimator was designed and simulated in Simulink. Some simulations are carried out for the closed-loop speed control systems under various load conditions to verify the proposed methods. Simulation results confirm the performance of ANN based sensorless DPC induction motor drive in various conditions.

  9. Volume fraction prediction in biphasic flow using nuclear technique and artificial neural network

    Energy Technology Data Exchange (ETDEWEB)

    Salgado, Cesar M.; Brandao, Luis E.B., E-mail: otero@ien.gov.br, E-mail: brandao@ien.gov.br [Instituto de Engenharia Nuclear (IEN/CNEN-RJ), Rio de Janeiro, RJ (Brazil)

    2015-07-01

    The volume fraction is one of the most important parameters used to characterize air-liquid two-phase flows. It is a physical value to determine other parameters, such as the phase's densities and to determine the flow rate of each phase. These parameters are important to predict the flow pattern and to determine a mathematical model for the system. To study, for example, heat transfer and pressure drop. This work presents a methodology for volume fractions prediction in water-gas stratified flow regime using the nuclear technique and artificial intelligence. The volume fractions calculate in biphasic flow systems is complex and the analysis by means of analytical equations becomes very difficult. The approach is based on gamma-ray pulse height distributions pattern recognition by means of the artificial neural network. The detection system uses appropriate broad beam geometry, comprised of a ({sup 137}Cs) energy gamma-ray source and a NaI(Tl) scintillation detector in order measure transmitted beam whose the counts rates are influenced by the phases composition. These distributions are directly used by the network without any parameterization of the measured signal. The ideal and static theoretical models for stratified regime have been developed using MCNP-X code, which was used to provide training, test and validation data for the network. The detector also was modeled with this code and the results were compared to experimental photopeak efficiency measurements of radiation sources. The proposed network could obtain with satisfactory prediction of the volume fraction in water-gas system, demonstrating to be a promising approach for this purpose. (author)

  10. Artificial intelligence techniques coupled with seasonality measures for hydrological regionalization of Q90 under Brazilian conditions

    Science.gov (United States)

    Beskow, Samuel; de Mello, Carlos Rogério; Vargas, Marcelle M.; Corrêa, Leonardo de L.; Caldeira, Tamara L.; Durães, Matheus F.; de Aguiar, Marilton S.

    2016-10-01

    Information on stream flows is essential for water resources management. The stream flow that is equaled or exceeded 90% of the time (Q90) is one the most used low stream flow indicators in many countries, and its determination is made from the frequency analysis of stream flows considering a historical series. However, stream flow gauging network is generally not spatially sufficient to meet the necessary demands of technicians, thus the most plausible alternative is the use of hydrological regionalization. The objective of this study was to couple the artificial intelligence techniques (AI) K-means, Partitioning Around Medoids (PAM), K-harmonic means (KHM), Fuzzy C-means (FCM) and Genetic K-means (GKA), with measures of low stream flow seasonality, for verification of its potential to delineate hydrologically homogeneous regions for the regionalization of Q90. For the performance analysis of the proposed methodology, location attributes from 108 watersheds situated in southern Brazil, and attributes associated with their seasonality of low stream flows were considered in this study. It was concluded that: (i) AI techniques have the potential to delineate hydrologically homogeneous regions in the context of Q90 in the study region, especially the FCM method based on fuzzy logic, and GKA, based on genetic algorithms; (ii) the attributes related to seasonality of low stream flows added important information that increased the accuracy of the grouping; and (iii) the adjusted mathematical models have excellent performance and can be used to estimate Q90 in locations lacking monitoring.

  11. Artificial intelligent techniques for optimizing water allocation in a reservoir watershed

    Science.gov (United States)

    Chang, Fi-John; Chang, Li-Chiu; Wang, Yu-Chung

    2014-05-01

    This study proposes a systematical water allocation scheme that integrates system analysis with artificial intelligence techniques for reservoir operation in consideration of the great uncertainty upon hydrometeorology for mitigating droughts impacts on public and irrigation sectors. The AI techniques mainly include a genetic algorithm and adaptive-network based fuzzy inference system (ANFIS). We first derive evaluation diagrams through systematic interactive evaluations on long-term hydrological data to provide a clear simulation perspective of all possible drought conditions tagged with their corresponding water shortages; then search the optimal reservoir operating histogram using genetic algorithm (GA) based on given demands and hydrological conditions that can be recognized as the optimal base of input-output training patterns for modelling; and finally build a suitable water allocation scheme through constructing an adaptive neuro-fuzzy inference system (ANFIS) model with a learning of the mechanism between designed inputs (water discount rates and hydrological conditions) and outputs (two scenarios: simulated and optimized water deficiency levels). The effectiveness of the proposed approach is tested on the operation of the Shihmen Reservoir in northern Taiwan for the first paddy crop in the study area to assess the water allocation mechanism during drought periods. We demonstrate that the proposed water allocation scheme significantly and substantially avails water managers of reliably determining a suitable discount rate on water supply for both irrigation and public sectors, and thus can reduce the drought risk and the compensation amount induced by making restrictions on agricultural use water.

  12. Egg volume prediction using machine vision technique based on pappus theorem and artificial neural network.

    Science.gov (United States)

    Soltani, Mahmoud; Omid, Mahmoud; Alimardani, Reza

    2015-05-01

    Egg size is one of the important properties of egg that is judged by customers. Accordingly, in egg sorting and grading, the size of eggs must be considered. In this research, a new method of egg volume prediction was proposed without need to measure weight of egg. An accurate and efficient image processing algorithm was designed and implemented for computing major and minor diameters of eggs. Two methods of egg size modeling were developed. In the first method, a mathematical model was proposed based on Pappus theorem. In second method, Artificial Neural Network (ANN) technique was used to estimate egg volume. The determined egg volume by these methods was compared statistically with actual values. For mathematical modeling, the R(2), Mean absolute error and maximum absolute error values were obtained as 0.99, 0.59 cm(3) and 1.69 cm(3), respectively. To determine the best ANN, R(2) test and RMSEtest were used as selection criteria. The best ANN topology was 2-28-1 which had the R(2) test and RMSEtest of 0.992 and 0.66, respectively. After system calibration, the proposed models were evaluated. The results which indicated the mathematical modeling yielded more satisfying results. So this technique was selected for egg size determination.

  13. Median Sternotomy or Right Thoracotomy Techniques for Total Artificial Heart Implantation in Calves.

    Science.gov (United States)

    Karimov, Jamshid H; Moazami, Nader; Sunagawa, Gengo; Kobayashi, Mariko; Byram, Nicole; Sale, Shiva; Such, Kimberly A; Horvath, David J; Golding, Leonard A R; Fukamachi, Kiyotaka

    2016-10-01

    The choice of optimal operative access technique for mechanical circulatory support device implantation ensures successful postoperative outcomes. In this study, we retrospectively evaluated the median sternotomy and lateral thoracotomy incisions for placement of the Cleveland Clinic continuous-flow total artificial heart (CFTAH) in a bovine model. The CFTAH was implanted in 17 calves (Jersey calves; weight range, 77.0-93.9 kg) through a median sternotomy (n = 9) or right thoracotomy (n = 8) for elective chronic implantation periods of 14, 30, or 90 days. Similar preoperative preparation, surgical techniques, and postoperative care were employed. Implantation of the CFTAH was successfully performed in all cases. Both methods provided excellent surgical field visualization. After device connection, however, the median sternotomy approach provided better visualization of the anastomoses and surgical lines for hemostasis confirmation and repair due to easier device displacement, which is severely limited following right thoracotomy. All four animals sacrificed after completion of the planned durations (up to 90 days) were operated through full median sternotomy. Our data demonstrate that both approaches provide excellent initial field visualization. Full median sternotomy provides larger viewing angles at the anastomotic suture line after device connection to inflow and outflow ports.

  14. Active Vibration Control of the Smart Plate Using Artificial Neural Network Controller

    Directory of Open Access Journals (Sweden)

    Mohit

    2015-01-01

    Full Text Available The active vibration control (AVC of a rectangular plate with single input and single output approach is investigated using artificial neural network. The cantilever plate of finite length, breadth, and thickness having piezoelectric patches as sensors/actuators fixed at the upper and lower surface of the metal plate is considered for examination. The finite element model of the cantilever plate is utilized to formulate the whole strategy. The compact RIO and MATLAB simulation software are exercised to get the appropriate results. The cantilever plate is subjected to impulse input and uniform white noise disturbance. The neural network is trained offline and tuned with LQR controller. The various training algorithms to tune the neural network are exercised. The best efficient algorithm is finally considered to tune the neural network controller designed for active vibration control of the smart plate.

  15. Active Noise Control Using a Functional Link Artificial Neural Network with the Simultaneous Perturbation Learning Rule

    Directory of Open Access Journals (Sweden)

    Ya-li Zhou

    2009-01-01

    Full Text Available In practical active noise control (ANC systems, the primary path and the secondary path may be nonlinear and time-varying. It has been reported that the linear techniques used to control such ANC systems exhibit degradation in performance. In addition, the actuators of an ANC system very often have nonminimum-phase response. A linear controller under such situations yields poor performance. A novel functional link artificial neural network (FLANN-based simultaneous perturbation stochastic approximation (SPSA algorithm, which functions as a nonlinear mode-free (MF controller, is proposed in this paper. Computer simulations have been carried out to demonstrate that the proposed algorithm outperforms the standard filtered-x least mean square (FXLMS algorithm, and performs better than the recently proposed filtered-s least mean square (FSLMS algorithm when the secondary path is time-varying. This observation implies that the SPSA-based MF controller can eliminate the need of the modeling of the secondary path for the ANC system.

  16. Artificial neural networks based controller for glucose monitoring during clamp test.

    Directory of Open Access Journals (Sweden)

    Merav Catalogna

    Full Text Available Insulin resistance (IR is one of the most widespread health problems in modern times. The gold standard for quantification of IR is the hyperinsulinemic-euglycemic glucose clamp technique. During the test, a regulated glucose infusion is delivered intravenously to maintain a constant blood glucose concentration. Current control algorithms for regulating this glucose infusion are based on feedback control. These models require frequent sampling of blood, and can only partly capture the complexity associated with regulation of glucose. Here we present an improved clamp control algorithm which is motivated by the stochastic nature of glucose kinetics, while using the minimal need in blood samples required for evaluation of IR. A glucose pump control algorithm, based on artificial neural networks model was developed. The system was trained with a data base collected from 62 rat model experiments, using a back-propagation Levenberg-Marquardt optimization. Genetic algorithm was used to optimize network topology and learning features. The predictive value of the proposed algorithm during the temporal period of interest was significantly improved relative to a feedback control applied at an equivalent low sampling interval. Robustness to noise analysis demonstrates the applicability of the algorithm in realistic situations.

  17. Evaluation of biological control agents for mosquitoes control in artificial breeding places

    Institute of Scientific and Technical Information of China (English)

    Salim Abadi Yaser; Vatandoost Hassan; Rassi Yavar; Abai Mohammad Reza; Sanei Dehkordi Ali Reza; Paksa Azim

    2010-01-01

    Objective:To evaluate the entomological impact of chlorpyrifos-methyl,Bacillus thuringiensis, andGambusia affinis on mosquitoes control in artificial breeding places.Methods:A Latin square design with 4 replicates was performed in order to evaluate the efficacy of chlorpyrifos-methyl,Bacillus thuringiensis, andGambusia affinis on larva. The larvicide was applied at the dosage of 100 mg a.h/ha,Bacillus thuringiensis at the recommended dosage and 10 fishes per m2 were applied at 1í1 m2 artificial breeding sites. The larval densities for both anopheline and culicine were counted according to larvae /10 dippers prior and 24 h after application.Results:All three control agents are effective for mosquito density reduction, and the difference between the three agents and the control is significant (P<0.05). There is also significant difference among chlorpyrifos-methyl,Bacillus thuringiensis andGambusia affinis.Bacillus thuringiensisexhibited more reduction on mosquito larval density than fish and larvicide (P<0.05).Conclusions:Bacillus thuringiensis in comparison with two other agents is the appropriate method for larviciding in the breeding places. Although long term assessing for biological activities as well as monitoring and mapping of resistance is required.

  18. Implantation technique of the 50-cm3 SynCardia Total Artificial Heart: does size make a difference?

    Science.gov (United States)

    Spiliopoulos, Sotirios; Guersoy, Dilek; Dimitriou, Alexandros Merkourios; Koerfer, Reiner; Tenderich, Gero

    2015-01-01

    Despite downsizing, implantation technique of the 50-cm(3) SynCardia Total Artificial Heart and settings of the Companion driver remain unchanged. Owing to the absence of de-airing nipples, de-airing procedure is even more crucial and has to be performed carefully.

  19. Ultrasonic techniques for process monitoring and control.

    Energy Technology Data Exchange (ETDEWEB)

    Chien, H.-T.

    1999-03-24

    Ultrasonic techniques have been applied successfully to process monitoring and control for many industries, such as energy, medical, textile, oil, and material. It helps those industries in quality control, energy efficiency improving, waste reducing, and cost saving. This paper presents four ultrasonic systems, ultrasonic viscometer, on-loom, real-time ultrasonic imaging system, ultrasonic leak detection system, and ultrasonic solid concentration monitoring system, developed at Argonne National Laboratory in the past five years for various applications.

  20. Using artificial intelligence to control fluid flow computations

    Science.gov (United States)

    Gelsey, Andrew

    1992-01-01

    Computational simulation is an essential tool for the prediction of fluid flow. Many powerful simulation programs exist today. However, using these programs to reliably analyze fluid flow and other physical situations requires considerable human effort and expertise to set up a simulation, determine whether the output makes sense, and repeatedly run the simulation with different inputs until a satisfactory result is achieved. Automating this process is not only of considerable practical importance but will also significantly advance basic artificial intelligence (AI) research in reasoning about the physical world.

  1. Control of Interfacial Phenomena in Artificial Oxide Heterostructures

    Science.gov (United States)

    2015-09-01

    superconductor  that likely rely on a  detailed  knowledge of the interface  structure  determined here.   Reference: K. Zou, S. Mandal, F.J. Walker...Artificial Oxide  Structures , Institute of  Physics, CAS, Beijing, China. (Invited Talk)   “Extreme carrier concentrations and  metallic  conductions in thin...heterostructures. Moreover, we have extended our research to the interfaces of complex oxides and transition metal chalcogenides with novel emergent

  2. Industrial applications of advanced control techniques

    Institute of Scientific and Technical Information of China (English)

    刘国平

    2003-01-01

    This paper discusses two industrial control applications using advanced control techniques. They are theoptimal-tuning nonlinear PID control of hydraulic systems and the neural predictive control of combustor acoustic ofgas turbines. For hydraulic control systems, an optimal PID controller with inverse of dead zone is introduced toovercome the dead zone and is designed to satisfy desired time-domain performance requirements. Using the adaptivemodel, an optimal-tuning PID control scheme is proposed to provide optimal PID parameters even in the case wherethe system dynamics is time variant. For combustor acoustic control of gas turbines, a neural predictive controlstrategy is presented, which consists of three parts: an output model, output predictor and feedback controller. Theoutput model of the combustor acoustic is established using neural networks to predict the output and overcome thetime delay of the system, which is often very large, compared with the sampling period. The output-feedback con-troller is introduced which uses the output of the predictor to suppress instability in the combustion process. The a-bove control strategies are implemented in the SIMULINK/dSPACE controller development environment. Theirperformance is evaluated on the industrial hydraulic test rig and the industrial combustor test rig.

  3. Error mapping controller: a closed loop neuroprosthesis controlled by artificial neural networks

    Directory of Open Access Journals (Sweden)

    De Momi Elena

    2006-10-01

    Full Text Available Abstract Background The design of an optimal neuroprostheses controller and its clinical use presents several challenges. First, the physiological system is characterized by highly inter-subjects varying properties and also by non stationary behaviour with time, due to conditioning level and fatigue. Secondly, the easiness to use in routine clinical practice requires experienced operators. Therefore, feedback controllers, avoiding long setting procedures, are required. Methods The error mapping controller (EMC here proposed uses artificial neural networks (ANNs both for the design of an inverse model and of a feedback controller. A neuromuscular model is used to validate the performance of the controllers in simulations. The EMC performance is compared to a Proportional Integral Derivative (PID included in an anti wind-up scheme (called PIDAW and to a controller with an ANN as inverse model and a PID in the feedback loop (NEUROPID. In addition tests on the EMC robustness in response to variations of the Plant parameters and to mechanical disturbances are carried out. Results The EMC shows improvements with respect to the other controllers in tracking accuracy, capability to prolong exercise managing fatigue, robustness to parameter variations and resistance to mechanical disturbances. Conclusion Different from the other controllers, the EMC is capable of balancing between tracking accuracy and mapping of fatigue during the exercise. In this way, it avoids overstressing muscles and allows a considerable prolongation of the movement. The collection of the training sets does not require any particular experimental setting and can be introduced in routine clinical practice.

  4. Appraisal of artificial screening techniques of tomato to accurately reflect field performance of the late blight resistance.

    Directory of Open Access Journals (Sweden)

    Marzena Nowakowska

    Full Text Available Late blight (LB caused by the oomycete Phytophthora infestans continues to thwart global tomato production, while only few resistant cultivars have been introduced locally. In order to gain from the released tomato germplasm with LB resistance, we compared the 5-year field performance of LB resistance in several tomato cultigens, with the results of controlled conditions testing (i.e., detached leaflet/leaf, whole plant. In case of these artificial screening techniques, the effects of plant age and inoculum concentration were additionally considered. In the field trials, LA 1033, L 3707, L 3708 displayed the highest LB resistance, and could be used for cultivar development under Polish conditions. Of the three methods using controlled conditions, the detached leaf and the whole plant tests had the highest correlation with the field experiments. The plant age effect on LB resistance in tomato reported here, irrespective of the cultigen tested or inoculum concentration used, makes it important to standardize the test parameters when screening for resistance. Our results help show why other reports disagree on LB resistance in tomato.

  5. Appraisal of artificial screening techniques of tomato to accurately reflect field performance of the late blight resistance.

    Science.gov (United States)

    Nowakowska, Marzena; Nowicki, Marcin; Kłosińska, Urszula; Maciorowski, Robert; Kozik, Elżbieta U

    2014-01-01

    Late blight (LB) caused by the oomycete Phytophthora infestans continues to thwart global tomato production, while only few resistant cultivars have been introduced locally. In order to gain from the released tomato germplasm with LB resistance, we compared the 5-year field performance of LB resistance in several tomato cultigens, with the results of controlled conditions testing (i.e., detached leaflet/leaf, whole plant). In case of these artificial screening techniques, the effects of plant age and inoculum concentration were additionally considered. In the field trials, LA 1033, L 3707, L 3708 displayed the highest LB resistance, and could be used for cultivar development under Polish conditions. Of the three methods using controlled conditions, the detached leaf and the whole plant tests had the highest correlation with the field experiments. The plant age effect on LB resistance in tomato reported here, irrespective of the cultigen tested or inoculum concentration used, makes it important to standardize the test parameters when screening for resistance. Our results help show why other reports disagree on LB resistance in tomato.

  6. A comparative study of the detectability of TMJ radiographic techniques for artificial mandibular condylar lesions

    Energy Technology Data Exchange (ETDEWEB)

    Jeong, Hee Jeong; Jung, Yeon Hwa; Cho, Bong Hae [Dept. of Oral and Maxillofacial Radiology, College of Dentistry, Pusan National University, Pusan(Korea, Republic of)

    1997-08-15

    The purpose of this study was to evaluate the detectability of various radiographic techniques for mandibular condylar lesions. Erosive lesion, osteophyte and flattening were formed on the artificial mandibular condyle, and panoramic, transcranial, transorbital radiography, lateral and frontal tomography were taken. The results were as follows; 1. The detectability for erosive lesions was superior in the order of frontal tomography (96%), lateral tomography (78%), transorbital (59%), transcranial (56%) and panoramic (48%) radiography. 2. The location of erosive lesion that showed the highest detectability was the medial third in panoramic, the lateral third in transcranial, the central portion of anteroposterior direction in transorbital, the central portion of mediolateral direction and the posterior third in lateral tomography. Frontal tomography disclosed all erosive lesions except one anterolateral lesion. 3. The detectability of osteophyte was 100% in lateral tomography, 78% in transcranial and 56% in panoramic radiography. 4. For flattening, lateral tomography showed the flattened condyle, but both panoramic and transcranial views showed only decreased bone density without the change of condylar shape.

  7. Multidisciplinary Techniques and Novel Aircraft Control Systems

    Science.gov (United States)

    Padula, Sharon L.; Rogers, James L.; Raney, David L.

    2000-01-01

    The Aircraft Morphing Program at NASA Langley Research Center explores opportunities to improve airframe designs with smart technologies. Two elements of this basic research program are multidisciplinary design optimization (MDO) and advanced flow control. This paper describes examples where MDO techniques such as sensitivity analysis, automatic differentiation, and genetic algorithms contribute to the design of novel control systems. In the test case, the design and use of distributed shape-change devices to provide low-rate maneuvering capability for a tailless aircraft is considered. The ability of MDO to add value to control system development is illustrated using results from several years of research funded by the Aircraft Morphing Program.

  8. Estimation of Sub Hourly Glacier Albedo Values Using Artificial Intelligence Techniques

    Science.gov (United States)

    Moya Quiroga, Vladimir; Mano, Akira; Asaoka, Yoshihiro; Udo, Keiko; Kure, Shuichi; Mendoza, Javier

    2013-04-01

    Glaciers are the most important fresh water reservoirs storing about 67% of total fresh water. Unfortunately, they are retreating and some small glaciers have already disappeared. Thus, snow glacier melt (SGM) estimation plays an important role in water resources management. Whether SGM is estimated by complete energy balance or a simplified method, albedo is an important data present in most of the methods. However, this is a variable value depending on the ground surface and local conditions. The present research presents a new approach for estimating sub hourly albedo values using different artificial intelligence techniques such as artificial neural networks and decision trees along with measured and easy to obtain data. . The models were developed using measured data from the Zongo-Ore station located in the Bolivian tropical glacier Zongo (68°10' W, 16°15' S). This station automatically records every 30 minutes several meteorological parameters such as incoming short wave radiation, outgoing short wave radiation, temperature or relative humidity. The ANN model used was the Multi Layer Perceptron, while the decision tree used was the M5 model. Both models were trained using the WEKA software and validated using the cross validation method. After analysing the model performances, it was concluded that the decision tree models have a better performance. The model with the best performance was then validated with measured data from the Equatorian tropical glacier Antizana (78°09'W, 0°28'S). The model predicts the sub hourly albedo with an overall mean absolute error of 0.103. The highest errors occur for albedo measured values higher than 0.9. Considering that this is an extreme value coincident with low measured values of incoming short wave radiation, it is reasonable to assume that such values include errors due to censored data. Assuming a maximum albedo of 0.9 improved the accuracy of the model reducing the MAE to less than 0.1. Considering that the

  9. Artificial Leg Design and Control Research of a Biped Robot with Heterogeneous Legs Based on PID Control Algorithm

    Directory of Open Access Journals (Sweden)

    Hualong Xie

    2015-04-01

    Full Text Available A biped robot with heterogeneous legs (BRHL is proposed to provide an ideal test-bed for intelligent bionic legs (IBL. To make artificial leg gait better suited to a human, a four-bar mechanism is used as its knee joint, and a pneumatic artificial muscle (PAM is used as its driving source. The static mathematical model of PAM is established and the mechanical model of a single degree of freedom of a knee joint driven by PAM is analyzed. A control simulation of an artificial leg based on PID control algorithm is carried out and the simulation results indicate that the artificial leg can simulate precisely a normal human walking gait.

  10. Vibration control of an artificial muscle manipulator with a magnetorheological fluid brake

    Science.gov (United States)

    Tomori, H.; Midorikawa, Y.; Nakamura, T.

    2013-02-01

    Recently, proposed applications of robots require them to contact human safely. Therefore, we focus on pneumatic rubber artificial muscle. This actuator is flexible, light, and has high-power density. However, because the artificial muscle is flexible, it vibrates when there is a high load. Therefore, we paid attention to the magnetorheological (MR) fluid. We propose a control method of the MR brake considering energy of the manipulator system. By this control method, MR brake dissipates energy leading to vibration of the manipulator. In this paper, we calculated the energy and controlled the MR brake. And, we deliberated the proposal method by simulation using the dynamic model of the manipulator, and experiment.

  11. Adaptive Artificial Intelligence Based Model Base Controller: Applied to Surgical Endoscopy Telemanipulator

    Directory of Open Access Journals (Sweden)

    Farzin Piltan

    2013-08-01

    Full Text Available This research involved developing a surgical robot assistant using an articulated PUMA robot running on a linear or nonlinear axis. The research concentrated on studying the artificial intelligence based switching computed torque controller to localization of an endoscopic tool. Results show that the switching artificial nonlinear control algorithm is capable to design a stable controller. For this system, error was used as the performance metric. Positioning of the endoscopic manipulator relative to the world coordinate frame was possible to within 0.05 inch. Error in maintaining a constant point in space is evident during repositioning however this was caused by limitations in the robot arm.

  12. Human factors issues in the use of artificial intelligence in air traffic control. October 1990 Workshop

    Science.gov (United States)

    Hockaday, Stephen; Kuhlenschmidt, Sharon (Editor)

    1991-01-01

    The objective of the workshop was to explore the role of human factors in facilitating the introduction of artificial intelligence (AI) to advanced air traffic control (ATC) automation concepts. AI is an umbrella term which is continually expanding to cover a variety of techniques where machines are performing actions taken based upon dynamic, external stimuli. AI methods can be implemented using more traditional programming languages such as LISP or PROLOG, or they can be implemented using state-of-the-art techniques such as object-oriented programming, neural nets (hardware or software), and knowledge based expert systems. As this technology advances and as increasingly powerful computing platforms become available, the use of AI to enhance ATC systems can be realized. Substantial efforts along these lines are already being undertaken at the FAA Technical Center, NASA Ames Research Center, academic institutions, industry, and elsewhere. Although it is clear that the technology is ripe for bringing computer automation to ATC systems, the proper scope and role of automation are not at all apparent. The major concern is how to combine human controllers with computer technology. A wide spectrum of options exists, ranging from using automation only to provide extra tools to augment decision making by human controllers to turning over moment-by-moment control to automated systems and using humans as supervisors and system managers. Across this spectrum, it is now obvious that the difficulties that occur when tying human and automated systems together must be resolved so that automation can be introduced safely and effectively. The focus of the workshop was to further explore the role of injecting AI into ATC systems and to identify the human factors that need to be considered for successful application of the technology to present and future ATC systems.

  13. Optimum Design of Fractional Order PID Controller for an AVR System Using an Improved Artificial Bee Colony Algorithm

    Institute of Scientific and Technical Information of China (English)

    ZHANG Dong-Li; TANG Ying-Gan; GUAN Xin-Ping

    2014-01-01

    Fractional order proportional-integral-derivative (FOPID) controller generalizes the standard PID controller. Compared to PID controller, FOPID controller has more pa-rameters and the tuning of parameters is more complex. In this paper, an improved artificial bee colony algorithm, which com-bines cyclic exchange neighborhood with chaos (CNC-ABC), is proposed for the sake of tuning the parameters of FOPID con-troller. The characteristic of the proposed CNC-ABC exists in two folds: one is that it enlarges the search scope of the solution by utilizing cyclic exchange neighborhood techniques, speeds up the convergence of artificial bee colony algorithm (ABC). The other is that it has potential to get out of local optima by exploit-ing the ergodicity of chaos. The proposed CNC-ABC algorithm is used to optimize the parameters of the FOPID controller for an automatic voltage regulator (AVR) system. Numerical sim-ulations show that the CNC-ABC FOPID controller has better performance than other FOPID and PID controllers.

  14. Applying Space Technology to Enhance Control of an Artificial Arm for Children and Adults With Amputations

    Science.gov (United States)

    Atkins, Diane J.

    1998-01-01

    The first single function myoelectric prosthetic hand was introduced in the 1960's. This hand was controlled by the electric fields generated by muscle contractions in the residual limb of the amputee user. Electrodes and amplifiers, embedded in the prosthetic socket, measured these electric fields across the skin, which increase in amplitude as the individual contracts their muscle. When the myoelectric signal reached a certain threshold amplitude, the control unit activated a motor which opened or closed a hand-like prosthetic terminal device with a pincher grip. Late in the 1990's, little has changed. Most current myoelectric prostheses still operate in this same, single-function way. To better understand the limitations of the current single-function myoelectric hand and the needs of those who use them, The Institute for Rehabilitation and Research (TIRR), sponsored by the National Institutes of Health (NUH), surveyed approximately 2,500 individuals with upper limb loss [1]. When asked to identify specific features of their current myoelectric prostheses that needed improvement, the survey respondents overwhelmingly identified the lack of wrist and finger movement, as well as poor control capability. However, simply building a mechanism with individual finger and wrist motion is not enough. In the 1960's and 1970's, engineers built a number of more dexterous prosthetic hands. Unfortunately, these were rejected during clinical trials due to a difficult and distracting control interface. The goal of this project, "Applying Space Technology to Enhance Control of an Artificial Arm for Children and Adults with Amputations," was to lay the foundation for a multi-function, intuitive myoelectric control system which requires no conscious thought to move the hand. We built an extensive myoelectric signal database for six motions from ten amputee volunteers, We also tested a control system based on new artificial intelligence techniques on the data from two of these

  15. Artificial intelligence in process control: Knowledge base for the shuttle ECS model

    Science.gov (United States)

    Stiffler, A. Kent

    1989-01-01

    The general operation of KATE, an artificial intelligence controller, is outlined. A shuttle environmental control system (ECS) demonstration system for KATE is explained. The knowledge base model for this system is derived. An experimental test procedure is given to verify parameters in the model.

  16. Application of Artificial Neural Network in Active Vibration Control of Diesel Engine

    Institute of Scientific and Technical Information of China (English)

    SUN Cheng-shun; ZHANG Jian-wu

    2005-01-01

    Artificial Neural Network (ANN) is applied to diesel twostage vibration isolating system and an AVC (Active Vibration Control) system is developed. Both identifier and controller are constructed by three-layer BP neural network. Besides computer simulation, experiment research is carried out on both analog bench and diesel bench. The results of simulation and experiment show a diminished response of vibration.

  17. An Optimal Control of Bone Marrow in Cancer Chemotherapy by Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    H. Hosseinipour

    2015-09-01

    Full Text Available Although neural network models for cancer chemotherapy have been analyzed since the early seventies, less research has been done in actually formulating them as optimal control problems. In this paper an artificial neural networks-based method for optimal control of bone marrow in cell-cycle-specific chemotherapy is proposed. In this method, we use artificial neural networks for approximating the optimal control problem which maximizes both bone marrow mass and drug`s dose at the same time. The corresponding model be transfer to Hamiltonian function and using Pontryagin principle we create the boundary conditions. After defining boundary conditions, we use the approximating property of artificial networks and put the boundary conditions in error functions to satisfy the limitations..

  18. Adaptive Sampling for WSAN Control Applications Using Artificial Neural Networks

    OpenAIRE

    2012-01-01

    Wireless sensor actuator networks are becoming a solution for control applications. Reliable data transmission and real time constraints are the most significant challenges. Control applications will have some Quality of Service (QoS) requirements from the sensor network, such as minimum delay and guaranteed delivery of packets. We investigate variable sampling method to mitigate the effects of time delays in wireless networked control systems using an observer based control system model. Our...

  19. Controlled artificial upwelling in a fjord to combat toxic algae

    Science.gov (United States)

    McClimans, T. A.; Hansen, A. H.; Fredheim, A.; Lien, E.; Reitan, K. I.

    2003-04-01

    During the summer, primary production in the surface layers of some fjords depletes the nutrients to the degree that some arts of toxic algae dominate the flora. We describe an experiment employing a bubble curtain to lift significant amounts of nutrient-rich seawater to the light zone and provide an environment in which useful algae can survive. The motivation for the experiment is to provide a local region in which mussels can be cleansed from the effects of toxic algae. Three 100-m long, perforated pipes were suspended at 40 m depth in the Arnafjord, a side arm of the Sognefjord. Large amounts of compressed air were supplied during a period of three weeks. The deeper water mixed with the surface water and flowed from the mixing region at 5 to 15 m depth. Within a few days, the mixture of nutrient-rich water covered most of the inner portion of Arnafjord. Within 10 days, the plankton samples showed that the artificial upwelling produced the desired type of algae and excluded the toxic blooms that were occurring outside the manipulated fjord arm. The project (DETOX) is supported by the Norwegian ministries of Fisheries, Agriculture and Public Administration.

  20. PERFORMANCE OF PID CONTROLLER OF NONLINEAR SYSTEM USING SWARM INTELLIGENCE TECHNIQUES

    Directory of Open Access Journals (Sweden)

    Neeraj Jain

    2016-07-01

    Full Text Available In this paper swarm intelligence based PID controller tuning is proposed for a nonlinear ball and hoop system. Particle swarm optimization (PSO, Artificial bee colony (ABC, Bacterial foraging optimization (BFO is some example of swarm intelligence techniques which are focused for PID controller tuning. These algorithms are also tested on perturbed ball and hoop model. Integral square error (ISE based performance index is used for finding the best possible value of controller parameters. Matlab software is used for designing the ball and hoop model. It is found that these swarm intelligence techniques have easy implementation & lesser settling & rise time compare to conventional methods.

  1. Mechanisms controlling the artificial aging of Al-Mg-Si Alloys

    Energy Technology Data Exchange (ETDEWEB)

    Pogatscher, S., E-mail: stefan.pogatscher@unileoben.ac.at [Institute of Nonferrous Metallurgy, Montanuniversitaet Leoben, Franz-Josef-Strasse 18, 8700 Leoben (Austria); Antrekowitsch, H. [Institute of Nonferrous Metallurgy, Montanuniversitaet Leoben, Franz-Josef-Strasse 18, 8700 Leoben (Austria); Leitner, H. [Department of Physical Metallurgy and Materials Testing, Montanuniversitaet Leoben, Franz-Josef-Strasse 18, 8700 Leoben (Austria); Ebner, T. [AMAG Rolling GmbH, Postfach 32, 5282 Ranshofen (Austria); Uggowitzer, P.J. [Laboratory of Metal Physics and Technology, Department of Materials, ETH Zurich, Wolfgang-Pauli-Strasse 10, 8093 Zurich (Switzerland)

    2011-05-15

    Highlights: > Artificial aging of Al-Mg-Si alloys in the range of 150 and 250 deg. C. > We study precipitation kinetics caused by various thermal histories. > Natural pre-aging affects kinetics at low artificial aging temperatures. > Natural pre-aging promotes kinetics at high artificial aging temperatures. > A vacancy-prison mechanism explains the effect of natural pre-aging. - Abstract: In this study the artificial aging behavior of the Al-Mg-Si alloy AA 6061 was investigated in the temperature range 150-250 deg. C using atom probe tomography, hardness and resistivity measurements for various thermal histories. It was found that the precipitation kinetics and age-hardening response of artificial aging at temperatures below 210 deg. C are lowered by prior natural aging but enhanced above this temperature. An analysis of hardness data was used to evaluate the temperature dependence of precipitation kinetics and dissolution processes. Supported by theoretical considerations, it is assumed that artificial aging of Al-Mg-Si alloys is controlled via the concentration of mobile vacancies. The 'vacancy-prison mechanism' proposed determines the mobile vacancy concentration in the case of natural pre-aging by temperature-dependent dissolution of co-clusters and solute-vacancy interactions.

  2. Artificial Intelligence Approach to Support Statistical Quality Control Teaching

    Science.gov (United States)

    Reis, Marcelo Menezes; Paladini, Edson Pacheco; Khator, Suresh; Sommer, Willy Arno

    2006-01-01

    Statistical quality control--SQC (consisting of Statistical Process Control, Process Capability Studies, Acceptance Sampling and Design of Experiments) is a very important tool to obtain, maintain and improve the Quality level of goods and services produced by an organization. Despite its importance, and the fact that it is taught in technical and…

  3. Cooperative adaptive cruise control: An artificial potential field approach

    NARCIS (Netherlands)

    Semsar-Kazerooni, E.; Verhaegh, J.; Ploeg, J.; Alirezaei, M.

    2016-01-01

    In this paper, in addition to the main functionality of vehicle following, cooperative adaptive cruise control (CACC) is enabled with additional features of gap closing and collision avoidance. Due to its nonlinear nature, a control objective such as collision avoidance, cannot be addressed using a

  4. Real-time remote control of artificial cilia actuation using fingertip drawing for efficient micromixing.

    Science.gov (United States)

    Chen, Chia-Yuan; Yao, Chih-Yuan; Lin, Cheng-Yi; Hung, Shih-Hsuan

    2014-10-01

    Low-efficiency diffusion mechanism poses a significant barrier to the enhancement of micromixing efficiency in microfluidics. Actuating artificial cilia to increase the contact area of two flow streams during micromixing provides a promising alternative to enhance the mixing performance. Real-time adjustment of beating behavior in artificial cilia is necessary to accommodate various biological/chemical reagents with different hydrodynamic properties that are processed in a single microfluidic platform during micromixing. Equipping the microfluidic device with a self-troubleshooting feature for the end user, such as a bubble removal function during the process of multiple chemical solution injections, is also essential for robust micromixing. To meet these requirements, we initiated a new beating control concept by controlling the beating behavior of the artificial cilia through remote and simultaneous actuation of human fingertip drawing. A series of micromixing test cases under extreme flow conditions (Re technical difficulties encountered during micromixing operations.

  5. Design and performance of heart assist or artificial heart control systems

    Science.gov (United States)

    Webb, J. A., Jr.; Gebben, V. D.

    1978-01-01

    The factors leading to the design of a controlled driving system for either a heart assist pump or artificial heart are discussed. The system provides square pressure waveform to drive a pneumatic-type blood pump. For assist usage the system uses an R-wave detector circuit that can detect the R-wave of the electrocardiogram in the presence of electrical disturbances. This circuit provides a signal useful for synchronizing an assist pump with the natural heart. It synchronizes a square wave circuit, the output of which is converted into square waveforms of pneumatic pressure suitable for driving both assist device and artificial heart. The pressure levels of the driving waveforms are controlled by means of feedback channels to maintain physiological regulation of the artificial heart's output flow. A more compact system that could achieve similar regulatory characteristics is also discussed.

  6. Adaptive artificial neural network for autonomous robot control

    Science.gov (United States)

    Arras, Michael K.; Protzel, Peter W.; Palumbo, Daniel L.

    1992-01-01

    The topics are presented in viewgraph form and include: neural network controller for robot arm positioning with visual feedback; initial training of the arm; automatic recovery from cumulative fault scenarios; and error reduction by iterative fine movements.

  7. Mosquito Control Techniques Developed for the US Military

    Science.gov (United States)

    The USDA developed and field tested new techniques to reduce the risk to deployed military troops from vector-borne diseases. Some of the methods developed included (1) novel military personal protection methods, (2) barrier treatments of artificial materials and natural vegetation, and (3) ground a...

  8. Novel USDA Mosquito Control Techniques for the US Military

    Science.gov (United States)

    Novel techniques that we developed at the USDA to protect deployed military troops from the threat of vector-borne diseases are described. Some of the methods developed included (1) novel military personal protection methods, (2) barrier treatments of artificial materials and natural vegetation, and...

  9. Artificial frozen orbit control scheme based on J2 perturbation

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Since the inclination of frozen orbit with non-rotation of the perigee that occurs due to J2 perturbation must be equal to the critical inclination, this regulation has restricted the application of frozen orbit a lot. In this paper, we propose two control strategies to eliminate the secular growth of the argument of the perigee for orbits that are not at the critical inclination. One control strategy is using transverse continuous low-thrust, and the other is using both the transverse and the radial continuous low-thrusts. Fuel optimization in the second control strategy is addressed to make sure that the fuel consumption is the minimum. Both strategies have no effect on other orbital parameters’ secular motion. It is proved that the strategy with transverse control could save more energy than the one with radial control. Simulations show that the second control strategy could save 54.6% and 86% of energy, respectively, compared with the two methods presented in the references.

  10. Optimal control of end-port glass tank furnace regenerator temperature based on artificial neural network

    Institute of Scientific and Technical Information of China (English)

    CHEN Xi; ZHAO Guo-zhu

    2005-01-01

    In the paper, an artificial neural network (ANN) method is put forward to optimize melting temperature control, which reveals the nonlinear relationships of tank melting temperature disturbances with secondary wind flow and fuel pressure, implements dynamic feed-forward complementation and dynamic correctional ratio between air and fuel in the main control system. The application to Anhui Fuyang Glass Factory improved the control character of the melting temperature greatly.

  11. Fuzzy Controller Design Using Evolutionary Techniques for Twin Rotor MIMO System: A Comparative Study

    Directory of Open Access Journals (Sweden)

    H. A. Hashim

    2015-01-01

    Full Text Available This paper presents a comparative study of fuzzy controller design for the twin rotor multi-input multioutput (MIMO system (TRMS considering most promising evolutionary techniques. These are gravitational search algorithm (GSA, particle swarm optimization (PSO, artificial bee colony (ABC, and differential evolution (DE. In this study, the gains of four fuzzy proportional derivative (PD controllers for TRMS have been optimized using the considered techniques. The optimization techniques are developed to identify the optimal control parameters for system stability enhancement, to cancel high nonlinearities in the model, to reduce the coupling effect, and to drive TRMS pitch and yaw angles into the desired tracking trajectory efficiently and accurately. The most effective technique in terms of system response due to different disturbances has been investigated. In this work, it is observed that GSA is the most effective technique in terms of solution quality and convergence speed.

  12. Artificial Intelligence Applied to the Command, Control, Communications, and Intelligence of the U.S. Central Command.

    Science.gov (United States)

    1983-06-06

    these components will be presented. 4.17 °°,. CHAPTER III FOOTNOTES 1. Arron Barr and Edward A. Feigenbaum, eds., Te Handbook gf Artificial Inteligence ol...RD-R137 205 ARTIFICIAL INTELLIGENCE APPLIED TO THE COMIMAND CONTROL i/i COMMUNICATIONS RND..(U) ARMY WAR COLL CARLISLE BARRACKS U PA J N ENVART 06...appropriate mlitary servic or *swesmment aency. ARTIFICIAL INTELLIGENCE APPLIED TO THE COMMAND, CONTROL, COMMUNICATIONS, AND INTELLIGENCE OF THE U.S. CENTRAL

  13. Balancing Training Techniques for Flight Controller Certification

    Science.gov (United States)

    Gosling, Christina

    2011-01-01

    Training of ground control teams has been a difficult task in space operations. There are several intangible skills that must be learned to become the steely eyed men and women of mission control who respond to spacecraft failures that can lead to loss of vehicle or crew if handled improperly. And as difficult as training is, it can also be costly. Every day, month or year an operator is in training, is a day that not only they are being trained without direct benefit to the organization, but potentially an instructor or mentor is also being paid for hours spent assisting them. Therefore, optimization of the training flow is highly desired. Recently the Expedition Division (DI) at Johnson Space Flight Center has recreated their training flows for the purpose of both moving to an operator/specialist/instructor hierarchy and to address past inefficiencies in the training flow. This paper will discuss the types of training DI is utilizing in their new flows, and the balance that has been struck between the ideal learning environments and realistic constraints. Specifically, the past training flow for the ISS Attitude Determination and Control Officer will be presented, including drawbacks that were encountered. Then the new training flow will be discussed and how a new approach utilizes more training methods and teaching techniques. We will look at how DI has integrated classes, workshops, checkouts, module reviews, scenarios, OJT, paper sims, Mini Sims, and finally Integrated Sims to balance the cost and timing of training a new flight controller.

  14. Artificial Neural Network Based Rotor Capacitive Reactance Control for Energy Efficient Wound Rotor Induction Motor

    Directory of Open Access Journals (Sweden)

    K. Siva Kumar

    2012-01-01

    Full Text Available Problem statement: The Rotor reactance control by inclusion of external capacitance in the rotor circuit has been in recent research for improving the performances of Wound Rotor Induction Motor (WRIM. The rotor capacitive reactance is adjusted such that for any desired load torque the efficiency of the WRIM is maximized. The rotor external capacitance can be controlled using a dynamic capacitor in which the duty ratio is varied for emulating the capacitance value. This study presents a novel technique for tracking maximum efficiency point in the entire operating range of WRIM using Artificial Neural Network (ANN. The data for ANN training were obtained on a three phase WRIM with dynamic capacitor control and rotor short circuit at different speed and load torque values. Approach: A novel neural network model based on the back-propagation algorithm has been developed and trained in determining the maximum efficiency of the motor with no prior knowledge of the machine parameters. The input variables to the ANN are stator current (Is, Speed (N and Torque (Tm and the output variable is the duty ratio (D. Results: The target is pre-set and the accuracy of the ANN model is measured using Mean Square Error (MSE and R2 parameters. The result of R2 value of the proposed ANN model is found to be 0.99980. Conclusion: The optimal duty ratio and corresponding optimal rotor capacitance for improving the performances of the motor are predicted for low, medium and full loads by using proposed ANN model.

  15. Application of an artificial neural network and morphing techniques in the redesign of dysplastic trochlea.

    Science.gov (United States)

    Cho, Kyung Jin; Müller, Jacobus H; Erasmus, Pieter J; DeJour, David; Scheffer, Cornie

    2014-01-01

    Segmentation and computer assisted design tools have the potential to test the validity of simulated surgical procedures, e.g., trochleoplasty. A repeatable measurement method for three dimensional femur models that enables quantification of knee parameters of the distal femur is presented. Fifteen healthy knees are analysed using the method to provide a training set for an artificial neural network. The aim is to use this artificial neural network for the prediction of parameter values that describe the shape of a normal trochlear groove geometry. This is achieved by feeding the artificial neural network with the unaffected parameters of a dysplastic knee. Four dysplastic knees (Type A through D) are virtually redesigned by way of morphing the groove geometries based on the suggested shape from the artificial neural network. Each of the four resulting shapes is analysed and compared to its initial dysplastic shape in terms of three anteroposterior dimensions: lateral, central and medial. For the four knees the trochlear depth is increased, the ventral trochlear prominence reduced and the sulcus angle corrected to within published normal ranges. The results show a lateral facet elevation inadequate, with a sulcus deepening or a depression trochleoplasty more beneficial to correct trochlear dysplasia.

  16. Genetic diversity analysis of mitochondrial DNA control region in artificially propagated Chinese sucker Myxocyprinus asiaticus.

    Science.gov (United States)

    Wan, Yuan; Zhou, Chun-Hua; Ouyang, Shan; Huang, Xiao-Chen; Zhan, Yang; Zhou, Ping; Rong, Jun; Wu, Xiao-Ping

    2015-08-01

    The genetic diversity of the three major artificially propagated populations of Chinese sucker, an endangered freshwater fish species, was investigated using the sequences of mitochondrial DNA (mtDNA) control regions. Among the 89 individuals tested, 66 variable sites (7.26%) and 10 haplotypes were detected (Haplotype diversity Hd = 0.805, Nucleotide diversity π = 0.0287). In general, genetic diversity was lower in artificially propagated populations than in wild populations. This reduction in genetic diversity may be due to population bottlenecks, genetic drift and human selection. A stepping-stone pattern of gene flow was detected in the populations studied, showing much higher gene flow between neighbouring populations. To increase the genetic diversity, wild lineages should be introduced, and more lineages should be shared among artificially propagated populations.

  17. Controllable rectification of the axial expansion in the thermally driven artificial muscle

    Science.gov (United States)

    Yue, Donghua; Zhang, Xingyi; Yong, Huadong; Zhou, Jun; Zhou, You-He

    2015-09-01

    At present, the concept of artificial muscle twisted by polymers or fibers has become a hot issue in the field of intelligent material research according to its distinguishing advantages, e.g., high energy density, large-stroke, non-hysteresis, and inexpensive. The axial thermal expansion coefficient is an important parameter which can affect its demanding applications. In this letter, a device with high accuracy capacitive sensor is constructed to measure the axial thermal expansion coefficient of the twisted carbon fibers and yarns of Kevlar, and a theoretical model based on the thermal elasticity and the geometrical features of the twisted structure are also presented to predict the axial expansion coefficient. It is found that the calculated results take good agreements with the experimental data. According to the present experiment and analyses, a method to control the axial thermal expansion coefficient of artificial muscle is proposed. Moreover, the mechanism of this kind of thermally driven artificial muscle is discussed.

  18. Genetic Fuzzy Logic Control Technique for a Mobile Robot Tracking a Moving Target

    Directory of Open Access Journals (Sweden)

    Karim Benbouabdallah

    2013-01-01

    Full Text Available Target tracking is a crucial function for an autonomous mobile robot navigating in unknown environments. This paper presents a mobile robot target tracking approach based on artificial intelligence techniques. The proposed controller calculates both the mobile robot linear and angular velocities from the distance and angle that separate it to the moving target. The controller was designed using fuzzy logics theory and then, a genetic algorithm was applied to optimize the scaling factors of the fuzzy logic controller for better accuracy and smoothness of the robot trajectory. Simulation results illustrate that the proposed controller leads to good performances in terms of computational time and tracking errors convergence.

  19. Artificial intelligence techniques to optimize the EDC/NHS-mediated immobilization of cellulase on Eudragit L-100.

    Science.gov (United States)

    Zhang, Yu; Xu, Jing-Liang; Yuan, Zhen-Hong; Qi, Wei; Liu, Yun-Yun; He, Min-Chao

    2012-01-01

    Two artificial intelligence techniques, namely artificial neural network (ANN) and genetic algorithm (GA) were combined to be used as a tool for optimizing the covalent immobilization of cellulase on a smart polymer, Eudragit L-100. 1-Ethyl-3-(3-dimethyllaminopropyl) carbodiimide (EDC) concentration, N-hydroxysuccinimide (NHS) concentration and coupling time were taken as independent variables, and immobilization efficiency was taken as the response. The data of the central composite design were used to train ANN by back-propagation algorithm, and the result showed that the trained ANN fitted the data accurately (correlation coefficient R(2) = 0.99). Then a maximum immobilization efficiency of 88.76% was searched by genetic algorithm at a EDC concentration of 0.44%, NHS concentration of 0.37% and a coupling time of 2.22 h, where the experimental value was 87.97 ± 6.45%. The application of ANN based optimization by GA is quite successful.

  20. Artificial Intelligence Techniques to Optimize the EDC/NHS-Mediated Immobilization of Cellulase on Eudragit L-100

    Science.gov (United States)

    Zhang, Yu; Xu, Jing-Liang; Yuan, Zhen-Hong; Qi, Wei; Liu, Yun-Yun; He, Min-Chao

    2012-01-01

    Two artificial intelligence techniques, namely artificial neural network (ANN) and genetic algorithm (GA) were combined to be used as a tool for optimizing the covalent immobilization of cellulase on a smart polymer, Eudragit L-100. 1-Ethyl-3-(3-dimethyllaminopropyl) carbodiimide (EDC) concentration, N-hydroxysuccinimide (NHS) concentration and coupling time were taken as independent variables, and immobilization efficiency was taken as the response. The data of the central composite design were used to train ANN by back-propagation algorithm, and the result showed that the trained ANN fitted the data accurately (correlation coefficient R2 = 0.99). Then a maximum immobilization efficiency of 88.76% was searched by genetic algorithm at a EDC concentration of 0.44%, NHS concentration of 0.37% and a coupling time of 2.22 h, where the experimental value was 87.97 ± 6.45%. The application of ANN based optimization by GA is quite successful. PMID:22942683

  1. Artificial and Natural Sensors in FES-assisted Human Movement Control

    OpenAIRE

    Veltink, Peter H.; Sinkjaer, Thomas; Baten, Chris T.M.; Bergveld, Piet; Spek, van der, R.J.; Haugland, Morten

    1998-01-01

    The availability of small and light micromachined sensors for human use and the demonstration that useful signals can be derived from the natural sensors of the human body have enabled new developments in the area of feedback controlled FES assistance of human movements. This paper presents the need for sensory feedback in FES control systems and gives an overview of available artificial sensors for human use and progress in the derivation and application of signals from natural sensors

  2. Applying Space Technology to Enhance Control of an Artificial Arm

    Science.gov (United States)

    Atkins, Diane; Donovan, William H.; Novy, Mara; Abramczyk, Robert

    1997-01-01

    At the present time, myoelectric prostheses perform only one function of the hand: open and close with the thumb, index and middle finger coming together to grasp various shaped objects. To better understand the limitations of the current single-function prostheses and the needs of the individuals who use them, The Institute for Rehabilitation and Research (TIRR), sponsored by the National Institutes of Health (August 1992 - November 1994), surveyed approximately 2500 individuals with upper limb loss. When asked to identify specific features of their current electric prosthesis that needed improvement, the survey respondents overwhelmingly identified the lack of wrist and finger movement as well as poor control capability. Simply building a mechanism with individual finger and wrist motion is not enough. Individuals with upper limb loss tend to reject prostheses that require continuous visual monitoring and concentration to control. Robotics researchers at NASA's Johnson Space Center (JSC) and Rice University have made substantial progress in myoelectric teleoperation. A myoelectric teleoperation system translates signals generated by an able-bodied robot operator's muscles during hand motions into commands that drive a robot's hand through identical motions. Farry's early work in myoelectric teleoperation used variations over time in the myoelectric spectrum as inputs to neural networks to discriminate grasp types and thumb motions. The resulting schemes yielded up to 93% correct classification on thumb motions. More recently, Fernandez achieved 100% correct non-realtime classification of thumb abduction, extension, and flexion on the same myoelectric data. Fernandez used genetic programming to develop functions that discriminate between thumb motions using myoelectric signal parameters. Genetic programming (GP) is an evolutionary programming method where the computer can modify the discriminating functions' form to improve its performance, not just adjust

  3. Brushless DC Motor Drive during Speed Regulation with Artificial Neural Network Controller

    Directory of Open Access Journals (Sweden)

    Sakshi Solanki

    2016-06-01

    Full Text Available Brushless DC motor, at this moment is extensively used being many industrial functions due to the different features like high efficiency and dynamic response and high speed range. This paper is proposing a technology named as Artificial Neural Network controller to control the speed of the brushless DC motor. Here the paper contributes an analysis of performance Artificial Neural Network controller. Because it is difficult to handle by the use of conventional PID controller as BLDC drive is a nonlinear. Through PID controller, the speed regulation of BLDC is not efficient and reliable as PID controller cannot operate the large data, results it gives different variation in BLDC motor control. The ANN easily trains the data of large amount by NN toolbox. As ANN controller has the strength to indulge characteristics of control and it is accessible to operate the huge amount of data as like human can store in a mind. The empirical results prove that an ANN controller can better control the act than the PID controller. The modelling, control and the simulation of the BLDCM get done by applying MATLAB/SIMULINK software kit.

  4. Progressive artificial endocrine pancreas: The era of novel perioperative blood glucose control for surgery.

    Science.gov (United States)

    Tsukamoto, Yuuki; Okabayashi, Takehiro; Hanazaki, Kazuhiro

    2011-10-01

    Strict glycemic control needs to be maintained in critically ill surgical patients to reduce the mortality and morbidity due to hyperglycemia and associated infection. However, conventional intensive insulin therapy (IIT), which consists of intermittent blood glucose measurement and manually controlled infusions of insulin, tends to induce hypoglycemia and glucose variability. Many randomized clinical trials have been conducted to improve the efficacy of IIT, although some of these were stopped owing to frequent hypoglycemia. In pursuing safe and strict glycemic control for critically ill surgical patients, we found that a closed-loop glycemic control system was able to maintain appropriate blood glucose levels without hypoglycemia in more than 400 clinical cases. Considering the need for the perioperative and intensive care environment, a well-established artificial pancreas was modified into a new closed-loop glycemic control system, called the progressive artificial pancreas. The new device is slim in shape and shows clinical compatibility with the conventional artificial pancreas. We herein review this new closed-loop glycemic control system and the expectations for its future application in critically ill surgical patients.

  5. Comparison of Artificial Neural Network And M5 Model Tree Technique In Water Level Forecasting of Solo River

    Science.gov (United States)

    Lasminto, Umboro; Hery Mularta, Listya

    2010-05-01

    Flood events along the Solo River flow at the end of December 2007 has caused lose of properties and lives. Floods occurred in the city of Ngawi, Madiun, Bojonegoro, Babat and surrounding areas. To reduce future losses, one of the important efforts that will occur during a flood is to get information about the magnitude and time will be floods, so that people can make an effort to reduce its impact. Flood forecasting model can provide information of water level in the river some time before the incident. This paper will compare the flood forecasting model at Bojonegoro City was built using the technique of Artificial Neural Network (ANN) and M5 Model Tree (M5MT). The model will forecast the water level of 1, 3 and 6 hours ahead at the point of water level recorders in the City of Bojonegoro using input from the water level at some point water level recorders in the upstream such as Karangnongko, Sekayu, Jurug and Wonogiri. The same data set of hourly water level records are used to build the model of ANN and M5MT technique. The selection of parameters and setup of ANN and M5MT technique is done to obtain the best result. The results of the model are evaluated by calculating the Root Mean Square Error (RMSE) between the predictions and observations. RMSE produced by the water level forecasting model 1, 3 and 6 hours ahead with M5MT technique are 0.2723, 0.6279 and 0.7176 meters. While the ANN technique are 0.1829, 0.3192 and 0517 meters. ANN technique has a better ability in predicting low flow, whereas M5 Model Tree technique has a better ability in predicting high flow. Keywords : Water level forecasting, Solo River, M5 Model Tree, Artificial Neural Network

  6. Decade Review (1999-2009): Artificial Intelligence Techniques in Student Modeling

    Science.gov (United States)

    Drigas, Athanasios S.; Argyri, Katerina; Vrettaros, John

    Artificial Intelligence applications in educational field are getting more and more popular during the last decade (1999-2009) and that is why much relevant research has been conducted. In this paper, we present the most interesting attempts to apply artificial intelligence methods such as fuzzy logic, neural networks, genetic programming and hybrid approaches such as neuro - fuzzy systems and genetic programming neural networks (GPNN) in student modeling. This latest research trend is a part of every Intelligent Tutoring System and aims at generating and updating a student model in order to modify learning content to fit individual needs or to provide reliable assessment and feedback to student's answers. In this paper, we make a brief presentation of methods used to point out their qualities and then we attempt a navigation to the most representative studies sought in the decade of our interest after classifying them according to the principal aim they attempted to serve.

  7. Side-scan sonar techniques for the characterization of physical properties of artificial benthic habitats

    Directory of Open Access Journals (Sweden)

    Wen-Miin Tian

    2011-01-01

    Full Text Available Side-scan sonar observations conducted at Mito artificial habitat site in the southwest coast off Taiwan, documented the locations of both concrete cubic blocks (more than 10,000 units and scrapped steel boats (39 units deployed previously. Based on their geographic locations, the concrete cubic artificial reefs could be grouped into 14 reef sets. About 30% of the reefs were deployed out of the promulgated site area. For the purpose of artificial habitat site identification and fishery resources management, a database structure was designed to accommodate types and positions of reefs, information of reef sets, bathymetric contours, textures of bottom sediments and geomorphological characteristics. The effectiveness of Mito artificial habitat site was evaluated to be positive after the deployment of both concrete block reefs and steel boat reefs.Observações com sonar de varredura lateral ao largo de Mito na costa sudoeste de Taiwan, revelou a localização de mais de 10.000 blocos de concreto e 39 embarcações de ferro assentados previamente como recifes artificiais. Com base nas imagens obtidas, os cubos de concreto formam 14 grupos separados. Cerca de 30% das unidades de concreto foram assentadas fora das áreas previstas. Para a identificacão correta dos recifes artificiais e manejo adequado dos recursos pesqueiros, foi organizada uma base de dados com informações sobre forma, materiais e posição, e arranjo espacial das unidades recifais, bem como dados de batimetria, natureza do sedimento do fundo e geomorfologia. A eficiência dos recifes artificiais de Mito foi avaliada positivamente após o assentamento tanto das unidades de concreto quanto das embarcações de ferro.

  8. Prediction of Human intestinal absorption of compounds using artificial intelligence techniques.

    Science.gov (United States)

    Kumar, Rajnish; Sharma, Anju; Siddiqui, Mohammed Haris; Tiwari, Rajesh Kumar

    2017-04-04

    Information about Pharmacokinetics of compounds is an essential component of drug design and development. Modeling the pharmacokinetic properties require identification of the factors effecting absorption, distribution, metabolism and excretion of compounds. There have been continuous attempts in the prediction of absorption of compounds using various Artificial intelligence methods in the effort to reduce the attrition rate of drug candidates entering to preclinical and clinical trials. Currently, there are large numbers of individual predictive models available for absorption using machine learning approaches. In current work, we are presenting a comprehensive study of prediction of absorption. Six Artificial intelligence methods namely, Support vector machine, k- nearest neighbor, Probabilistic neural network, Artificial neural network, Partial least square and Linear discriminant analysis were used for prediction of absorption of compounds with prediction accuracy of 91.54%, 88.33%, 84.30%, 86.51%, 79.07% and 80.08% respectively. Comparative analysis of all the six prediction models suggested that Support vector machine with Radial basis function based kernel is comparatively better for binary classification of compounds using human intestinal absorption and may be useful at preliminary stages of drug design and development.

  9. Design and implementation of an adaptive single pole autoreclosure technique for transmission lines using artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Fitton, D.S.; Dunn, R.W.; Aggarwal, R.K.; Johns, A.T. [Univ. of Bath (United Kingdom). School of Electronic and Electrical Engineering; Bennett, A. [Reyrolle Protection, Hebburn (United Kingdom)

    1996-04-01

    Adaptive Single Pole AutoReclosure (SPAR) offers many advantages over conventional techniques. In the case of transient faults, the secondary arc extinction time can be accurately determined and in the case of a permanent fault, breaker reclosure can be avoided. This paper describes, in some detail, the design and implementation of a SPAR technique using Artificial Neural Networks (ANNs). The design described includes special methods for extracting features from post-circuit break opening fault data, which is a prerequisite for setting up training data sets. The technique is then implemented in hardware based on a high performance T800 transputer system and some results obtained from laboratory tests of this equipment are presented.

  10. Precision Blasting Techniques For Avalanche Control

    Science.gov (United States)

    Powell, Kevin M.

    Experimental firings sponsored by the Center For Snow Science at Alta, Utah have demonstrated the potential of a unique prototype shaped charge device designed to stimulate snow pack and ice. These studies, conducted against stable snow pack, demonstrated a fourfold increase in crater volume yield and introduced a novel application of Shock Tube technology to facilitate position control, detonation and dud recovery of manually deployed charges. The extraordinary penetration capability of the shaped charge mechanism has been exploited in many non-military applications to meet a wide range of rapidpiercing and/or cutting requirements. The broader exploitation of the potential of the shaped charge mechanism has nevertheless remained confined to defence based applications. In the studies reported in this paper, the inimitable ability of the shaped charge mechanism to project shock energy, or a liner material, into a highly focussed energetic stream has been applied uniquely to the stimulation of snow pack. Recent research and development work, conducted within the UK, has resulted in the integration of shaped charge technology into a common Avalauncher and hand charge device. The potential of the common charge configuration and spooled Shock Tube fire and control system to improve the safety and cost effectiveness of explosives used in avalanche control operations was successfully demonstrated at Alta in March 2001. Future programmes of study will include focussed shock/blast mechanisms for suspended wire traverse techniques, application of the shaped charge mechanism to helibombing, and the desig n and development of non-fragmenting shaped charge ammunition formilitary artillery gun systems.

  11. Evaluation of a novel artificial pancreas: closed loop glycemic control system with continuous blood glucose monitoring.

    Science.gov (United States)

    Tsukamoto, Yuuki; Kinoshita, Yoshihiko; Kitagawa, Hiroyuki; Munekage, Masaya; Munekage, Eri; Takezaki, Yuka; Yatabe, Tomoaki; Yamashita, Koichi; Yamazaki, Rie; Okabayashi, Takehiro; Tarumi, Masatoshi; Kobayashi, Masaki; Mishina, Suguru; Hanazaki, Kazuhiro

    2013-04-01

    A closed-loop glycemic control system using an artificial pancreas has been applied with many clinical benefits in Japan since 1987. To update this system incorporating user-friendly features, we developed a novel artificial pancreas (STG-55). The purpose of this study was to evaluate STG-55 for device usability, performance of blood glucose measurement, glycemic control characteristics in vivo in animal experiments, and evaluate its clinical feasibility. There are several features for usability improvement based on the design concepts, such as compactness, display monitor, batteries, guidance function, and reduction of the preparation time. All animal study data were compared with a clinically available artificial pancreas system in Japan (control device: STG-22). We examined correlations of both blood glucose levels between two groups (STG-55 vs. control) using Clarke's error grid analysis, and also compared mean glucose infusion rate (GIR) during glucose clamp. The results showed strong correlation in blood glucose concentrations (Pearson's product-moment correlation coefficient: 0.97; n = 1636). Clarke's error grid analysis showed that 98.4% of the data fell in Zones A and B, which represent clinically accurate or benign errors, respectively. The difference in mean GIRs was less than 0.2 mg/kg/min, which was considered not significant. Clinical feasibility study demonstrated sufficient glycemic control maintaining target glucose range between 80 and 110 (mg/dL), and between 140 and 160 without any hypoglycemia. In conclusion, STG-55 was a clinically acceptable artificial pancreas with improved interface and usability. A closed-loop glycemic control system with STG-55 would be a useful tool for surgical and critical patients in intensive care units, as well as diabetic patients.

  12. Control of a Heavy-Lift Robotic Manipulator with Pneumatic Artificial Muscles

    Directory of Open Access Journals (Sweden)

    Ryan M. Robinson

    2014-04-01

    Full Text Available Lightweight, compliant actuators are particularly desirable in robotic systems intended for interaction with humans. Pneumatic artificial muscles (PAMs exhibit these characteristics and are capable of higher specific work than comparably-sized hydraulic actuators and electric motors. The objective of this work is to develop a control algorithm that can smoothly and accurately track the desired motions of a manipulator actuated by pneumatic artificial muscles. The manipulator is intended for lifting humans in nursing assistance or casualty extraction scenarios; hence, the control strategy must be capable of responding to large variations in payload over a large range of motion. The present work first investigates the feasibility of two output feedback controllers (proportional-integral-derivative and fuzzy logic, but due to the limitations of pure output feedback control, a model-based feedforward controller is developed and combined with output feedback to achieve improved closed-loop performance. The model upon which the controller is based incorporates the internal airflow dynamics, the physical parameters of the pneumatic muscles and the manipulator dynamics. Simulations were performed in order to validate the control algorithms, guide controller design and predict optimal gains. Using real-time interface software and hardware, the controllers were implemented and experimentally tested on the manipulator, demonstrating the improved capability.

  13. Approximate Matching as a Key Technique in Organization of Natural and Artificial Intelligence

    Science.gov (United States)

    Mack, Marilyn; Lapir, Gennadi M.; Berkovich, Simon

    2000-01-01

    The basic property of an intelligent system, natural or artificial, is "understanding". We consider the following formalization of the idea of "understanding" among information systems. When system I issues a request to system 2, it expects a certain kind of desirable reaction. If such a reaction occurs, system I assumes that its request was "understood". In application to simple, "push-button" systems the situation is trivial because in a small system the required relationship between input requests and desired outputs could be specified exactly. As systems grow, the situation becomes more complex and matching between requests and actions becomes approximate.

  14. Optimal Fuzzy PID Controller with Adjustable Factors and Its Application to Intelligent Artificial Legs

    Institute of Scientific and Technical Information of China (English)

    Tan Guanzheng(谭冠政); Xiao Hongfeng; Wang Yuechao

    2004-01-01

    A new kind of optimal fuzzy PID controller is proposed, which contains two parts. One is an on-line fuzzy inference mechanism and another is a conventional PID controller. In the fuzzy inference mechanism, three adjustable factors xp, xi, and xd are introduced. Their function is to further modify and optimize the result of the fuzzy inference to make the controller have the optimal control effect on a given object. The optimal values of these factors are determined based on the ITAE criterion and the flexible polyhedron search algorithm of Nelder and Mead. This PID controller has been used to control a D.C. motor of the intelligent artificial leg designed by the authors. The result of computer simulation indicates that the design of this controller is very effective and can be widely used to control different kinds of objects and processes.

  15. Control techniques for invasive alien plants

    Directory of Open Access Journals (Sweden)

    Michele de Sá Dechoum

    2013-03-01

    Full Text Available Invasive alien species are recognized as a major threat to the conservation of biodiversity. These species should be managed based on local and regional environmental conditions. Control techniques were tested for ten invasive species in Santa Catarina State: the trees Casuarina equisetifolia, Hovenia dulcis, Psidium guajava, Syzygium cumini, and Terminalia catappa, and shrubs and herbs Rubus fruticosus, Furcraea foetida, Hedychium coronarium, Impatiens walleriana, and Tradescantia zebrina. Treatments applied for trees were cut stump, frill and girdling or ring-barking followed by herbicide application, while the other species were treated with foliar spray, application of herbicide on the root system, cut stump and herbicide injection. The active ingredients tested were Triclopyr, Glyphosate, and the combination of Triclopyr + Fluroxipyr in concentrations from 2 to 6%, according to the species. The cut stump method was efficient for all of the woody species, while ring-barking and frilling followed by herbicide application and basal bark application resulted in different levels of efficiency for the species tested. The most efficient method for herbs and shrubs was foliar spray, and the least efficient methods were cut stump and herbicide injection.

  16. Control of a hybrid compensator in a power network by an artificial neural network

    Directory of Open Access Journals (Sweden)

    I. S. Shaw

    1998-07-01

    Full Text Available Increased interest in the elimination of distortion in electrical power networks has led to the development of various compensator topologies. The increasing cost of electrical energy necessitates the cost-effective operation of any of these topologies. This paper considers the development of an artificial neural network based controller, trained by means of the backpropagation method, that ensures the cost-effective operation of the hybrid compensator consisting of various converters and filters.

  17. Modeling the cost-effectiveness of insect rearing on artificial diets: A test with a tephritid fly used in the sterile insect technique

    Science.gov (United States)

    Birke, Andrea; Williams, Trevor; Aluja, Martín

    2017-01-01

    We modeled the cost-effectiveness of rearing Anastrepha ludens, a major fruit fly pest currently mass reared for sterilization and release in pest control programs implementing the sterile insect technique (SIT). An optimization model was generated by combining response surface models of artificial diet cost savings with models of A. ludens pupation, pupal weight, larval development time and adult emergence as a function of mixtures of yeast, a costly ingredient, with corn flour and corncob fractions in the diet. Our model revealed several yeast-reduced mixtures that could be used to prepare diets that were considerably cheaper than a standard diet used for mass rearing. Models predicted a similar production of insects (pupation and adult emergence), with statistically similar pupal weights and larval development times between yeast-reduced diets and the standard mass rearing diet formulation. Annual savings from using the modified diets could be up to 5.9% of the annual cost of yeast, corn flour and corncob fractions used in the standard diet, representing a potential saving of US $27.45 per ton of diet (US $47,496 in the case of the mean annual production of 1,730.29 tons of artificial diet in the Moscafrut mass rearing facility at Metapa, Chiapas, Mexico). Implementation of the yeast-reduced diet on an experimental scale at mass rearing facilities is still required to confirm the suitability of new mixtures of artificial diet for rearing A. ludens for use in SIT. This should include the examination of critical quality control parameters of flies such as adult flight ability, starvation resistance and male sexual competitiveness across various generations. The method used here could be useful for improving the cost-effectiveness of invertebrate or vertebrate mass rearing diets worldwide. PMID:28257496

  18. Augmented Nonlinear Controller for Maximum Power-Point Tracking with Artificial Neural Network in Grid-Connected Photovoltaic Systems

    Directory of Open Access Journals (Sweden)

    Suliang Ma

    2016-11-01

    Full Text Available Photovoltaic (PV systems have non-linear characteristics that generate maximum power at one particular operating point. Environmental factors such as irradiance and temperature variations greatly affect the maximum power point (MPP. Diverse offline and online techniques have been introduced for tracking the MPP. Here, to track the MPP, an augmented-state feedback linearized (AFL non-linear controller combined with an artificial neural network (ANN is proposed. This approach linearizes the non-linear characteristics in PV systems and DC/DC converters, for tracking and optimizing the PV system operation. It also reduces the dependency of the designed controller on linearized models, to provide global stability. A complete model of the PV system is simulated. The existing maximum power-point tracking (MPPT and DC/DC boost-converter controller techniques are compared with the proposed ANN method. Two case studies, which simulate realistic circumstances, are presented to demonstrate the effectiveness and superiority of the proposed method. The AFL with ANN controller can provide good dynamic operation, faster convergence speed, and fewer operating-point oscillations around the MPP. It also tracks the global maxima under different conditions, especially irradiance-mutating situations, more effectively than the conventional methods. Detailed mathematical models and a control approach for a three-phase grid-connected intelligent hybrid system are proposed using MATLAB/Simulink.

  19. Quality by design approach: application of artificial intelligence techniques of tablets manufactured by direct compression.

    Science.gov (United States)

    Aksu, Buket; Paradkar, Anant; de Matas, Marcel; Ozer, Ozgen; Güneri, Tamer; York, Peter

    2012-12-01

    The publication of the International Conference of Harmonization (ICH) Q8, Q9, and Q10 guidelines paved the way for the standardization of quality after the Food and Drug Administration issued current Good Manufacturing Practices guidelines in 2003. "Quality by Design", mentioned in the ICH Q8 guideline, offers a better scientific understanding of critical process and product qualities using knowledge obtained during the life cycle of a product. In this scope, the "knowledge space" is a summary of all process knowledge obtained during product development, and the "design space" is the area in which a product can be manufactured within acceptable limits. To create the spaces, artificial neural networks (ANNs) can be used to emphasize the multidimensional interactions of input variables and to closely bind these variables to a design space. This helps guide the experimental design process to include interactions among the input variables, along with modeling and optimization of pharmaceutical formulations. The objective of this study was to develop an integrated multivariate approach to obtain a quality product based on an understanding of the cause-effect relationships between formulation ingredients and product properties with ANNs and genetic programming on the ramipril tablets prepared by the direct compression method. In this study, the data are generated through the systematic application of the design of experiments (DoE) principles and optimization studies using artificial neural networks and neurofuzzy logic programs.

  20. Artificial Intelligence Based Control Power Optimization on Tailless Aircraft. [ARMD Seedling Fund Phase I

    Science.gov (United States)

    Gern, Frank; Vicroy, Dan D.; Mulani, Sameer B.; Chhabra, Rupanshi; Kapania, Rakesh K.; Schetz, Joseph A.; Brown, Derrell; Princen, Norman H.

    2014-01-01

    Traditional methods of control allocation optimization have shown difficulties in exploiting the full potential of controlling large arrays of control devices on innovative air vehicles. Artificial neutral networks are inspired by biological nervous systems and neurocomputing has successfully been applied to a variety of complex optimization problems. This project investigates the potential of applying neurocomputing to the control allocation optimization problem of Hybrid Wing Body (HWB) aircraft concepts to minimize control power, hinge moments, and actuator forces, while keeping system weights within acceptable limits. The main objective of this project is to develop a proof-of-concept process suitable to demonstrate the potential of using neurocomputing for optimizing actuation power for aircraft featuring multiple independently actuated control surfaces. A Nastran aeroservoelastic finite element model is used to generate a learning database of hinge moment and actuation power characteristics for an array of flight conditions and control surface deflections. An artificial neural network incorporating a genetic algorithm then uses this training data to perform control allocation optimization for the investigated aircraft configuration. The phase I project showed that optimization results for the sum of required hinge moments are improved by more than 12% over the best Nastran solution by using the neural network optimization process.

  1. A novel numerical technique for the high-precision simulation of flow processes related to artificial recharge

    Science.gov (United States)

    Stevens, David; Orsini, Paolo; Power, Henry; Morvan, Herve; Bensabat, Jacob

    2010-05-01

    This paper presents a novel numerical technique for large-scale groundwater flow simulations, in the frame of artificial recharge planning. The implementation is demonstrated using two test-sites from the EU funded GABARDINE project (FP6): The Sindos test site, near Thessaloniki, Greece, examines the infiltration of water towards the water table, through several unsaturated soil layers. The test site at Campina de Faro, Portugal, investigates phreatic surface movement around a large-diameter well. For both test cases a numerical simulation is constructed, and the local subsurface flow regime is investigated. Numerical methods for solving PDEs using interpolation with radial basis functions (RBFs) will typically provide high accuracy solutions, achieve excellent convergence rates, and offer great flexibility with regards to the enforcement of arbitrary boundary conditions. However, RBF methods have traditionally been limited to the solution of small academic problems, due to issues of computational cost and numerical conditioning. Recent developments in locally supported RBF methods have led to techniques which can be scaled to the largest problem sizes, while maintaining many of the flexibilities of traditional RBF methods. As a contribution to the GABARDINE project, two such numerical techniques have been developed; the meshless LHI method and the control-volume based CV-RBF method. These numerical techniques are capable of modelling flow and transport in heterogeneous porous media, and are of order-N computational complexity, allowing problems to be solved on large and irregular datasets. For both numerical techniques, the RBF Hermitian collocation method is utilised to perform interpolation at the local level, allowing the simultaneous imposition of pressure and mass-flux matching conditions at soil-layer interfaces. The non-overlapping stencil configuration then allows the accurate capture of non-smooth solution profiles across layer interfaces, to a high

  2. On-Line Tracking Controller for Brushless DC Motor Drives Using Artificial Neural Networks

    Science.gov (United States)

    Rubaai, Ahmed

    1996-01-01

    A real-time control architecture is developed for time-varying nonlinear brushless dc motors operating in a high performance drives environment. The developed control architecture possesses the capabilities of simultaneous on-line identification and control. The dynamics of the motor are modeled on-line and controlled using an artificial neural network, as the system runs. The control architecture combines the experience and dependability of adaptive tracking systems with potential and promise of the neural computing technology. The sensitivity of real-time controller to parametric changes that occur during training is investigated. Such changes are usually manifested by rapid changes in the load of the brushless motor drives. This sudden change in the external load is simulated for the sigmoidal and sinusoidal reference tracks. The ability of the neuro-controller to maintain reasonable tracking accuracy in the presence of external noise is also verified for a number of desired reference trajectories.

  3. Remote detection of artificially triggered avalanches below a fixed avalanche control installation

    Science.gov (United States)

    van Herwijnen, Alec; Simioni, Stephan; Schweizer, Juerg

    2014-05-01

    Avalanche control by explosives is widely used as a temporary preventive measure to reduce avalanche hazard. The goal is to artificially trigger smaller less destructive avalanches, by detonating charges either above or on the snow surface. Hand charges are most often used, whereby the explosives are deployed by manually hand tossing or lowering onto the snow slope. Given the inherent dangers and limitations of this type of avalanche control, fixed avalanche control installations are increasingly used. These consist of strategically placed remote controlled installations that generate an explosion above the snow pack in an avalanche starting zone. While fixed installations can be used at any time and minimize the risk to avalanche control personnel, visual confirmation is still required to verify if an avalanche released. In order to remotely detect artificially triggered avalanches, we therefore developed a low-cost seismic monitoring system. We deployed the monitoring system in a ski area above the town of Davos , in the eastern Swiss Alps, below a Gazex installation, a remote controlled installation that generates an air blast by detonating a fuel-air explosive above the snow pack. The monitoring system consists of three vertical component geophones inserted in the ground at approximately 14, 27 and 46 meters from the Gazex installation. Our results show that, despite the relatively low precision of the monitoring equipment, both the detonation and the resulting avalanches can clearly be identified in the seismic data. Specifically, detonations are characterized by short, high amplitude broadband signals, while avalanches generate much longer, low frequency signals. Furthermore, information on the size of the artificially triggered avalanches is also obtained as it directly relates to the duration of the generated seismic signal. The overall goal is to assess the effectiveness of the fixed avalanche control installation with regards to yield (i.e. number of

  4. To Improvement in Image Compression ratio using Artificial Neural Network Technique

    Directory of Open Access Journals (Sweden)

    Shabbir Ahmad

    2015-10-01

    Full Text Available Compression of data in any form is a large and active field as well as a big business. This paper presents a neural network based technique that may be applied to data compression. This paper breaks down large images into smaller windows and eliminates redundant information. Finally, the technique uses a neural network trained by direct solution methods. Conventional techniques such as Huffman coding and the Shannon Fano method, LZ Method, Run Length Method, LZ-77 are discussed as well as more recent methods for the compression of data presents a neural network based technique that may be applied to data compression. The proposed technique and images. Intelligent methods for data compression are reviewed including the use of Back propagation and Kohonen neural networks. The proposed technique has been implemented in C on the SP2 and tested on digital mammograms and other images. The results obtained are presented in this paper.

  5. Intelligent techniques for system identification and controller tuning in pH process

    Directory of Open Access Journals (Sweden)

    K. Valarmathi

    2009-03-01

    Full Text Available This paper presents an application of Artificial Neural Network (ANN and Genetic Algorithm (GA for system identification for controller tuning in a pH process. In this paper, the ANN based approach is applied to estimate the system parameters. Once the variations in parameters are identified frequently, GA optimally tunes the controller. The simulation results show that the proposed intelligent technique is effective in identifying the parameters and has resulted in a minimum value of the Integral Square Error, peak overshoot and minimum settling time as compared to conventional methods. The experimental results show that their performance is superior and it matches favorably with the simulation results.

  6. Position control of fishing line artificial muscles (coiled polymer actuators) from nylon thread

    Science.gov (United States)

    Arakawa, Takeshi; Takagi, Kentaro; Tahara, Kenji; Asaka, Kinji

    2016-04-01

    Recently, fishing line artificial muscle has been developed and is paid much attention due to the properties such as large contraction, light weight and extremely low cost. Typical fishing line artificial muscle is made from Nylon thread and made by just twisting the polymer. In this paper, because of the structure of the actuator, such actuators may be named as coiled polymer actuators (CPAs). In this paper, a CPA is fabricated from commercial Nylon fishing line and Ni-Cr alloy (Nichrome) wire is wound around it. The CPA contracts by the Joule heat generated by applied voltage to the Nichrome wire. For designing the control system, a simple model is proposed. According to the physical principle of the actuator, two first-order transfer functions are introduced to represent the actuator model. One is a system from the input power to the temperature and the other is a system from the temperature to the deformation. From the system identification result, it is shown that the dominant dynamics is the system from the input power to the temperature. Using the developed model, position control of the voltage-driven CPA is discussed. Firstly, the static nonlinearity from the voltage to the power is eliminated. Then, a 2-DOF PID controller which includes an inversion-based feed forward controller and a PID controller are designed. In order to demonstrate the proposed controller, experimental verification is shown.

  7. Artificial Neural Network Based Controller for Speed Control of An Induction Motor (IM using Indirect Vector Control Method

    Directory of Open Access Journals (Sweden)

    Ashutosh Mishra

    2012-10-01

    Full Text Available

    In this paper, an implementation of intelligent controller for speed control of an induction motor (IM using indirect vector control method has been developed and analyzed in detail. The project is complete mathematical model of field orientation control (FOC induction motor is described and simulated in MATLAB for studies a 50 HP(37KW, cage type induction motor has been considered .The comparative  performance of PI, Fuzzy and Neural network control techniques have been  presented and analyzed in this work.  The present approach avoids the use of flux and speed sensor which increase the installation cost and mechanical robustness .The neural network based controller is found to be a very useful technique to obtain a high performance speed control. The scheme consist of neural network controller, reference modal, an algorithm for changing the neural network weight in order that  speed of the derive can track performance speed.  The indirect vector controlled induction motor drive involve decoupling of the stator current in to torque and flux producing components.

  8. Integration of daylight, artificial light and electronic light controls into office buildings

    Energy Technology Data Exchange (ETDEWEB)

    Ehling, K.; Knoop, T.; Aydinli, S.; Kaase, H. [Technical Univ. of Berlin, Inst. of Electronics and Lighting Technology (Germany)

    1996-12-31

    From a technical point of view daylight can be used in two different ways. On the one hand the available daylight can be distributed in an optimised way in order to illuminate deep spaces and to prevent from glare and on the other hand the artificial light can be controlled with respect to the daylight penetrating the room in order to save electrical energy. If these systems are adjusted according to the available daylight both strategies require sensors and logic elements which are supplied by electronic light controls on the basis of building management systems. (orig.)

  9. Improvement of controlled pollination techniques of poplar

    Institute of Scientific and Technical Information of China (English)

    ZHOU Zhong-cheng; LIU Zong-you; HOU Kai-ju; SUN Xian-meng; ZHANG Ji-he; SHEN Bao-xian

    2008-01-01

    Over a number of years, in order to find substitutes for two traditional poplar pollination techniques: outdoor bridging trees and indoor cutting with water culture, research into two new pollination methods of uprooted outdoor seed trees and outdoor cutting branches was carried out. The advantages of two new and improved techniques were of efficiency, economy, safety and ease of operation. The methods can be applied in hybridization and breeding of poplar and other easy-to-root trees.

  10. Two applications of airtightness control techniques on big assemblies

    CERN Document Server

    Devallan, C; Marcellin, J

    1973-01-01

    Deals with two airtightness control techniques respectively applied on intersecting storage rings (ISR) at CERN in Geneva and on a liquid methane storage tank. These two big assemblies called for two different control techniques which use helium and ammonia respectively as tracer gas. Existing practical leakage detection techniques to meet industrial needs are discussed at the end of the article. (2 refs).

  11. The relationship between strategic control and conscious structural knowledge in artificial grammar learning.

    Science.gov (United States)

    Norman, Elisabeth; Scott, Ryan B; Price, Mark C; Dienes, Zoltan

    2016-05-01

    We address Jacoby's (1991) proposal that strategic control over knowledge requires conscious awareness of that knowledge. In a two-grammar artificial grammar learning experiment all participants were trained on two grammars, consisting of a regularity in letter sequences, while two other dimensions (colours and fonts) varied randomly. Strategic control was measured as the ability to selectively apply the grammars during classification. For each classification, participants also made a combined judgement of (a) decision strategy and (b) relevant stimulus dimension. Strategic control was found for all types of decision strategy, including trials where participants claimed to lack conscious structural knowledge. However, strong evidence of strategic control only occurred when participants knew or guessed that the letter dimension was relevant, suggesting that strategic control might be associated with - or even causally requires - global awareness of the nature of the rules even though it does not require detailed knowledge of their content.

  12. Artificial Intelligence Techniques to Optimize the EDC/NHS-Mediated Immobilization of Cellulase on Eudragit L-100

    Directory of Open Access Journals (Sweden)

    Min-Chao He

    2012-06-01

    Full Text Available Two artificial intelligence techniques, namely artificial neural network (ANN and genetic algorithm (GA were combined to be used as a tool for optimizing the covalent immobilization of cellulase on a smart polymer, Eudragit L-100. 1-Ethyl-3-(3-dimethyllaminopropyl carbodiimide (EDC concentration, N-hydroxysuccinimide (NHS concentration and coupling time were taken as independent variables, and immobilization efficiency was taken as the response. The data of the central composite design were used to train ANN by back-propagation algorithm, and the result showed that the trained ANN fitted the data accurately (correlation coefficient R2 = 0.99. Then a maximum immobilization efficiency of 88.76% was searched by genetic algorithm at a EDC concentration of 0.44%, NHS concentration of 0.37% and a coupling time of 2.22 h, where the experimental value was 87.97 ± 6.45%. The application of ANN based optimization by GA is quite successful.

  13. Comparison of artificial intelligence techniques for prediction of soil temperatures in Turkey

    Science.gov (United States)

    Citakoglu, Hatice

    2016-08-01

    Soil temperature is a meteorological data directly affecting the formation and development of plants of all kinds. Soil temperatures are usually estimated with various models including the artificial neural networks (ANNs), adaptive neuro-fuzzy inference system (ANFIS), and multiple linear regression (MLR) models. Soil temperatures along with other climate data are recorded by the Turkish State Meteorological Service (MGM) at specific locations all over Turkey. Soil temperatures are commonly measured at 5-, 10-, 20-, 50-, and 100-cm depths below the soil surface. In this study, the soil temperature data in monthly units measured at 261 stations in Turkey having records of at least 20 years were used to develop relevant models. Different input combinations were tested in the ANN and ANFIS models to estimate soil temperatures, and the best combination of significant explanatory variables turns out to be monthly minimum and maximum air temperatures, calendar month number, depth of soil, and monthly precipitation. Next, three standard error terms (mean absolute error (MAE, °C), root mean squared error (RMSE, °C), and determination coefficient (R 2 )) were employed to check the reliability of the test data results obtained through the ANN, ANFIS, and MLR models. ANFIS (RMSE 1.99; MAE 1.09; R 2 0.98) is found to outperform both ANN and MLR (RMSE 5.80, 8.89; MAE 1.89, 2.36; R 2 0.93, 0.91) in estimating soil temperature in Turkey.

  14. Study on classification of soy sauce by electronic tongue technique combined with artificial neural network.

    Science.gov (United States)

    Ou-Yang, Qin; Zhao, Jie-Wen; Chen, Quan-Sheng; Lin, Hao; Huang, Xing-Yi

    2011-01-01

    Electronic tongue as an analytical tool coupled with pattern recognition was attempted to classify 4 different brands and 2 categories (produced by different processes) of Chinese soy sauce. An electronic tongue system was used for data acquisition of the samples. Some effective variables were extracted from electronic tongue data by principal component analysis (PCA). Backpropagation artificial neural network (BP-ANN) was applied to build identification models. PCA score plots show an obvious cluster trend of different brands and different categories of soy sauce in the 2-dimensional space. The optimal BP-ANN model for different brands was achieved when principal components (PCs) were 2, and the identification rate of the discrimination model was 100% in both the calibration set and the prediction set, and the optimal BP-ANN model for different categories had the same result. This work demonstrates that electronic tongue technology combined with a suitable pattern recognition method can be successfully used in the classification of different brands and categories of soy sauce.

  15. An artificial neural network technique for downscaling GCM outputs to RCM spatial scale

    Directory of Open Access Journals (Sweden)

    R. Chadwick

    2011-12-01

    Full Text Available An Artificial Neural Network (ANN approach is used to downscale ECHAM5 GCM temperature (T and rainfall (R fields to RegCM3 regional model scale over Europe. The main inputs to the neural network were the ECHAM5 fields and topography, and RegCM3 topography. An ANN trained for the period 1960–1980 was able to recreate the RegCM3 1981–2000 mean T and R fields with reasonable accuracy. The ANN showed an improvement over a simple lapse-rate correction method for T, although the ANN R field did not capture all the fine-scale detail of the RCM field. An ANN trained over a smaller area of Southern Europe was able to capture this detail with more precision. The ANN was unable to accurately recreate the RCM climate change (CC signal between 1981–2000 and 2081–2100, and it is suggested that this is because the relationship between the GCM fields, RCM fields and topography is not constant with time and changing climate. An ANN trained with three ten-year "time-slices" was able to better reproduce the RCM CC signal, particularly for the full European domain. This approach shows encouraging results but will need further refinement before becoming a viable supplement to dynamical regional climate modelling of temperature and rainfall.

  16. Tactile on-chip pre-processing with techniques from artificial retinas

    Science.gov (United States)

    Maldonado-Lopez, R.; Vidal-Verdu, F.; Linan, G.; Roca, E.; Rodriguez-Vazquez, A.

    2005-06-01

    The interest in tactile sensors is increasing as their use in complex unstructured environments is demanded, like in telepresence, minimal invasive surgery, robotics etc. The matrix of pressure data these devices provide can be managed with many image processing algorithms to extract the required information. However, as in the case of vision chips or artificial retinas, problems arise when the array size and the computation complexity increase. Having a look to the skin, the information collected by every mechanoreceptor is not carried to the brain for its processing, but some complex pre-processing is performed to fit the limited throughput of the nervous system. This is specially important for high bandwidth demanding tasks. Experimental works report that neural response of skin mechanoreceptors encodes the change in local shape from an offset level rather than the absolute force or pressure distributions. This is also the behavior of the retina, which implements a spatio-temporal averaging. We propose the same strategy in tactile preprocessing, and we show preliminary results when it faces the detection of the slip, which involves fast real-time processing.

  17. An artificial vision-based control system for automatic heliostat positioning offset correction in a central receiver solar power plant

    Energy Technology Data Exchange (ETDEWEB)

    Berenguel, M. [Universidad de Almeria, Dept. de Lenguajes y Computacion, La Canada Almeria (Spain); Rubio, F.R.; Lara, P.J.; Arahal, M.R.; Camacho, E.F.; Lopez, M. [Universidad de Sevilla, Dept. de Ingenieria de Sistemas y Automatica, Sevilla (Spain); Valverde, A. [Plataforma Solar de Almeria (PSA-CIEMAT), Tabernas (Almeria) (Spain)

    2004-07-01

    This paper presents the development of a simplified and automatic heliostat positioning offset correction control system using artificial vision techniques and common CCD devices. The heliostats of a solar power plant reflect solar radiation onto a receiver (in this case, a volumetric receiver) placed at the top of a tower in order to provide a desired energy flux distribution correlated with the coolant flow (in this case air mass flow) through the receiver, usually in an open loop control configuration. There exist error sources that increase the complexity of the control system, some of which are systematic ones, mainly due to tolerances, wrong mirror facets alignment (optical errors), errors due to the approximations made when calculating the solar position, etc., that produce errors (offsets) in the heliostat orientation (aiming point). The approximation adopted in this paper is based on the use of a B/W CCD camera to correct these deviations in an automatic way imitating the same procedure followed by the operators. The obtained images are used to estimate the distance between the sunbeam centroid projected by the heliostats and a target placed on the tower, this distance thus is used for low accuracy offset correction purposes. Basic threshold-based image processing techniques are used for automatic correction. (Author)

  18. Artificial Reefs

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — An artificial reef is a human-made underwater structure, typically built to promote marine life in areas with a generally featureless bottom, control erosion, block...

  19. Chaotic behavior control in fluidized bed systems using artificial neural network. Quarterly progress report, April 1, 1996--June 30, 1996

    Energy Technology Data Exchange (ETDEWEB)

    Bodruzzaman, M.; Essawy, M.A.

    1996-07-30

    We have developed techniques to control the chaotic behavior in the Fluidized Bed (FBC) Systems using Artificial Neural Networks (ANNs). For those techniques to cross from theory to implementation, the computer programs we are developing have to be interfaced with the outside world, as a necessary step towards the actual interface with an FBC system or its experimental mock up. For this reason we are working on a Data Acquisition Board setup that will enable communication between our programs and external systems. Communication is planned to be enabled in both ways to deliver feedback signals from a system to the control programs in one way, and the control signals from the control programs to the controlled system in the other way. On the other hand, since most of our programs are PC based, they have to follow the revolutionary progress in the PC technology. Our programs were developed in the DOS environment using an early version of Microsoft C compiler. For those programs to meet the current needs of most PC users, we are working on converting those programs to the Windows environment, using a very advanced and up to date C++ compiler. This compiler is known as the Microsoft Visual C++ Version 4.0. This compiler enables the implementation of very professional and sophisticated Windows 95, 32 bit applications. It also allows a simple utilization of the Object Oriented Programming (OOP) techniques, and lots of powerful graphical and communication tools known as the Microsoft Foundation Classes (MFC). This compiler also allows creating Dynamic Link Libraries (DLLS) that can be liked together or with other Windows programs. These two main aspects, the computer-system interface and the DOS-Windows migration will give our programs a leap frog towards their real implementation.

  20. Predictive ion source control using artificial neural network for RFT-30 cyclotron

    Energy Technology Data Exchange (ETDEWEB)

    Kong, Young Bae, E-mail: ybkong@kaeri.re.kr; Hur, Min Goo; Lee, Eun Je; Park, Jeong Hoon; Park, Yong Dae; Yang, Seung Dae

    2016-01-11

    An RFT-30 cyclotron is a 30 MeV proton accelerator for radioisotope production and fundamental research. The ion source of the RFT-30 cyclotron creates plasma from hydrogen gas and transports an ion beam into the center region of the cyclotron. Ion source control is used to search source parameters for best quality of the ion beam. Ion source control in a real system is a difficult and time consuming task, and the operator should search the source parameters by manipulating the cyclotron directly. In this paper, we propose an artificial neural network based predictive control approach for the RFT-30 ion source. The proposed approach constructs the ion source model by using an artificial neural network and finds the optimized parameters with the simulated annealing algorithm. To analyze the performance of the proposed approach, we evaluated the simulations with the experimental data of the ion source. The performance results show that the proposed approach can provide an efficient way to analyze and control the ion source of the RFT-30 cyclotron.

  1. An Approximate Solution Technique Depending on an Artificial Parameter:A Special Example10

    Institute of Scientific and Technical Information of China (English)

    JihuanHE

    1998-01-01

    In this paper,a new perturbation method is proposed.In contrast to the traditional perturbation methods,this technique does not require a small parameters in the equation.In this method,according to the homotopy technique,a homotopy with an imbedding parameter is constructed,and the imbedding parameter is considered as a “small parameter”,so the method is called homotopy perturbation method,which can take the full advantage of the traditional perturbation methods and the homotopy technique.To illustrate its effectiveness and its convenience,a few typical nonlinear equations are used.The results reveal their first-order appoximations obtained by the proposed method are valid uniformly even for very large parameters.and are more accurate than the perturbation solutions.

  2. Determination of Complex-Valued Parametric Model Coefficients Using Artificial Neural Network Technique

    Directory of Open Access Journals (Sweden)

    A. M. Aibinu

    2010-01-01

    Full Text Available A new approach for determining the coefficients of a complex-valued autoregressive (CAR and complex-valued autoregressive moving average (CARMA model coefficients using complex-valued neural network (CVNN technique is discussed in this paper. The CAR and complex-valued moving average (CMA coefficients which constitute a CARMA model are computed simultaneously from the adaptive weights and coefficients of the linear activation functions in a two-layered CVNN. The performance of the proposed technique has been evaluated using simulated complex-valued data (CVD with three different types of activation functions. The results show that the proposed method can accurately determine the model coefficients provided that the network is properly trained. Furthermore, application of the developed CVNN-based technique for MRI K-space reconstruction results in images with improve resolution.

  3. Development of a microcontroller-based automatic control system for the electrohydraulic total artificial heart.

    Science.gov (United States)

    Kim, H C; Khanwilkar, P S; Bearnson, G B; Olsen, D B

    1997-01-01

    An automatic physiological control system for the actively filled, alternately pumped ventricles of the volumetrically coupled, electrohydraulic total artificial heart (EHTAH) was developed for long-term use. The automatic control system must ensure that the device: 1) maintains a physiological response of cardiac output, 2) compensates for an nonphysiological condition, and 3) is stable, reliable, and operates at a high power efficiency. The developed automatic control system met these requirements both in vitro, in week-long continuous mock circulation tests, and in vivo, in acute open-chested animals (calves). Satisfactory results were also obtained in a series of chronic animal experiments, including 21 days of continuous operation of the fully automatic control mode, and 138 days of operation in a manual mode, in a 159-day calf implant.

  4. Reducing risk of closed loop control of blood glucose in artificial pancreas using fractional calculus.

    Science.gov (United States)

    Ghorbani, Mahboobeh; Bogdan, Paul

    2014-01-01

    Healthcare costs in the US are among the highest in the world. Chronic diseases such as diabetes significantly contribute to these extensive costs. Despite technological advances to improve sensing and actuation devices, we still lack a coherent theory that facilitates the design and optimization of efficient and robust medical cyber-physical systems for managing chronic diseases. In this paper, we propose a mathematical model for capturing the complex dynamics of blood glucose time series (e.g., time dependent and fractal behavior) observed in real world measurements via fractional calculus concepts. Building upon our time dependent fractal model, we propose a novel model predictive controller for an artificial pancreas that regulates insulin injection. We verify the accuracy of our controller by comparing it to conventional non-fractal models using real world measurements and show how the nonlinear optimal controller based on fractal calculus concepts is superior to non-fractal controllers in terms of average risk index and prediction accuracy.

  5. From bioseparation to artificial micro-organs: microfluidic chip based particle manipulation techniques

    Science.gov (United States)

    Stelzle, Martin

    2010-02-01

    Microfluidic device technology provides unique physical phenomena which are not available in the macroscopic world. These may be exploited towards a diverse array of applications in biotechnology and biomedicine ranging from bioseparation of particulate samples to the assembly of cells into structures that resemble the smallest functional unit of an organ. In this paper a general overview of chip-based particle manipulation and separation is given. In the state of the art electric, magnetic, optical and gravitational field effects are utilized. Also, mechanical obstacles often in combination with force fields and laminar flow are employed to achieve separation of particles or molecules. In addition, three applications based on dielectrophoretic forces for particle manipulation in microfluidic systems are discussed in more detail. Firstly, a virus assay is demonstrated. There, antibody-loaded microbeads are used to bind virus particles from a sample and subsequently are accumulated to form a pico-liter sized aggregate located at a predefined position in the chip thus enabling highly sensitive fluorescence detection. Secondly, subcellular fractionation of mitochondria from cell homogenate yields pure samples as was demonstrated by Western Blot and 2D PAGE analysis. Robust long-term operation with complex cell homogenate samples while avoiding electrode fouling is achieved by a set of dedicated technical means. Finally, a chip intended for the dielectrophoretic assembly of hepatocytes and endothelial cells into a structure resembling a liver sinusoid is presented. Such "artificial micro organs" are envisioned as substance screening test systems providing significantly higher predictability with respect to the in vivo response towards a substance under test.

  6. Automatic control systems of daylighting and artificial lighting; Saiko shomei setsubi no seigyo system

    Energy Technology Data Exchange (ETDEWEB)

    Saito, M. [Obayashi Corp., Tokyo (Japan)

    1997-06-05

    Means for controlling illumination include a blind for adjusting the light coming directly from the sun, system for maintaining environmental comfort by controlling light-modulating glass and the like, labor-saving system incorporating a control center governing multiple buildings in the vicinity, and system intended for improved energy efficiency. Energy saving efforts include an occupancy sensor control for the automatic turn-on/off of lighting by detecting the presence or absence of people in a chamber, optimum lighting control using sensors for adjusting illumination to the designed level, time-scheduled control for the turning-on/off of lighting according to the time of the day, daylight utilizing control for adjusting artificial lighting according to the amount of incident daylight, guidance light control system for turning on guidance lights upon sensing a decrease in incident daylight. Other than these, there are controls of lighting for performance and demonstration. Examples of practical application include the system adopted by Museum of Contemporary Art, Tokyo, for keeping incident light homogeneous, and the optimum illumination control and daylight utilizing control of Research & Development Center, The Tokyo Electric Power Co., Ltd. 8 refs., 10 figs.

  7. Artificial intelligence techniques applied to the development of a decision–support system for diagnosing celiac disease

    Science.gov (United States)

    Tenório, Josceli Maria; Hummel, Anderson Diniz; Cohrs, Frederico Molina; Sdepanian, Vera Lucia; Pisa, Ivan Torres; de Fátima Marin, Heimar

    2013-01-01

    Background Celiac disease (CD) is a difficult-to-diagnose condition because of its multiple clinical presentations and symptoms shared with other diseases. Gold-standard diagnostic confirmation of suspected CD is achieved by biopsying the small intestine. Objective To develop a clinical decision–support system (CDSS) integrated with an automated classifier to recognize CD cases, by selecting from experimental models developed using intelligence artificial techniques. Methods A web-based system was designed for constructing a retrospective database that included 178 clinical cases for training. Tests were run on 270 automated classifiers available in Weka 3.6.1 using five artificial intelligence techniques, namely decision trees, Bayesian inference, k-nearest neighbor algorithm, support vector machines and artificial neural networks. The parameters evaluated were accuracy, sensitivity, specificity and area under the ROC curve (AUC). AUC was used as a criterion for selecting the CDSS algorithm. A testing database was constructed including 38 clinical CD cases for CDSS evaluation. The diagnoses suggested by CDSS were compared with those made by physicians during patient consultations. Results The most accurate method during the training phase was the averaged one-dependence estimator (AODE) algorithm (a Bayesian classifier), which showed accuracy 80.0%, sensitivity 0.78, specificity 0.80 and AUC 0.84. This classifier was integrated into the web-based decision–support system. The gold-standard validation of CDSS achieved accuracy of 84.2% and k = 0.68 (p < 0.0001) with good agreement. The same accuracy was achieved in the comparison between the physician’s diagnostic impression and the gold standard k = 0. 64 (p < 0.0001). There was moderate agreement between the physician’s diagnostic impression and CDSS k = 0.46 (p = 0.0008). Conclusions The study results suggest that CDSS could be used to help in diagnosing CD, since the algorithm tested achieved excellent

  8. DETECTION OF MENDELIAN AND GENOTYPE FREQUENCY OF GROWTH HORMONE GENE IN ONGOLE CROSSBRED CATTLE MATED BY THE ARTIFICIAL INSEMINATION TECHNIQUE

    Directory of Open Access Journals (Sweden)

    U. Paputungan

    2012-06-01

    Full Text Available The objectives of this study were to detect the Mendelian mode inheritance of growth hormone (GH and to establish genotype frequency of GH gene in Ongole-crossbred cattle mated by the artificial insemination (AI technique. Total of 76 blood samples were collected from Ongole-crossbred cows and bulls (G0, and their progenies (G1 at the Tumaratas AI service center in North Sulawesi province, Indonesia. All blood samples were screened for the presence of GH locus using a PCR-RFLP method involving restricted enzyme Msp1 on 1.2 % of agarose gel. Data were analyzed using statistical program function in Excel XP. The results showed that GH locus using alleles of Msp1+ and Msp1- enzyme restriction in Ongole-crossbred cows and bulls was inherited to their Ongole-crossbred progenies following the Mendelian mode inheritance. This Mendelian inheritance generated by AI technique was not under genetic equilibrium for the Msp1 genotype frequencies in groups of G0 and G1. The breeding program using genotypes of bulls and cows (G0 for generating the genotype of GH Msp1 enzyme restriction by AI technique should be maintained to increase these various allele dispersion rates for breeding under genetic equilibrium of the Ongole-crossbred cattle population.

  9. Control of Fusarium head blight of winter wheat by artificial and natural infection using new fungicides

    Directory of Open Access Journals (Sweden)

    Olga Treikale

    2012-12-01

    Full Text Available In Latvia, climatic factors are influential in spreading of Fusarium head blight of cereals caused by Fusarium species. The most significant factor affecting the incidence of the disease in winter wheat is hightened temperature at the time of wheat anthesis. Field trials for the control of the disease in winter wheat were done in 2003-2004 using new fungicides applied at various rates by natural infection and artificial inoculation. Three species of causative agents: Fusarium avenaceum var. herbarum, F. gibbosum, F. culmorum were collected from infected seeds of wheat and used for inoculation of experimental plots at the concentration 106 conidia ml-1 (1:1:1 at the stage of full anthesis. Effective control of the disease was obtained through application of new fungicides with different active ingredient: Prosaro 250 EC (tebuconazole 125 G, prothioconazole 125 G L-1, Input 460 EC (spiroxamine 300 G, prothioconazole 160 G L-1. In conditions of artificial infection by severe attack of Fusarium spp. the application of fungicides containing tebuconazole at T3 gave significant influence on yield of winter wheat through plumpness of grains increase. High efficacy of fungicides against leaf infection with Erysiphe graminis and Drechslera tritici-repentis was also in the trial achieved. Application of fungicide containing cyproconazole and trifloxystrobin at T1 in the trial 2004 gave good control of Septoria tritici, E. graminis and D. triticirepentis.

  10. Inverse simulation system for manual-controlled rendezvous and docking based on artificial neural network

    Science.gov (United States)

    Zhou, Wanmeng; Wang, Hua; Tang, Guojin; Guo, Shuai

    2016-09-01

    The time-consuming experimental method for handling qualities assessment cannot meet the increasing fast design requirements for the manned space flight. As a tool for the aircraft handling qualities research, the model-predictive-control structured inverse simulation (MPC-IS) has potential applications in the aerospace field to guide the astronauts' operations and evaluate the handling qualities more effectively. Therefore, this paper establishes MPC-IS for the manual-controlled rendezvous and docking (RVD) and proposes a novel artificial neural network inverse simulation system (ANN-IS) to further decrease the computational cost. The novel system was obtained by replacing the inverse model of MPC-IS with the artificial neural network. The optimal neural network was trained by the genetic Levenberg-Marquardt algorithm, and finally determined by the Levenberg-Marquardt algorithm. In order to validate MPC-IS and ANN-IS, the manual-controlled RVD experiments on the simulator were carried out. The comparisons between simulation results and experimental data demonstrated the validity of two systems and the high computational efficiency of ANN-IS.

  11. Microsoft Kinect-Based Artificial Perception System for Control of Functional Electrical Stimulation Assisted Grasping

    Directory of Open Access Journals (Sweden)

    Matija Štrbac

    2014-01-01

    Full Text Available We present a computer vision algorithm that incorporates a heuristic model which mimics a biological control system for the estimation of control signals used in functional electrical stimulation (FES assisted grasping. The developed processing software acquires the data from Microsoft Kinect camera and implements real-time hand tracking and object analysis. This information can be used to identify temporal synchrony and spatial synergies modalities for FES control. Therefore, the algorithm acts as artificial perception which mimics human visual perception by identifying the position and shape of the object with respect to the position of the hand in real time during the planning phase of the grasp. This artificial perception used within the heuristically developed model allows selection of the appropriate grasp and prehension. The experiments demonstrate that correct grasp modality was selected in more than 90% of tested scenarios/objects. The system is portable, and the components are low in cost and robust; hence, it can be used for the FES in clinical or even home environment. The main application of the system is envisioned for functional electrical therapy, that is, intensive exercise assisted with FES.

  12. Microsoft kinect-based artificial perception system for control of functional electrical stimulation assisted grasping.

    Science.gov (United States)

    Strbac, Matija; Kočović, Slobodan; Marković, Marko; Popović, Dejan B

    2014-01-01

    We present a computer vision algorithm that incorporates a heuristic model which mimics a biological control system for the estimation of control signals used in functional electrical stimulation (FES) assisted grasping. The developed processing software acquires the data from Microsoft Kinect camera and implements real-time hand tracking and object analysis. This information can be used to identify temporal synchrony and spatial synergies modalities for FES control. Therefore, the algorithm acts as artificial perception which mimics human visual perception by identifying the position and shape of the object with respect to the position of the hand in real time during the planning phase of the grasp. This artificial perception used within the heuristically developed model allows selection of the appropriate grasp and prehension. The experiments demonstrate that correct grasp modality was selected in more than 90% of tested scenarios/objects. The system is portable, and the components are low in cost and robust; hence, it can be used for the FES in clinical or even home environment. The main application of the system is envisioned for functional electrical therapy, that is, intensive exercise assisted with FES.

  13. Mathematical Model and Artificial Intelligent Techniques Applied to a Milk Industry through DSM

    Science.gov (United States)

    Babu, P. Ravi; Divya, V. P. Sree

    2011-08-01

    The resources for electrical energy are depleting and hence the gap between the supply and the demand is continuously increasing. Under such circumstances, the option left is optimal utilization of available energy resources. The main objective of this chapter is to discuss about the Peak load management and overcome the problems associated with it in processing industries such as Milk industry with the help of DSM techniques. The chapter presents a generalized mathematical model for minimizing the total operating cost of the industry subject to the constraints. The work presented in this chapter also deals with the results of application of Neural Network, Fuzzy Logic and Demand Side Management (DSM) techniques applied to a medium scale milk industrial consumer in India to achieve the improvement in load factor, reduction in Maximum Demand (MD) and also the consumer gets saving in the energy bill.

  14. Photons and (artificial) atoms: an overview of optical spectroscopy techniques on quantum dots

    Science.gov (United States)

    Vamivakas, A. N.; Atatüre, M.

    2010-01-01

    In most branches within experimental physics technical prowess lies at the heart of many seminal works. From the observation of the photoelectric effect and the ultraviolet catastrophe that led to the development of quantum mechanics to the first transistor that shaped the modern age of electronics, significant physical insight has been achieved on the shoulders of technical advances and progress. Research on self-assembled quantum dots may be a drop in the sea of physics, but it still is no exception to this trend, and more physical insight continues to be revealed as the tools of the trade get increasingly more complex and advanced. This article is written primarily for senior undergraduate students and first year graduate students of experimental physics involving optically active quantum dots. More often than not, we have seen students shuffling through journal articles trying to relate the reported physics to the used experimental techniques. What we want to cover here is not in any way the history or the recent progress in quantum dot research - there are an ample number of topical books and review articles for that - but rather to highlight a selection of optics-based measurement techniques that have led to significant progress in our understanding of quantum dot physics as well as their applications in the last two decades. We hope a basic survey of the relevant optical spectroscopy techniques will help the newcomers in connecting the dots between measurements and physics.

  15. Simulation Techniques and Prosthetic Approach Towards Biologically Efficient Artificial Sense Organs- An Overview

    OpenAIRE

    Neogi, Biswarup; Ghosal, Soumya; Mukherjee, Soumyajit; Das, Achintya; Tibarewala, D. N.

    2011-01-01

    An overview of the applications of control theory to prosthetic sense organs including the senses of vision, taste and odor is being presented in this paper. Simulation aspect nowadays has been the centre of research in the field of prosthesis. There have been various successful applications of prosthetic organs, in case of natural biological organs dis-functioning patients. Simulation aspects and control modeling are indispensible for knowing system performance, and to generate an original a...

  16. Software tool for resolution of inverse problems using artificial intelligence techniques: an application in neutron spectrometry; Herramienta en software para resolucion de problemas inversos mediante tecnicas de inteligencia artificial: una aplicacion en espectrometria neutronica

    Energy Technology Data Exchange (ETDEWEB)

    Castaneda M, V. H.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Leon P, A. A.; Hernandez P, C. F.; Espinoza G, J. G.; Ortiz R, J. M.; Vega C, H. R. [Universidad Autonoma de Zacatecas, 98000 Zacatecas, Zac. (Mexico); Mendez, R. [CIEMAT, Departamento de Metrologia de Radiaciones Ionizantes, Laboratorio de Patrones Neutronicos, Av. Complutense 22, 28040 Madrid (Spain); Gallego, E. [Universidad Politecnica de Madrid, Departamento de Ingenieria Nuclear, C. Jose Gutierrez Abascal 2, 28006 Madrid (Spain); Sousa L, M. A. [Comision Nacional de Energia Nuclear, Centro de Investigacion de Tecnologia Nuclear, Av. Pte. Antonio Carlos 6627, Pampulha, 31270-901 Belo Horizonte, Minas Gerais (Brazil)

    2016-10-15

    The Taguchi methodology has proved to be highly efficient to solve inverse problems, in which the values of some parameters of the model must be obtained from the observed data. There are intrinsic mathematical characteristics that make a problem known as inverse. Inverse problems appear in many branches of science, engineering and mathematics. To solve this type of problem, researches have used different techniques. Recently, the use of techniques based on Artificial Intelligence technology is being explored by researches. This paper presents the use of a software tool based on artificial neural networks of generalized regression in the solution of inverse problems with application in high energy physics, specifically in the solution of the problem of neutron spectrometry. To solve this problem we use a software tool developed in the Mat Lab programming environment, which employs a friendly user interface, intuitive and easy to use for the user. This computational tool solves the inverse problem involved in the reconstruction of the neutron spectrum based on measurements made with a Bonner spheres spectrometric system. Introducing this information, the neural network is able to reconstruct the neutron spectrum with high performance and generalization capability. The tool allows that the end user does not require great training or technical knowledge in development and/or use of software, so it facilitates the use of the program for the resolution of inverse problems that are in several areas of knowledge. The techniques of Artificial Intelligence present singular veracity to solve inverse problems, given the characteristics of artificial neural networks and their network topology, therefore, the tool developed has been very useful, since the results generated by the Artificial Neural Network require few time in comparison to other techniques and are correct results comparing them with the actual data of the experiment. (Author)

  17. Intraoperative glycemic control procedures and the use of an artificial pancreas

    Institute of Scientific and Technical Information of China (English)

    Koichi Yamashita; Tomoaki Yatabe

    2009-01-01

    Strict intraoperative glycemic control can significantly decrease the incidence of postoperative infection;however, anesthesiologists must carefully control blood glucose levels as well as properly manage the respiratory and cardiovascular systems. However,standard blood glucose measurement systems and insulin dosing algorithms, which are necessary for achieving strict glycemic control, have not yet been developed. An artificial pancreas (STG-22TM;Nikkiso Co., Tokyo, Japan) is considered a highly accurate blood glucose monitoring system capable of closedloopcontrol of blood glucose. The device has, however,many problems to be addressed since it is a large and expensive system with little versatility, and it requires a large amount of blood to be collected. Therefore,the development of less invasive and inexpensive systems with future technological progress is greatly anticipated.

  18. An optimized control of ventilation in coal mines based on artificial neural network

    Institute of Scientific and Technical Information of China (English)

    付华; 邵良杉

    2002-01-01

    According to the nonlinear and time-dependent features of the ventilation systems for coal mines, a neural network method is applied to control the ventilator for coal mines in real time. The technical processes of coal mine ventilation system are introduced, and the principle of controlling a ventilation fan is also explained in detail. The artificial neutral network method is used to calculate the wind quantity needed by work spots in coal mine on the basis of the data collected by the system, including ventilation conditions, environmental temperatures, humidity, coal dust and the contents of all kinds of poisonous and harmful gases. Then the speed of ventilation fan is controlled according to the required wind which is determined by an overall integration of data. A neural network method is presented for overall optimized solution or the genetic algorithm of simulated annealing.

  19. Hydraulic Control Design and Modeling Techniques.

    Science.gov (United States)

    1989-02-01

    methodologies. This report may be difficult to read for the casual reader . It is written assuming the reader has some fundamental background in control...INTERVAL DTSMP=.O0012207 STEP=. 0012207 INDEX=INDEX+i DOUT( INDEX2)=L1 A- 4 END $*OF DISCRETE SAMP 2" DERIVATIVE tarot (INDEX2 .GE. 4098) END $*OF

  20. Advanced Control Techniques for WEC Wave Dragon

    DEFF Research Database (Denmark)

    Tedd, James; Kofoed, Jens Peter; Jasinski, M.;

    2007-01-01

    This paper presents the ongoing work on control of the Wave Dragon wave energy converter. Research is being conducted in and between several centers across Europe. This is building upon the knowledge gained in the prototype project, and will enable much better performance of the future deployment...

  1. Establishing structure-property correlations and classification of base oils using statistical techniques and artificial neural networks

    Energy Technology Data Exchange (ETDEWEB)

    Kapur, G.S.; Sastry, M.I.S.; Jaiswal, A.K.; Sarpal, A.S

    2004-03-17

    The present paper describes various classification techniques like cluster analysis, principal component (PC)/factor analysis to classify different types of base stocks. The API classification of base oils (Group I-III) has been compared to a more detailed NMR derived chemical compositional and molecular structural parameters based classification in order to point out the similarities of the base oils in the same group and the differences between the oils placed in different groups. The detailed compositional parameters have been generated using {sup 1}H and {sup 13}C nuclear magnetic resonance (NMR) spectroscopic methods. Further, oxidation stability, measured in terms of rotating bomb oxidation test (RBOT) life, of non-conventional base stocks and their blends with conventional base stocks, has been quantitatively correlated with their {sup 1}H NMR and elemental (sulphur and nitrogen) data with the help of multiple linear regression (MLR) and artificial neural networks (ANN) techniques. The MLR based model developed using NMR and elemental data showed a high correlation between the 'measured' and 'estimated' RBOT values for both training (R=0.859) and validation (R=0.880) data sets. The ANN based model, developed using fewer number of input variables (only {sup 1}H NMR data) also showed high correlation between the 'measured' and 'estimated' RBOT values for training (R=0.881), validation (R=0.860) and test (R=0.955) data sets.

  2. Recent advances in knowledge-based paradigms and applications enhanced applications using hybrid artificial intelligence techniques

    CERN Document Server

    Jain, Lakhmi

    2014-01-01

    This book presents carefully selected contributions devoted to the modern perspective of AI research and innovation. This collection covers several areas of applications and motivates new research directions. The theme across all chapters combines several domains of AI research , Computational Intelligence and Machine Intelligence including an introduction to  the recent research and models. Each of the subsequent chapters reveals leading edge research and innovative solution that employ AI techniques with an applied perspective. The problems include classification of spatial images, early smoke detection in outdoor space from video images, emergent segmentation from image analysis, intensity modification in images, multi-agent modeling and analysis of stress. They all are novel pieces of work and demonstrate how AI research contributes to solutions for difficult real world problems that benefit the research community, industry and society.

  3. Position and Speed Control of Brushless DC Motors Using Sensorless Techniques and Application Trends

    Science.gov (United States)

    Gamazo-Real, José Carlos; Vázquez-Sánchez, Ernesto; Gómez-Gil, Jaime

    2010-01-01

    This paper provides a technical review of position and speed sensorless methods for controlling Brushless Direct Current (BLDC) motor drives, including the background analysis using sensors, limitations and advances. The performance and reliability of BLDC motor drivers have been improved because the conventional control and sensing techniques have been improved through sensorless technology. Then, in this paper sensorless advances are reviewed and recent developments in this area are introduced with their inherent advantages and drawbacks, including the analysis of practical implementation issues and applications. The study includes a deep overview of state-of-the-art back-EMF sensing methods, which includes Terminal Voltage Sensing, Third Harmonic Voltage Integration, Terminal Current Sensing, Back-EMF Integration and PWM strategies. Also, the most relevant techniques based on estimation and models are briefly analysed, such as Sliding-mode Observer, Extended Kalman Filter, Model Reference Adaptive System, Adaptive observers (Full-order and Pseudoreduced-order) and Artificial Neural Networks. PMID:22163582

  4. Position and speed control of brushless DC motors using sensorless techniques and application trends.

    Science.gov (United States)

    Gamazo-Real, José Carlos; Vázquez-Sánchez, Ernesto; Gómez-Gil, Jaime

    2010-01-01

    This paper provides a technical review of position and speed sensorless methods for controlling Brushless Direct Current (BLDC) motor drives, including the background analysis using sensors, limitations and advances. The performance and reliability of BLDC motor drivers have been improved because the conventional control and sensing techniques have been improved through sensorless technology. Then, in this paper sensorless advances are reviewed and recent developments in this area are introduced with their inherent advantages and drawbacks, including the analysis of practical implementation issues and applications. The study includes a deep overview of state-of-the-art back-EMF sensing methods, which includes Terminal Voltage Sensing, Third Harmonic Voltage Integration, Terminal Current Sensing, Back-EMF Integration and PWM strategies. Also, the most relevant techniques based on estimation and models are briefly analysed, such as Sliding-mode Observer, Extended Kalman Filter, Model Reference Adaptive System, Adaptive observers (Full-order and Pseudoreduced-order) and Artificial Neural Networks.

  5. Position and Speed Control of Brushless DC Motors Using Sensorless Techniques and Application Trends

    Directory of Open Access Journals (Sweden)

    Jaime Gómez-Gil

    2010-07-01

    Full Text Available This paper provides a technical review of position and speed sensorless methods for controlling Brushless Direct Current (BLDC motor drives, including the background analysis using sensors, limitations and advances. The performance and reliability of BLDC motor drivers have been improved because the conventional control and sensing techniques have been improved through sensorless technology. Then, in this paper sensorless advances are reviewed and recent developments in this area are introduced with their inherent advantages and drawbacks, including the analysis of practical implementation issues and applications. The study includes a deep overview of state-of-the-art back-EMF sensing methods, which includes Terminal Voltage Sensing, Third Harmonic Voltage Integration, Terminal Current Sensing, Back-EMF Integration and PWM strategies. Also, the most relevant techniques based on estimation and models are briefly analysed, such as Sliding-mode Observer, Extended Kalman Filter, Model Reference Adaptive System, Adaptive observers (Full-order and Pseudoreduced-order and Artificial Neural Networks.

  6. Technique for Controlling Spread of Limnotic Oncomelania

    Institute of Scientific and Technical Information of China (English)

    Li Damei(李大美); WANG Xiangsan(王祥三); LAI Yonggen

    2003-01-01

    Schistosomiasis is a parasitic disease mostly found in areas along the Changjiang River of China. The disease is spread solely through an intermediary named oncomelania, so its spread of schistosomiasis can be controlled by properly designing water intakes which prevent oncomelania from entering fanning land or residential areas. This paper reports a successful design process and a new oncomelania-free intake device. The design of the new intake is based on a sound research program in which extensive experimental studies were carried out to gain knowledge of oncomelania eco-hydraulic behavior and detailed flow field information through CFD simulation.

  7. Bio-inspired online variable recruitment control of fluidic artificial muscles

    Science.gov (United States)

    Jenkins, Tyler E.; Chapman, Edward M.; Bryant, Matthew

    2016-12-01

    This paper details the creation of a hybrid variable recruitment control scheme for fluidic artificial muscle (FAM) actuators with an emphasis on maximizing system efficiency and switching control performance. Variable recruitment is the process of altering a system’s active number of actuators, allowing operation in distinct force regimes. Previously, FAM variable recruitment was only quantified with offline, manual valve switching; this study addresses the creation and characterization of novel, on-line FAM switching control algorithms. The bio-inspired algorithms are implemented in conjunction with a PID and model-based controller, and applied to a simulated plant model. Variable recruitment transition effects and chatter rejection are explored via a sensitivity analysis, allowing a system designer to weigh tradeoffs in actuator modeling, algorithm choice, and necessary hardware. Variable recruitment is further developed through simulation of a robotic arm tracking a variety of spline position inputs, requiring several levels of actuator recruitment. Switching controller performance is quantified and compared with baseline systems lacking variable recruitment. The work extends current variable recruitment knowledge by creating novel online variable recruitment control schemes, and exploring how online actuator recruitment affects system efficiency and control performance. Key topics associated with implementing a variable recruitment scheme, including the effects of modeling inaccuracies, hardware considerations, and switching transition concerns are also addressed.

  8. Cerebellar-inspired algorithm for adaptive control of nonlinear dielectric elastomer-based artificial muscle

    Science.gov (United States)

    Assaf, Tareq; Rossiter, Jonathan M.; Porrill, John

    2016-01-01

    Electroactive polymer actuators are important for soft robotics, but can be difficult to control because of compliance, creep and nonlinearities. Because biological control mechanisms have evolved to deal with such problems, we investigated whether a control scheme based on the cerebellum would be useful for controlling a nonlinear dielectric elastomer actuator, a class of artificial muscle. The cerebellum was represented by the adaptive filter model, and acted in parallel with a brainstem, an approximate inverse plant model. The recurrent connections between the two allowed for direct use of sensory error to adjust motor commands. Accurate tracking of a displacement command in the actuator's nonlinear range was achieved by either semi-linear basis functions in the cerebellar model or semi-linear functions in the brainstem corresponding to recruitment in biological muscle. In addition, allowing transfer of training between cerebellum and brainstem as has been observed in the vestibulo-ocular reflex prevented the steady increase in cerebellar output otherwise required to deal with creep. The extensibility and relative simplicity of the cerebellar-based adaptive-inverse control scheme suggests that it is a plausible candidate for controlling this type of actuator. Moreover, its performance highlights important features of biological control, particularly nonlinear basis functions, recruitment and transfer of training. PMID:27655667

  9. Embedded Control in Wearable Medical Devices: Application to the Artificial Pancreas

    Directory of Open Access Journals (Sweden)

    Stamatina Zavitsanou

    2016-09-01

    Full Text Available Significant increases in processing power, coupled with the miniaturization of processing units operating at low power levels, has motivated the embedding of modern control systems into medical devices. The design of such embedded decision-making strategies for medical applications is driven by multiple crucial factors, such as: (i guaranteed safety in the presence of exogenous disturbances and unexpected system failures; (ii constraints on computing resources; (iii portability and longevity in terms of size and power consumption; and (iv constraints on manufacturing and maintenance costs. Embedded control systems are especially compelling in the context of modern artificial pancreas systems (AP used in glucose regulation for patients with type 1 diabetes mellitus (T1DM. Herein, a review of potential embedded control strategies that can be leveraged in a fully-automated and portable AP is presented. Amongst competing controllers, emphasis is provided on model predictive control (MPC, since it has been established as a very promising control strategy for glucose regulation using the AP. Challenges involved in the design, implementation and validation of safety-critical embedded model predictive controllers for the AP application are discussed in detail. Additionally, the computational expenditure inherent to MPC strategies is investigated, and a comparative study of runtime performances and storage requirements among modern quadratic programming solvers is reported for a desktop environment and a prototype hardware platform.

  10. The application of artificial intelligent techniques to accelerator operations at McMaster University

    Science.gov (United States)

    Poehlman, W. F. S.; Garland, Wm. J.; Stark, J. W.

    1993-06-01

    In an era of downsizing and a limited pool of skilled accelerator personnel from which to draw replacements for an aging workforce, the impetus to integrate intelligent computer automation into the accelerator operator's repertoire is strong. However, successful deployment of an "Operator's Companion" is not trivial. Both graphical and human factors need to be recognized as critical areas that require extra care when formulating the Companion. They include interactive graphical user's interface that mimics, for the operator, familiar accelerator controls; knowledge of acquisition phases during development must acknowledge the expert's mental model of machine operation; and automated operations must be seen as improvements to the operator's environment rather than threats of ultimate replacement. Experiences with the PACES Accelerator Operator Companion developed at two sites over the past three years are related and graphical examples are given. The scale of the work involves multi-computer control of various start-up/shutdown and tuning procedures for Model FN and KN Van de Graaff accelerators. The response from licensing agencies has been encouraging.

  11. Active structural control with stable fuzzy PID techniques

    CERN Document Server

    Yu, Wen

    2016-01-01

    This book presents a detailed discussion of intelligent techniques to measure the displacement of buildings when they are subjected to vibration. It shows how these techniques are used to control active devices that can reduce vibration 60–80% more effectively than widely used passive anti-seismic systems. After introducing various structural control devices and building-modeling and active structural control methods, the authors propose offset cancellation and high-pass filtering techniques to solve some common problems of building-displacement measurement using accelerometers. The most popular control algorithms in industrial settings, PD/PID controllers, are then analyzed and then combined with fuzzy compensation. The stability of this combination is proven with standard weight-training algorithms. These conditions provide explicit methods for selecting PD/PID controllers. Finally, fuzzy-logic and sliding-mode control are applied to the control of wind-induced vibration. The methods described are support...

  12. A case of perioperative glucose control by using an artificial pancreas in a patient with glycogen storage disease.

    Science.gov (United States)

    Yatabe, Tomoaki; Nakamura, Ryu; Kitagawa, Hiroyuki; Munekage, Masaya; Hanazaki, Kazuhiro

    2016-03-01

    A 57-year-old woman was diagnosed with type I glycogen storage disease in her twenties. She had undergone hepatectomy under general anesthesia with epidural anesthesia. Fifty minutes after the induction of anesthesia, a 20-gauge venous catheter was inserted in the patient's right hand, and an artificial pancreas (STG-55, Nikkiso Co., Tokyo, Japan) was connected for continuous glucose monitoring and automatic glucose control. Insulin was infused when the blood glucose level reached 120 mg/dL or higher, and glucose was infused when the level fell to 100 mg/dL or lower. After the Pringle maneuver, the blood glucose level increased, and insulin was administered automatically via an artificial pancreas. Hypoglycemia did not occur during the operation. After total parenteral nutrition was started in the intensive care unit (ICU), the blood glucose level increased, and the artificial pancreas controlled the blood glucose level through automatic insulin administration. Thirty-four hours after admission to the ICU, the artificial pancreas was removed because the blood sampling failed. After the removal of the artificial pancreas, blood glucose level was measured every 2 h until extubation. During the ICU stay, hypoglycemia never occurred, with the average blood glucose level being 144 mg/dL. In conclusion, the use of an artificial pancreas for perioperative blood glucose management in a patient with glycogen storage disease had the beneficial effect of enabling the management of blood glucose levels without hypoglycemia.

  13. Fuzzy-GA PID controller with incomplete derivation and its application to intelligent bionic artificial leg

    Institute of Scientific and Technical Information of China (English)

    谭冠政; 李安平

    2003-01-01

    An optimal PID controller with incomplete derivation is proposed based on fuzzy inference and the geneticalgorithm, which is called the fuzzy-GA PID controller with incomplete derivation. It consists of the off-line part andthe on-line part. In the off-line part, by taking the overshoot, rise time, and settling time of system unit step re-sponse as the performance indexes and by using the genetic algorithm, a group of optimal PID parameters K*p , Ti* ,and Tj are obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-linepart, based on K; , Ti* , and T*d and according to the current system error e and its time derivative, a dedicatedprogram is written, which is used to optimize and adjust the PID parameters on line through a fuzzy inference mech-anism to ensure that the system response has optimal dynamic and steady-state performance. The controller has beenused to control the D. C. motor of the intelligent bionic artificial leg designed by the authors. The result of computersimulation shows that this kind of optimal PID controller has excellent control performance and robust performance.

  14. An efficient artificial bee colony algorithm with application to nonlinear predictive control

    Science.gov (United States)

    Ait Sahed, Oussama; Kara, Kamel; Benyoucef, Abousoufyane; Laid Hadjili, Mohamed

    2016-05-01

    In this paper a constrained nonlinear predictive control algorithm, that uses the artificial bee colony (ABC) algorithm to solve the optimization problem, is proposed. The main objective is to derive a simple and efficient control algorithm that can solve the nonlinear constrained optimization problem with minimal computational time. Indeed, a modified version, enhancing the exploring and the exploitation capabilities, of the ABC algorithm is proposed and used to design a nonlinear constrained predictive controller. This version allows addressing the premature and the slow convergence drawbacks of the standard ABC algorithm, using a modified search equation, a well-known organized distribution mechanism for the initial population and a new equation for the limit parameter. A convergence statistical analysis of the proposed algorithm, using some well-known benchmark functions is presented and compared with several other variants of the ABC algorithm. To demonstrate the efficiency of the proposed algorithm in solving engineering problems, the constrained nonlinear predictive control of the model of a Multi-Input Multi-Output industrial boiler is considered. The control performances of the proposed ABC algorithm-based controller are also compared to those obtained using some variants of the ABC algorithms.

  15. ADRC or adaptive controller--A simulation study on artificial blood pump.

    Science.gov (United States)

    Wu, Yi; Zheng, Qing

    2015-11-01

    Active disturbance rejection control (ADRC) has gained popularity because it requires little knowledge about the system to be controlled, has the inherent disturbance rejection ability, and is easy to tune and implement in practical systems. In this paper, the authors compared the performance of an ADRC and an adaptive controller for an artificial blood pump for end-stage congestive heart failure patients using only the feedback signal of pump differential pressure. The purpose of the control system was to provide sufficient perfusion when the patients' circulation system goes through different pathological and activity variations. Because the mean arterial pressure is equal to the total peripheral flow times the total peripheral resistance, this goal was converted to an expression of making the mean aortic pressure track a reference signal. The simulation results demonstrated that the performance of the ADRC is comparable to that of the adaptive controller with the saving of modeling and computational effort and fewer design parameters: total peripheral flow and mean aortic pressure with ADRC fall within the normal physiological ranges in activity variation (rest to exercise) and in pathological variation (left ventricular strength variation), similar to those values of adaptive controller.

  16. Recycling potential of air pollution control residue from sewage sludge thermal treatment as artificial lightweight aggregates.

    Science.gov (United States)

    Bialowiec, Andrzej; Janczukowicz, Wojciech; Gusiatin, Zygmunt M; Thornton, Arthur; Rodziewicz, Joanna; Zielinska, Magdalena

    2014-03-01

    Thermal treatment of sewage sludge produces fly ash, also known as the air pollution control residue (APCR), which may be recycled as a component of artificial lightweight aggregates (ALWA). Properties of APCR are typical: high content of Ca, Mg, P2O5, as well as potential to induce alkaline reactions. These properties indicate that ALWA prepared with a high content of APCR may remove heavy metals, phosphorus, and ammonium nitrogen from wastewater with high efficiency. The aim of this preliminary study was to determine the optimal composition of ALWA for potential use as a filter media in wastewater treatment systems. Five kinds of ALWA were produced, with different proportions of ash (shown as percentages in subscripts) in mixture with bentonite: ALWA0 (reference), ALWA12.5, ALWA25, ALWA50, and ALWA100. The following parameters of ALWA were determined: density, bulk density, compressive strength, hydraulic conductivity, and removal efficiency of ions Zn(2+), NH4 (+), and PO4 (3-). Tests showed that ALWA had good mechanical and hydraulic properties, and might be used in wastewater filtering systems. Phosphates and zinc ions were removed with high efficiency (80-96%) by ALWA25-100 in static (batch) conditions. The efficiency of ammonium nitrogen removal was low, <18%. Artificial wastewater treatment performance in dynamic conditions (through-flow), showed increasing removal efficiency of Zn(2+), PO4 (3-) with a decrease in flow rate.

  17. An Intensive Insulinotherapy Mobile Phone Application Built on Artificial Intelligence Techniques

    Science.gov (United States)

    Curran, Kevin; Nichols, Eric; Xie, Ermai; Harper, Roy

    2010-01-01

    Background Software to help control diabetes is currently an embryonic market with the main activity to date focused mainly on the development of noncomputerized solutions, such as cardboard calculators or computerized solutions that use “flat” computer models, which are applied to each person without taking into account their individual lifestyles. The development of true, mobile device-driven health applications has been hindered by the lack of tools available in the past and the sheer lack of mobile devices on the market. This has now changed, however, with the availability of pocket personal computer handsets. Method This article describes a solution in the form of an intelligent neural network running on mobile devices, allowing people with diabetes access to it regardless of their location. Utilizing an easy to learn and use multipanel user interface, people with diabetes can run the software in real time via an easy to use graphical user interface. The neural network consists of four neurons. The first is glucose. If the user's current glucose level is within the target range, the glucose weight is then multiplied by zero. If the glucose level is high, then there will be a positive value multiplied to the weight, resulting in a positive amount of insulin to be injected. If the user's glucose level is low, then the weights will be multiplied by a negative value, resulting in a decrease in the overall insulin dose. Results A minifeasibility trial was carried out at a local hospital under a consultant endocrinologist in Belfast. The short study ran for 2 weeks with six patients. The main objectives were to investigate the user interface, test the remote sending of data over a 3G network to a centralized server at the university, and record patient data for further proofing of the neural network. We also received useful feedback regarding the user interface and the feasibility of handing real-world patients a new mobile phone. Results of this short trial

  18. Genetically controlled fusion, exocytosis and fission of artificial vesicles-a roadmap

    DEFF Research Database (Denmark)

    Bönzli, Eva; Hadorn, Maik; de Lucrezia, Davide

    2011-01-01

    Artificial vesicles represent ideal candidates as a model for artificial cells. It was shown that artificial genetic programs and the required cellular machinery (cell-free expression systems) can be incorporated into vesicles and allow the synthesis of proteins (Noireaux et al. 2005). Vesicles...... of principle. Furthermore, we optimized the already established protocol (Hadorn et al. 2011) to produce nested vesicles in the presence of peptides. This project may present an important step towards an artificial cell. Especially vesicle division is discussed as one of the upcoming challenges in designing...... an artificial cell (Noireaux et al. 2011). Moreover, it may become important in personalized drug delivery....

  19. Biomechanics of a posture-controlling cervical artificial disc: mechanical, in vitro, and finite-element analysis.

    Science.gov (United States)

    Crawford, Neil R; Arnett, Jeffery D; Butters, Joshua A; Ferrara, Lisa A; Kulkarni, Nikhil; Goel, Vijay K; Duggal, Neil

    2010-06-01

    Different methods have been described by numerous investigators for experimentally assessing the kinematics of cervical artificial discs. However, in addition to understanding how artificial discs affect range of motion, it is also clinically relevant to understand how artificial discs affect segmental posture. The purpose of this paper is to describe novel considerations and methods for experimentally assessing cervical spine postural control in the laboratory. These methods, which include mechanical testing, cadaveric testing, and computer modeling studies, are applied in comparing postural biomechanics of a novel postural control arthroplasty (PCA) device versus standard ball-and-socket (BS) and ball-in-trough (BT) arthroplasty devices. The overall body of evidence from this group of tests supports the conclusion that the PCA device does control posture to a particular lordotic position, whereas BS and BT devices move freely through their ranges of motion.

  20. Fuzzy Self-Tuning PID Control of Hydrogen-Driven Pneumatic Artificial Muscle Actuator

    Institute of Scientific and Technical Information of China (English)

    Thanana Nuchkrua; Thananchai Leephakpreeda

    2013-01-01

    In this paper,a fuzzy self-tuning Proportional-Integral-Derivative (PID) control of hydrogen-driven Pneumatic Artificial Muscle (PAM) actuator is presented.With a conventional PID control,non-linear thermodynamics of the hydrogen-driven PAM actuator still highly affects the mechanical actuations itself,causing deyiation of desired tasks.The fuzzy self-tuning PID controller is systematically developed so as to achieve dynamic performance targets of the hydrogen-driven PAM actuator.The fuzzy rules based on desired characteristics of closed-loop control are designed to finely tune the PID gains of the controller under different operating conditions.The empirical models and properties of the hydrogen-driven PAM actuator are used as a genuine representation of mechanical actuations.A mass-spring-damper system is applied to the hydrogen-driven PAM actuator as a typical mechanical load during actuations.The results of the implementation show that the viability of the proposed method in actuating the hydrogen-driven PAM under mechanical loads is close to desired performance.

  1. Artificial neural network model with the parameter tuning assisted by a differential evolution technique: the study of the hold up of the slurry flow in a pipeline

    Directory of Open Access Journals (Sweden)

    S. K. Lahiri

    2009-05-01

    Full Text Available This paper describes a robust hybrid artificial neural network (ANN methodology which can offer a superior performance for the important process engineering problems. The method incorporates a hybrid artificial neural network and differential evolution technique (ANN-DE for the efficient tuning of ANN meta parameters. The algorithm has been applied for the prediction of the hold up of the solid liquid slurry flow. A comparison with selected correlations in the literature showed that the developed ANN correlation noticeably improved the prediction of hold up over a wide range of operating conditions, physical properties, and pipe diameters.

  2. A Multi-form Multiple Choice Editor Exam Tool Based on HTML Website and Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    A. Rjoub

    2009-01-01

    Full Text Available Problem statement: The educators argue that in the post modern world changes in the nature of work, globalization, the information revaluation and today's social challenges will all impact on educational priorities and thus will require a new mode of assessment. Approach: The objectives of this study were to: (1 Present a novel software package tool to create multiple choice and true/false exam forms. (2 Provide exams key solutions automatically (3 Meet special instructors' needs by allowing to easily incorporating multimedia elements into the exam questions, as well as the word processor editing functions and (4 Save both instructors time and money. Results: The multiform exam can be created randomly from question database or manually with shuffled answers for each question. The tool was built based on website and HTML interface using the multimedia applications, two different languages English/Arabic inserted to be used on the same time, efficient Artificial Intelligence techniques and Algorithms are used. The tool had been designed, implemented and tested by experienced instructors, with the result that efficiency, accountability and saving time improved. Conclusion/Recommendations: The transform from paper to electronic resulted in greatly enhanced user satisfaction. Editor exam tool can be used via internet without the need to download and install it to users machine, it’s a time saving system when multiple versions of random exams are required. This should highly motivated, instructors and teachers to utilize technology and IT to enhance exams and performance.

  3. Artificial neural networks and approximate reasoning for intelligent control in space

    Science.gov (United States)

    Berenji, Hamid R.

    1991-01-01

    A method is introduced for learning to refine the control rules of approximate reasoning-based controllers. A reinforcement-learning technique is used in conjunction with a multi-layer neural network model of an approximate reasoning-based controller. The model learns by updating its prediction of the physical system's behavior. The model can use the control knowledge of an experienced operator and fine-tune it through the process of learning. Some of the space domains suitable for applications of the model such as rendezvous and docking, camera tracking, and tethered systems control are discussed.

  4. Controlling dispersion forces between small particles with artificially created random light fields

    CERN Document Server

    Bruegger, Georges; Scheffold, Frank; Saenz, Juan Jose

    2015-01-01

    Appropriate combinations of laser beams can be used to trap and manipulate small particles with "optical tweezers" as well as to induce significant "optical binding" forces between particles. These interaction forces are usually strongly anisotropic depending on the interference landscape of the external fields. This is in contrast with the familiar isotropic, translationally invariant, van der Waals and, in general, Casimir-Lifshitz interactions between neutral bodies arising from random electromagnetic waves generated by equilibrium quantum and thermal fluctuations. Here we show, both theoretically and experimentally, that dispersion forces between small colloidal particles can also be induced and controlled using artificially created fluctuating light fields. Using optical tweezers as gauge, we present experimental evidence for the predicted isotropic attractive interactions between dielectric microspheres induced by laser-generated, random light fields. These light induced interactions open a path towards...

  5. Solving Harmonics Elimination Problem in Three-Phase Voltage controlled Inverter using Artificial Neural Networks

    Directory of Open Access Journals (Sweden)

    O. BOUHALI

    2005-03-01

    Full Text Available A novel concept of application of Artificial Neural Networks (ANN for generating the optimum switching functions for the voltage and harmonic control of DC-to-AC bridge inverters is presented. In many research, the neural network is trained off line using the desired switching angles given by the classic harmonic elimination strategy to any value of the modulation index. This limits the utilisability and the precision in other modulation index values. In order to avoid this problem, a new training algorithm is developed without using the desired switching angles but it uses the desired solution of the elimination harmonic equation, i.e. first harmonics are equal to zero. Theoretical analysis of the proposed solving algorithm with neural networks is provided, and simulation results are given to show the high performance and technical advantages of the developed modulator.

  6. The Virtual UNICOS Process Expert: integration of Artificial Intelligence tools in Control Systems

    CERN Multimedia

    Vilches Calvo, I; Barillere, R

    2009-01-01

    UNICOS is a CERN framework to produce control applications. It provides operators with ways to interact with all process items from the most simple (e.g. I/O channels) to the most abstract objects (e.g. a part of the plant). This possibility of fine grain operation is particularly useful to recover from abnormal situations if operators have the required knowledge. The Virtual UNICOS Process Expert project aims at providing operators with means to handle difficult operation cases for which the intervention of process experts is usually requested. The main idea of project is to use the openness of the UNICOS-based applications to integrate tools (e.g. Artificial Intelligence tools) which will act as Process Experts to analyze complex situations, to propose and to execute smooth recovery procedures.

  7. Promise of a Low Power Mobile CPU based Embedded System in Artificial Leg Control

    Science.gov (United States)

    Hernandez, Robert; Zhang, Fan; Zhang, Xiaorong; Huang, He; Yang, Qing

    2013-01-01

    This paper presents the design and implementation of a low power embedded system using mobile processor technology (Intel Atom™ Z530 Processor) specifically tailored for a neural-machine interface (NMI) for artificial limbs. This embedded system effectively performs our previously developed NMI algorithm based on neuromuscular-mechanical fusion and phase-dependent pattern classification. The analysis shows that NMI embedded system can meet real-time constraints with high accuracies for recognizing the user's locomotion mode. Our implementation utilizes the mobile processor efficiently to allow a power consumption of 2.2 watts and low CPU utilization (less than 4.3%) while executing the complex NMI algorithm. Our experiments have shown that the highly optimized C program implementation on the embedded system has superb advantages over existing PC implementations on MATLAB. The study results suggest that mobile-CPU-based embedded system is promising for implementing advanced control for powered lower limb prostheses. PMID:23367113

  8. Hormone-free protocols for the control of reproduction and artificial insemination in goats.

    Science.gov (United States)

    Lopez-Sebastián, A; Coloma, M A; Toledano, A; Santiago-Moreno, J

    2014-10-01

    The dairy goat industry is of great economic importance to certain rural areas of the European Union (EU), especially the Mediterranean region. Its sustainability, however, is severely affected by the seasonality of goat reproduction, which leads to fluctuations in the availability of final products. Classical hormone treatments based on progestagens and eCG are the main tools employed in the effort to achieve fertility outside of the normal breeding season. They are also used to induce and synchronize oestrus and ovulation in artificial insemination programs. The food safety policy of the EU is becoming ever stricter with regard to the use of hormonal treatments for reproductive purposes, pushing livestock-raising towards ever cleaner and greener production systems. Recent advances in the use of natural methods able to generate endocrine signals that induce the ovulatory process have improved our capacity to foster reproduction in the non-breeding season. When used in a fashion appropriate for the latitude at which animals live, their breed, and the management system under which they are raised, environmental (photoperiod), nutritional and sociosexual (the male effect) signals offer alternatives to classic hormonal techniques. This affords the fragile and heterogeneous goat production sector with new opportunities. This article describes the most representative advances made in the use of the male effect as a natural method of inducing ovulation during seasonal anoestrus. Its association with other methods for optimizing responses and synchronizing induced ovulation is also discussed; such associations allow it to be used as an alternative to hormonal treatment in artificial insemination programs.

  9. Synergistic control of forearm based on accelerometer data and artificial neural networks

    Directory of Open Access Journals (Sweden)

    B. Mijovic

    2008-05-01

    Full Text Available In the present study, we modeled a reaching task as a two-link mechanism. The upper arm and forearm motion trajectories during vertical arm movements were estimated from the measured angular accelerations with dual-axis accelerometers. A data set of reaching synergies from able-bodied individuals was used to train a radial basis function artificial neural network with upper arm/forearm tangential angular accelerations. The trained radial basis function artificial neural network for the specific movements predicted forearm motion from new upper arm trajectories with high correlation (mean, 0.9149-0.941. For all other movements, prediction was low (range, 0.0316-0.8302. Results suggest that the proposed algorithm is successful in generalization over similar motions and subjects. Such networks may be used as a high-level controller that could predict forearm kinematics from voluntary movements of the upper arm. This methodology is suitable for restoring the upper limb functions of individuals with motor disabilities of the forearm, but not of the upper arm. The developed control paradigm is applicable to upper-limb orthotic systems employing functional electrical stimulation. The proposed approach is of great significance particularly for humans with spinal cord injuries in a free-living environment. The implication of a measurement system with dual-axis accelerometers, developed for this study, is further seen in the evaluation of movement during the course of rehabilitation. For this purpose, training-related changes in synergies apparent from movement kinematics during rehabilitation would characterize the extent and the course of recovery. As such, a simple system using this methodology is of particular importance for stroke patients. The results underlie the important issue of upper-limb coordination.

  10. Active Force with Fuzzy Logic Control of a Two-Link Arm Driven by Pneumatic Artificial Muscles

    Institute of Scientific and Technical Information of China (English)

    H. Jahanabadi; M. Mailah; M. Z. Md Zain; H. M. Hooi

    2011-01-01

    In this paper,the practicality and feasibility of Active Force Control (AFC) integrated with Fuzzy Logic(AFCAFL) appliedto a two link planar arm actuated by a pair of Pneumatic Artificial Muscle (PAM) is investigated.The study emphasizes on the application and control of PAM actuators which may be considered as the new generation of actuators comprising fluidic muscle that has high-tension force,high power to weight ratio and high strength in spite of its drawbacks in the form of high nonlinearity behaviour,high hysteresis and time varying parameters.Fuzzy Logic (FL) is used as a technique to estimate the best value of the inertia matrix of robot arm essential for the AFC mechanism that is complemented with a conventional Proportional-Integral-Derivative (PID) control at the outermost loop.A simulation study was first performed followed by an experimental investigation for validation.The experimental study was based on the independent joint tracking control and coordinated motion control of the arm in Cartesian or task space.In the former,the PAM actuated arm is commanded to track the prescribed trajectories due to harmonic excitations at the joints for a given frequency,whereas for the latter,two sets of trajectories with different loadings were considered.A practical rig utilizing a Hardware-In-The-Loop Simulation (H1LS) configuration was developed and a number of experiments were carried out.The results of the experiment and the simulation works were in good agreement,which verified the effectiveness and robustness of the proposed AFCAFL scheme actuated by PAM.

  11. Incorporating Artificial Neural Networks in the dynamic thermal-hydraulic model of a controlled cryogenic circuit

    Science.gov (United States)

    Carli, S.; Bonifetto, R.; Savoldi, L.; Zanino, R.

    2015-09-01

    A model based on Artificial Neural Networks (ANNs) is developed for the heated line portion of a cryogenic circuit, where supercritical helium (SHe) flows and that also includes a cold circulator, valves, pipes/cryolines and heat exchangers between the main loop and a saturated liquid helium (LHe) bath. The heated line mimics the heat load coming from the superconducting magnets to their cryogenic cooling circuits during the operation of a tokamak fusion reactor. An ANN is trained, using the output from simulations of the circuit performed with the 4C thermal-hydraulic (TH) code, to reproduce the dynamic behavior of the heated line, including for the first time also scenarios where different types of controls act on the circuit. The ANN is then implemented in the 4C circuit model as a new component, which substitutes the original 4C heated line model. For different operational scenarios and control strategies, a good agreement is shown between the simplified ANN model results and the original 4C results, as well as with experimental data from the HELIOS facility confirming the suitability of this new approach which, extended to an entire magnet systems, can lead to real-time control of the cooling loops and fast assessment of control strategies for heat load smoothing to the cryoplant.

  12. Control and driving of pneumatic total artificial hearts TNS-BRNO-II and -III in long-term experiments.

    Science.gov (United States)

    Vasků, J; Urbánek, P; Vasků, J; Cerný, J; Smutný, M; Urbánek, E; Suchánek, J; Gregor, Z; Dostál, M; Guba, P

    1986-04-01

    Hemodynamic analysis was carried out during long-term experiments with the pneumatic total artificial hearts TNS-BRNO-II and TNS-BRNO-III to determine standard methods of starting artificial hearts and criteria for their long-term operation in vivo. In long-term experiments, regulatory mechanisms automatically regulating the systole length and diastolic aspiration pressure have also been verified. Comparison of hemodynamic variables obtained from invasive measurements with pneumatic pressure curves permitted the control and monitoring of the experiment in its entirety by noninvasive methods only. The control of the artificial heart using the Chirasist TN 3 and Chirasist TN 4 was adapted to specific properties of the pumps, above all to the functions of the atypical inlet valves. The terminal stages of the experiments have shown that a 100-ml pump can ensure survival of experimental calves up to 210 kg body weight.

  13. Artificial Cooperative Search Algorithm based Load Frequency Control of Interconnected Power Systems with AC-DC Tie-lines

    Directory of Open Access Journals (Sweden)

    S. Ramesh kumar

    2014-05-01

    Full Text Available A maiden effort for optimal tuning of load frequency controller parameters using Artificial Cooperative Search (ACS algorithm for a two area interconnected power system with AC-DC parallel tie-lines has been presented in this paper. ACS is a recent swarm intelligence algorithm developed for solving numerical optimization problems. The swarm intelligence philosophy behind ACS algorithm is based on the migration of two artificial superorganisms as they biologically interact to achieve the global minimum value pertaining to the problem. The HVDC link in parallel with AC tie-line is used as system interconnection to effectively damp the frequency oscillations of the AC system. An integral square error criterion (ISE has been used as performance index to design the optimal parameters. A comparative study of tuned values has been presented to show the effectiveness of the Artificial Cooperative Search algorithm. The results demonstrate the success of ACS algorithm in solving Load frequency control (LFC optimization problem.

  14. A comparison of hand washing techniques to remove Escherichia coli and caliciviruses under natural or artificial fingernails.

    Science.gov (United States)

    Lin, Chia-Min; Wu, Fone-Mao; Kim, Hoi-Kyung; Doyle, Michael P; Michael, Barry S; Williams, L Keoki

    2003-12-01

    Compared with other parts of the hand, the area beneath fingernails harbors the most microorganisms and is most difficult to clean. Artificial fingernails, which are usually long and polished, reportedly harbor higher microbial populations than natural nails. Hence, the efficacy of different hand washing methods for removing microbes from natural and artificial fingernails was evaluated. Strains of nonpathogenic Escherichia coli JM109 and feline calicivirus (FCV) strain F9 were used as bacterial and viral indicators, respectively. Volunteers with artificial or natural nails were artificially contaminated with ground beef containing E. coli JM109 or artificial feces containing FCV. Volunteers washed their hands with tap water, regular liquid soap, antibacterial liquid soap, alcohol-based hand sanitizer gel, regular liquid soap followed by alcohol gel, or regular liquid soap plus a nailbrush. The greatest reduction of inoculated microbial populations was obtained by washing with liquid soap plus a nailbrush, and the least reduction was obtained by rubbing hands with alcohol gel. Lower but not significantly different (P > 0.05) reductions of E. coli and FCV counts were obtained from beneath artificial than from natural fingernails. However, significantly (P hands with artificial nails than from natural nails before and after hand washing. In addition, microbial cell numbers were correlated with fingernail length, with greater numbers beneath fingernails with longer nails. These results indicate that best practices for fingernail sanitation of food handlers are to maintain short fingernails and scrub fingernails with soap and a nailbrush when washing hands.

  15. A program for assisting automatic generation control of the ELETRONORTE using artificial neural network; Um programa para assistencia ao controle automatico de geracao da Eletronorte usando rede neuronal artificial

    Energy Technology Data Exchange (ETDEWEB)

    Brito Filho, Pedro Rodrigues de; Nascimento Garcez, Jurandyr do [Para Univ., Belem, PA (Brazil). Centro Tecnologico; Charone Junior, Wady [Centrais Eletricas do Nordeste do Brasil S.A. (ELETRONORTE), Belem, PA (Brazil)

    1994-12-31

    This work presents an application of artificial neural network as a support to decision making in the automatic generation control (AGC) of the ELETRONORTE. It uses a software to auxiliary in the decisions in real time of the AGC. (author) 2 refs., 6 figs., 1 tab.

  16. UAV path planning using artificial potential field method updated by optimal control theory

    Science.gov (United States)

    Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long

    2016-04-01

    The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.

  17. On-chip artificial magnon-polariton device for voltage control of electromagnetically induced transparency

    Science.gov (United States)

    Kaur, Sandeep; Yao, Bimu; Gui, Yong-Sheng; Hu, Can-Ming

    2016-11-01

    We demonstrate an on-chip device utilizing the concept of an artificial cavity magnon-polariton (CMP) generated via coupling between a microwave cavity mode and the artificial magnetism dynamics of a split ring resonator. This on-chip device allows the easy tuning of the artificial CMP gap by using a DC voltage signal, which enables tuneable electrodynamically induced transparency. The high tunability of the artificial magnon-polariton system not only enables the study of phenomena associated with the classical analogues of different coupling regimes, but also may open up avenues for designing advanced microwave devices and ultra-sensitive sensors.

  18. Use of a novel double uterine deposition artificial insemination technique using low concentrations of sperm in pigs.

    Science.gov (United States)

    Mozo-Martín, R; Gil, L; Gómez-Rincón, C F; Dahmani, Y; García-Tomás, M; Úbeda, J L; Grandía, J

    2012-07-01

    Currently, the three most important non-surgical artificial insemination systems used in pigs are the conventional, the post-cervical (IUI), and the deep-intrauterine (DIUI) methods. In this study, a new system, termed double uterine deposition insemination (DUDI), which combines aspects of both IUI and DIUI, was evaluated. This method used a thinner, shorter and more flexible catheter than those normally used for DIUI and resulted in the deposition of semen post-cervically, approximately half-way along the uterine horn, thus potentially by-passing the threat of 'unilateral' insemination or pregnancy when using sperm of low concentration. The experiment was carried out over 8 weeks on a group of 166 sows, which were divided into seven groups, inseminated with semen of varying concentration, using the conventional system (control group) or by DUDI. There were no significant differences in fertility at day 35 post-insemination between the controls and the various DUDI sub-groups. Only sows inseminated with 500 million viable spermatozoa in a total of 30 mL of fluid using the DUDI system demonstrated decreased total litter sizes when compared to conventional insemination (Pinsemination normally uses 2.5-3.5 billion sperm, the findings of this study suggest that DUDI can be used under 'field' conditions with sperm concentrations as low as 750 million spermatozoa in 50-30 mL without any detrimental effect on fertility or litter size. DUDI may provide a viable, robust alternative to IUI and DIUI, and has the potential to become incorporated into on-farm insemination systems.

  19. Artificial kagome spin ice: dimensional reduction, avalanche control and emergent magnetic monopoles.

    Science.gov (United States)

    Hügli, R V; Duff, G; O'Conchuir, B; Mengotti, E; Rodríguez, A Fraile; Nolting, F; Heyderman, L J; Braun, H B

    2012-12-28

    Artificial spin-ice systems consisting of nanolithographic arrays of isolated nanomagnets are model systems for the study of frustration-induced phenomena. We have recently demonstrated that monopoles and Dirac strings can be directly observed via synchrotron-based photoemission electron microscopy, where the magnetic state of individual nanoislands can be imaged in real space. These experimental results of Dirac string formation are in excellent agreement with Monte Carlo simulations of the hysteresis of an array of dipoles situated on a kagome lattice with randomized switching fields. This formation of one-dimensional avalanches in a two-dimensional system is in sharp contrast to disordered thin films, where avalanches associated with magnetization reversal are two-dimensional. The self-organized restriction of avalanches to one dimension provides an example of dimensional reduction due to frustration. We give simple explanations for the origin of this dimensional reduction and discuss the disorder dependence of these avalanches. We conclude with the explicit demonstration of how these avalanches can be controlled via locally modified anisotropies. Such a controlled start and stop of avalanches will have potential applications in data storage and information processing.

  20. Engine control techniques to account for fuel effects

    Science.gov (United States)

    Kumar, Shankar; Frazier, Timothy R.; Stanton, Donald W.; Xu, Yi; Bunting, Bruce G.; Wolf, Leslie R.

    2014-08-26

    A technique for engine control to account for fuel effects including providing an internal combustion engine and a controller to regulate operation thereof, the engine being operable to combust a fuel to produce an exhaust gas; establishing a plurality of fuel property inputs; establishing a plurality of engine performance inputs; generating engine control information as a function of the fuel property inputs and the engine performance inputs; and accessing the engine control information with the controller to regulate at least one engine operating parameter.

  1. Nonlinear control techniques for an atomic force microscope system

    Institute of Scientific and Technical Information of China (English)

    Yongchun FANG; Matthew FEEMSTER; Darren DAWSON; Nader M.JALILI

    2005-01-01

    Two nonlinear control techniques are proposed for an atomic force microscope system.Initially,a learning-based control algorithm is developed for the microcantilever-sample system that achieves asymptotic cantilever tip tracking for periodic trajectories.Specifically,the control approach utilizes a learning-based feedforward term to compensate for periodic dynamics and high-gain terms to account for non-periodic dynamics.An adaptive control algorithm is then developed to achieve asymptotic cantilever tip tracking for bounded tip trajectories despite uncertainty throughout the system parameters.Simulation results are provided to illustrate the efficacy and performance of the control strategies.

  2. Sliding mode control of switching power converters techniques and implementation

    CERN Document Server

    Tan, Siew-Chong; Tse, Chi-Kong

    2011-01-01

    Sliding Mode Control of Switching Power Converters: Techniques and Implementation is perhaps the first in-depth account of how sliding mode controllers can be practically engineered to optimize control of power converters. A complete understanding of this process is timely and necessary, as the electronics industry moves toward the use of renewable energy sources and widely varying loads that can be adequately supported only by power converters using nonlinear controllers.Of the various advanced control methods used to handle the complex requirements of power conversion systems, sliding mode c

  3. Active vibration control of flexible cantilever plates using piezoelectric materials and artificial neural networks

    Science.gov (United States)

    Abdeljaber, Osama; Avci, Onur; Inman, Daniel J.

    2016-02-01

    The study presented in this paper introduces a new intelligent methodology to mitigate the vibration response of flexible cantilever plates. The use of the piezoelectric sensor/actuator pairs for active control of plates is discussed. An intelligent neural network based controller is designed to control the optimal voltage applied on the piezoelectric patches. The control technique utilizes a neurocontroller along with a Kalman Filter to compute the appropriate actuator command. The neurocontroller is trained based on an algorithm that incorporates a set of emulator neural networks which are also trained to predict the future response of the cantilever plate. Then, the neurocontroller is evaluated by comparing the uncontrolled and controlled responses under several types of dynamic excitations. It is observed that the neurocontroller reduced the vibration response of the flexible cantilever plate significantly; the results demonstrated the success and robustness of the neurocontroller independent of the type and distribution of the excitation force.

  4. Robust Fault-Tolerant Control for Satellite Attitude Stabilization Based on Active Disturbance Rejection Approach with Artificial Bee Colony Algorithm

    OpenAIRE

    Fei Song; Shiyin Qin

    2014-01-01

    This paper proposed a robust fault-tolerant control algorithm for satellite stabilization based on active disturbance rejection approach with artificial bee colony algorithm. The actuating mechanism of attitude control system consists of three working reaction flywheels and one spare reaction flywheel. The speed measurement of reaction flywheel is adopted for fault detection. If any reaction flywheel fault is detected, the corresponding fault flywheel is isolated and the spare reaction flywhe...

  5. Artificially constructed quorum-sensing circuits are used for subtle control of bacterial population density.

    Science.gov (United States)

    Wang, Zhaoshou; Wu, Xin; Peng, Jianghai; Hu, Yidan; Fang, Baishan; Huang, Shiyang

    2014-01-01

    Vibrio fischeri is a typical quorum-sensing bacterium for which lux box, luxR, and luxI have been identified as the key elements involved in quorum sensing. To decode the quorum-sensing mechanism, an artificially constructed cell-cell communication system has been built. In brief, the system expresses several programmed cell-death BioBricks and quorum-sensing genes driven by the promoters lux pR and PlacO-1 in Escherichia coli cells. Their transformation and expression was confirmed by gel electrophoresis and sequencing. To evaluate its performance, viable cell numbers at various time periods were investigated. Our results showed that bacteria expressing killer proteins corresponding to ribosome binding site efficiency of 0.07, 0.3, 0.6, or 1.0 successfully sensed each other in a population-dependent manner and communicated with each other to subtly control their population density. This was also validated using a proposed simple mathematical model.

  6. ARTIFICIAL NEURAL NETWORK CONTROLLER BASED DISTRIBUTION STATIC COMPENSATOR FOR VOLTAGE SAG MITIGATION

    Directory of Open Access Journals (Sweden)

    D. Rajasekaran

    2013-01-01

    Full Text Available Switching of loads, capacitors, along with the proliferation of power electronics equipment, non-linear loads in industrial, commercial and domestic applications have lead to power quality issues in the distribution system. Power quality issues such as voltage sag, voltage swell and harmonics, which are certainly major concerning issues in the present era. These issues can lead to failure or malfunction of the many sensitive loads connected to the distribution system, thus incurring a high cost for end users. Power quality problems are solved by advanced custom power devices. This study presents how the custom power device Distribution Static Compensator (D-STATCOM is used to mitigate voltage sag and voltage harmonics in distribution system. Artificial Neural Network (ANN controller based D-STATCOM is simulated in MATLAB-SIMULINK environment. Prototype model for single phase D-STATCOM is developed to verify the results. The simulation and hardware results show clearly the performance of the D-STATCOM in mitigating voltage sag and voltage harmonics in distribution system.

  7. 3D Tissue Scaffold Printing On Custom Artificial Bone Applications

    OpenAIRE

    Betül ALDEMİR; DİKİCİ, Serkan; ÖZTÜRK, Şükrü; KAHRAMAN, Ozan; Aylin ŞENDEMİR ÜRKMEZ; Oflaz, Hakan, 1980-

    2015-01-01

    Production of defect-matching scaffolds is the most critical step in custom artificial bone applications. Three dimensional printing (3DP) is one of the best techniques particularly for custom designs on artificial bone applications because of the high controllability and design independency. Our long-term aim is to implant an artificial custom bone that is cultured with patient's own mesenchymal stem cells after determining defect architecture on patient's bone by using CT-scan and printing ...

  8. A Novel Application of Artificial Neural Network for the Solution of Inverse Kinematics Controls of Robotic Manipulators

    Directory of Open Access Journals (Sweden)

    Santosh Kumar Nanda

    2012-08-01

    Full Text Available In robotic applications and research, inverse kinematics is one of the most important problems in terms of robot kinematics and control. Consequently, finding the solution of Inverse Kinematics in now days is considered as one of the most important problems in robot kinematics and control. As the intricacy of robot manipulator increases, obtaining the mathematical, statistical solutions of inverse kinematics are difficult and computationally expensive. For that reason, now soft-computing based highly intelligent based model applications should be adopted to getting appropriate solution for inverse kinematics. In this paper, a novel application of artificial neural network is used for controlling a robotic manipulator. The proposed methods are based on the establishments of the non-linear mapping between Cartesian and joint coordinates using multi layer perceptron and functional link artificial neural network.

  9. Application of Agent Technique in Traffic Control%Agent技术在交通控制中的应用

    Institute of Scientific and Technical Information of China (English)

    孙静

    2011-01-01

    The Agent originates the artificial intelligence,the artificial intelligence technique combines distributing type calculation techniques together in the middle of 80's in 20 centuries,appearing the distributing type artificial intelligence.At the same time,the Agent is mentioned more and more,the Agent technical research direction and applications contain more extensive development space,this text mainly introduced the Agent concept,characteristic,type,with many techniques of Agent in application of traffic control system.%Agent技术来源于分布式人工智能DAI领域。也有人将其翻译为智能主体或智能体,Agent技术在90年代成为热门话题,Agent一词越来越多地被提到,Agent技术的研究方向和应用就有了更加广泛的发展空间。主要介绍了Agent的概念、特性、类型,与多Agent技术在交通控制系统中的应用这两大方面的内容。

  10. A control theory approach to clock steering techniques.

    Science.gov (United States)

    Farina, Marcello; Galleani, Lorenzo; Tavella, Patrizia; Bittanti, Sergio

    2010-10-01

    Several clock and time scale steering methods have been developed according to different viewpoints by various time laboratories. By resorting to control theory ideas, we propose a common theoretical framework encompassing these methods. A comparison of the most common steering methodologies, namely, the classical steering approach, the GPS bang-bang method, and the linear quadratic Gaussian technique, is carried out. We believe that the use of control theory methods can potentially lead to a better understanding of clock steering algorithms.

  11. Abstraction and control techniques for non-stationary scheduling problems

    CERN Document Server

    Innocenti, Giacomo

    2009-01-01

    The paper faces the problem of scheduling from a new perspective, trying to bridge the gap between classical heuristic approaches and system identification and control strategies. To this aim, a complete mathematical formulation of a general scheduling process is derived, beginning from very broad assumptions. This allows a greater freedom of manipulation and guarantee the resolution of the identification (and control) techniques. Both an adaptive and a switching strategies are presented in relation to the performances of a simple Round Robin algorithm.

  12. Power electronic converters PWM strategies and current control techniques

    CERN Document Server

    Monmasson, Eric

    2013-01-01

    A voltage converter changes the voltage of an electrical power source and is usually combined with other components to create a power supply. This title is devoted to the control of static converters, which deals with pulse-width modulation (PWM) techniques, and also discusses methods for current control. Various application cases are treated. The book is ideal for professionals in power engineering, power electronics, and electric drives industries, as well as practicing engineers, university professors, postdoctoral fellows, and graduate students.

  13. Rewritable artificial magnetic charge ice

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Y. -L.; Xiao, Z. -L.; Snezhko, A.; Xu, J.; Ocola, L. E.; Divan, R.; Pearson, J. E.; Crabtree, G. W.; Kwok, W. -K.

    2016-05-19

    Artificial ices enable the study of geometrical frustration by design and through direct observation. However, it has proven difficult to achieve tailored long-range ordering of their diverse configurations, limiting both fundamental and applied research directions. We designed an artificial spin structure that produces a magnetic charge ice with tunable long-range ordering of eight different configurations. We also developed a technique to precisely manipulate the local magnetic charge states and demonstrate write-read-erase multifunctionality at room temperature. This globally reconfigurable and locally writable magnetic charge ice could provide a setting for designing magnetic monopole defects, tailoring magnonics, and controlling the properties of other two-dimensional materials.

  14. 白木通人工繁育技术研究%Research on Artificial Propagation Techniques of Caulis Akebiae

    Institute of Scientific and Technical Information of China (English)

    雷可

    2011-01-01

    为探讨白木通人工繁育技术,以出苗率和成活率为指标,研究了播种季节、播种方式对有性繁殖的影响,以及扦插种条前处理、扦插用种条的采集时间、扦插用种条的质量、扦插时间4因素对扦插效果的影响。结果表明,播种季节以农历冬至前后播种效果最好;播种方式为种子直播到塑料大棚的营养钵中,并加盖1~2 cm厚的营养土;扦插繁殖中,激素处理对扦插效果影响较大,其中ABT(2号)处理成活率最高;冬季采集种条置湿沙贮藏成活率明显高于其它采集时间所采集的种条;扦插种条的质量直接影响扦插成活率,其中以直接5~8 mm的种条成活率最高;扦插时间对扦插种条的成活起关键作用,其中以3月份扦插效果最好。通过本研究,初步拟定了白木通有性繁殖与无性繁殖技术。%To study the technique of artificial propagation of Akebia trifoliate. The effects of sexual reproduction in different planting season and with different planting methods were studied according to seed germination rate and survival rate. The effects of cuttage with different pre-treatment, in different cutting acquisition time,with different cutting qualifies, and in different outrage time were studies according to the survival rate. The best planting season was about lunar winter solstice. The best planting method was to plant seeds diretly in nutrition bowl in greenhouse and cover with 1 - 2 cm thick nutrient soil. In cuttage propagation, the highest survival rate was obtained from ABT ( NO. 2) treatment. The survival rate of cutting collected in winter was higher than that of collected in other seasons. The survival rate of cutting with 5 - 8 mm in length was higher than other length, and the cuttage time was very important to the survival rate, the best cuttage effect was obtained from March. Through this study, the technique of sexual reproduction and asexual propagation of Akebia trifoliate were

  15. Functional evaluation of artificial skeletal muscle tissue constructs fabricated by a magnetic force-based tissue engineering technique.

    Science.gov (United States)

    Yamamoto, Yasunori; Ito, Akira; Fujita, Hideaki; Nagamori, Eiji; Kawabe, Yoshinori; Kamihira, Masamichi

    2011-01-01

    Skeletal muscle tissue engineering is currently applied in a variety of research fields, including regenerative medicine, drug screening, and bioactuator development, all of which require the fabrication of biomimic and functional skeletal muscle tissues. In the present study, magnetite cationic liposomes were used to magnetically label C2C12 myoblast cells for the construction of three-dimensional artificial skeletal muscle tissues by an applied magnetic force. Skeletal muscle functions, such as biochemical and contractile properties, were evaluated for the artificial tissue constructs. Histological studies revealed that elongated and multinucleated myotubes were observed within the tissue. Expression of muscle-specific markers, such as myogenin, myosin heavy chain and tropomyosin, were detected in the tissue constructs by western blot analysis. Further, creatine kinase activity increased during differentiation. In response to electric pulses, the artificial tissue constructs contracted to generate a physical force (the maximum twitch force, 33.2 μN [1.06 mN/mm2]). Rheobase and chronaxie of the tissue were determined as 4.45 V and 0.72 ms, respectively. These results indicate that the artificial skeletal muscle tissue constructs fabricated in this study were physiologically functional and the data obtained for the evaluation of their functional properties may provide useful information for future skeletal muscle tissue engineering studies.

  16. Development of a modified artificial insemination technique combining penile vibration stimulation and the swim-up method in the common marmoset.

    Science.gov (United States)

    Takabayashi, Shuji; Suzuki, Yuiko; Katoh, Hideki

    2015-05-01

    The common marmoset, Callithrix jacchus, is used as a New World monkey species in biomedical studies because of its small body size and good reproduction in captivity. A modified artificial insemination technique was developed in this species to encourage breeding of lines carrying interesting genes and traits. Fresh semen was collected by penile vibratory stimulation. Medium containing highly motile sperm was inseminated into the uterus using a catheter. Seven females were inseminated using freshly prepared sperm from different males every day for 3 days including the expected ovulation day. As a result, four females conceived, and three females delivered six offspring in total (two singletons and one quadruplet). The paternity of the newborns was determined using microsatellite markers to accurately pinpoint the timing of insemination and ovulation. It is expected that our artificial insemination protocol can be effectively used to establish marmoset lines and genetically manage marmoset colonies.

  17. Artificial Culture and Breeding Technique of Shizothorax grahami%昆明裂腹鱼人工驯养繁殖技术

    Institute of Scientific and Technical Information of China (English)

    胡思玉; 詹会祥; 赵海涛; 陈永祥

    2012-01-01

    昆明裂腹鱼(Shizothorax grahami)是长江上游特有的较大型经济鱼类之一,为更好地保护这一珍稀鱼类资源,对其生物学特性、人工驯养及人工繁殖技术进行了综述,为昆明裂腹鱼的人工驯养及繁殖提供一定的理论依据.%Shizothorax grahami is a kind of economic fish which is unique in the upper Yangtze River. To protect this rarefish, the biological characteristics, artificial domestication and artificial reproduction techniques of Shizothorax grahami were investigated, and it have large theoretical significance.

  18. Quality control in hard disc drive manufacturing using pattern recognition technique

    Science.gov (United States)

    Masood, Ibrahim; Shyen, Victor Bee Ee

    2016-11-01

    Computerized monitoring-diagnosis is an efficient technique to identify the source of unnatural variation (UV) in manufacturing process. In this study, a pattern recognition scheme (PRS) for monitoring-diagnosis the UVs was developed based on control chart pattern recognition technique. This PRS integrates the multivariate exponentially weighted moving average (MEWMA) control chart and artificial neural network (ANN) recognizer to perform two-stage monitoring-diagnosis. The first stage monitoring was performed using the MEWMA statistics, whereas the second stage monitoring-diagnosis was performed using an ANN. The PRS was designed based on bivariate process mean shifts between 0.75σ and 3.00σ, with cross correlation between ρ=0.1 and 0.9. The performance of the proposed PRS has been validated in quality control of hard disk drive component manufacturing. The validation proved that it is efficient in rapidly detecting UV and accurately classify the source of UV patterns. In a nutshell, the PRS will aid in realizing automated decision making system in manufacturing industry.

  19. A new method of controlling chemical chaos——Nonlinear artificial neural network (ANN)-occasional perturbation feedback control in the whole chaotic region

    Institute of Scientific and Technical Information of China (English)

    宋浩; 蔡遵生; 赵学庄; 李勇军; 习保民; 李燕妮

    1999-01-01

    A new method of controlling chemical chaos to attain the stabilized unstable periodic orbit (UPO) is proposed. It is an extension of the occasional proportional feedback (OPF) control strategy which spans the limitations of OPF, i.e. the linear region of the control rule, and extends to the whole chaotic region. It also expresses the nonlinear control rule with the back propogation-artificial neural network (BP-ANN) in order to increase the robustness of the control. Its effectiveness is examined through controlling an autocatalytic chaotic reaction model numerically.

  20. Control Techniques in Heating, Ventilating and Air Conditioning Systems

    Directory of Open Access Journals (Sweden)

    H. Mirinejad

    2008-01-01

    Full Text Available Problem statement: Heating, Ventilating and Air Conditioning (HVAC systems are among the main installations in residential, commercial and industrial buildings. The purpose of the HVAC systems is normally to provide a comfortable environment in terms of temperature, humidity and other environmental parameters for the occupants as well as to save energy. Achieving these objectives requires a suitable control system design. Approach: In this overview, thermal comfort level and ISO comfort field is introduced, followed by a review and comparison of the main existing control techniques used in HVAC systems to date. Results: The present overview shows that intelligent controllers which are based on the human sensation of thermal comfort have a better performance in providing thermal comfort as well as energy saving than the traditional controllers and those based on a model of the HVAC system. Conclusion: Such an overview provides an insight into current control methods in HVAC systems and can help scholars and HVAC learners to have the comprehensive information about a variety of control techniques in the field of HVAC and therefore to better design a proper controller for their work

  1. The Development of Radiation hardened tele-robot system - Development of artificial force reflection control for teleoperated mobile robots

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Ju Jang; Hong, Sun Gi; Kang, Young Hoon; Kim, Min Soeng [Korea Advanced Institute of Science and Technology, Taejon (Korea)

    1999-04-01

    One of the most important issues in teleoperation is to provide the sense of telepresence so as to conduct the task more reliably. In particular, teleoperated mobile robots are needed to have some kinds of backup system when the operator is blind for remote situation owing to the failure of vision system. In the first year, the idea of artificial force reflection was researched to enhance the reliability of operation when the mobile robot travels on the plain ground. In the second year, we extend previous results to help the teleoperator even when the robot climbs stairs. Finally, we apply the developed control algorithms to real experiments. The artificial force reflection method has two modes; traveling on the plain ground and climbing stairs. When traveling on the plain ground, the force information is artificially generated by using the range data from the environment while generating the impulse force when climbing stairs. To verify the validity of our algorithm, we develop the simulator which consists of the joystick and the visual display system. Through some experiments using this system, we confirm the validity and effectiveness of our new idea of artificial force reflection in the teleoperated mobile robot. 11 refs., 30 figs. (Author)

  2. Artificial Error Tuning Based on Design a Novel SISO Fuzzy Backstepping Adaptive Variable Structure Control

    Directory of Open Access Journals (Sweden)

    Samaneh Zahmatkesh

    2013-10-01

    Full Text Available This paper examines single input single output (SISO chattering free variable structure control (VSC which controller coefficient is on-line tuned by fuzzy backstepping algorithm to control of continuum robot manipulator. Variable structure methodology is selected as a framework to construct the control law and address the stability and robustness of the close loop system based on Lyapunove formulation. The main goal is to guarantee acceptable error result and adjust the trajectory following. The proposed approach effectively combines the design technique from variable structure controller is based on Lyapunov and modified Proportional plus Derivative (P+D fuzzy estimator to estimate the nonlinearity of undefined system dynamic in backstepping controller. The input represents the function between variable structure function, error and the modified rate of error. The outputs represent joint torque, respectively. The fuzzy backstepping methodology is on-line tune the variable structure function based on adaptive methodology. The performance of the SISO VSC based on-line tuned by fuzzy backstepping algorithm (FBSAVSC is validated through comparison with VSC. Simulation results signify good performance of trajectory in presence of uncertainty joint torque load.

  3. H(sub infinity) techniques for spacecraft control

    Science.gov (United States)

    Frapard, B.; Leballois, S.; Champetier, C.

    1993-09-01

    The high performance Attitude and Orbit Control Systems (AOCS) and high accuracy Instrument Pointing Systems design require more and more control bandwidth: dynamic couplings can be no more neglected and control laws tend to be highly sensitive to the unmodeled dynamics. Multivariable systems analysis and optimal control synthesis tools, with robustness bounds/robustness constraints with respect to the unmodeled dynamics, are a major area of research for space applications. Among others, the large field of techniques provided by H(sub infinity) theory appears to be very promising. Two typical applications are presented in this paper, one concerning high accuracy pointing for observation satellites, with a particular interest in the SPOT Mark II platform, the other addressing the Drag Free Control problem for missions such as Aristoteles, STEP and Gravity Probe B.

  4. Safety of Outpatient Closed-Loop Control: First Randomized Crossover Trials of a Wearable Artificial Pancreas

    Science.gov (United States)

    Renard, Eric; Cobelli, Claudio; Zisser, Howard C.; Keith-Hynes, Patrick; Anderson, Stacey M.; Brown, Sue A.; Chernavvsky, Daniel R.; Breton, Marc D.; Mize, Lloyd B.; Farret, Anne; Place, Jérôme; Bruttomesso, Daniela; Del Favero, Simone; Boscari, Federico; Galasso, Silvia; Avogaro, Angelo; Magni, Lalo; Di Palma, Federico; Toffanin, Chiara; Messori, Mirko; Dassau, Eyal; Doyle, Francis J.

    2014-01-01

    OBJECTIVE We estimate the effect size of hypoglycemia risk reduction on closed-loop control (CLC) versus open-loop (OL) sensor-augmented insulin pump therapy in supervised outpatient setting. RESEARCH DESIGN AND METHODS Twenty patients with type 1 diabetes initiated the study at the Universities of Virginia, Padova, and Montpellier and Sansum Diabetes Research Institute; 18 completed the entire protocol. Each patient participated in two 40-h outpatient sessions, CLC versus OL, in randomized order. Sensor (Dexcom G4) and insulin pump (Tandem t:slim) were connected to Diabetes Assistant (DiAs)—a smartphone artificial pancreas platform. The patient operated the system through the DiAs user interface during both CLC and OL; study personnel supervised on site and monitored DiAs remotely. There were no dietary restrictions; 45-min walks in town and restaurant dinners were included in both CLC and OL; alcohol was permitted. RESULTS The primary outcome—reduction in risk for hypoglycemia as measured by the low blood glucose (BG) index (LGBI)—resulted in an effect size of 0.64, P = 0.003, with a twofold reduction of hypoglycemia requiring carbohydrate treatment: 1.2 vs. 2.4 episodes/session on CLC versus OL (P = 0.02). This was accompanied by a slight decrease in percentage of time in the target range of 3.9–10 mmol/L (66.1 vs. 70.7%) and increase in mean BG (8.9 vs. 8.4 mmol/L; P = 0.04) on CLC versus OL. CONCLUSIONS CLC running on a smartphone (DiAs) in outpatient conditions reduced hypoglycemia and hypoglycemia treatments when compared with sensor-augmented pump therapy. This was accompanied by marginal increase in average glycemia resulting from a possible overemphasis on hypoglycemia safety. PMID:24929429

  5. Models of signal validation using artificial intelligence techniques applied to a nuclear reactor; Modelos de validacao de sinal utilizando tecnicas de inteligencia artificial aplicados a um reator nuclear

    Energy Technology Data Exchange (ETDEWEB)

    Oliveira, Mauro V. [Instituto de Engenharia Nuclear (IEN), Rio de Janeiro, RJ (Brazil); Schirru, Roberto [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

    2000-07-01

    This work presents two models of signal validation in which the analytical redundancy of the monitored signals from a nuclear plant is made by neural networks. In one model the analytical redundancy is made by only one neural network while in the other it is done by several neural networks, each one working in a specific part of the entire operation region of the plant. Four cluster techniques were tested to separate the entire operation region in several specific regions. An additional information of systems' reliability is supplied by a fuzzy inference system. The models were implemented in C language and tested with signals acquired from Angra I nuclear power plant, from its start to 100% of power. (author)

  6. Robust and Accurate Closed-Loop Control of McKibben Artificial Muscle Contraction with a Linear Single Integral Action

    Directory of Open Access Journals (Sweden)

    Bertrand Tondu

    2014-06-01

    Full Text Available We analyze the possibility of taking advantage of artificial muscle’s own stiffness and damping, and substituting it for a classic proportional-integral-derivative controller (PID controller an I controller. The advantages are that there would only be one parameter to tune and no need for a dynamic model. A stability analysis is proposed from a simple phenomenological artificial muscle model. Step and sinus-wave tracking responses performed with pneumatic McKibben muscles are reported showing the practical efficiency of the method to combine accuracy and load robustness. In the particular case of the McKibben artificial muscle technology, we suggest that the dynamic performances in stability and load robustness would result from the textile nature of its braided sleeve and its internal friction which do not obey Coulomb’s third law, as verified by preliminary reported original friction experiments. Comparisons are reported between three kinds of braided sleeves made of rayon yarns, plastic, and thin metal wires, whose similar closed-loop dynamic performances are highlighted. It is also experimentally shown that a sleeve braided with thin metal wires can give high accuracy performance, in step as in tracking response. This would be due to a low static friction coefficient combined with a kinetic friction exponentially increasing with speed in accordance with hydrodynamic lubrication theory applied to textile physics.

  7. Key techniques of automatic gauge control and profile control for aluminium strip and foil

    Institute of Scientific and Technical Information of China (English)

    LI Mou-wei; LIU Hong-fei; WANG Xiang-li; TONG Chao-nan; YIN Feng-fu; BIAN Xin-xiao; ZHANG Lei

    2006-01-01

    Such characteristics of aluminium strip and foil as soft and thin gauge make tension control one of the key techniques for automation gauge control(AGC). To avoid the disadvantage of traditional mathematical control method which is unfitful for nonlinear hysteresis, the technique for tension AGC fuzzy control was developed and thickness deviation more than 3% of product thickness was achieved consequently in 1 350 mm cold rolling mill of aluminium strip and foil. Additionally, because the gauge of aluminium strip and foil is thin, stage-cooling roll method becomes a key technique for profile control. So stage-cooling roll intelligent control method is developed and pre-coated aluminum foil with good profile less than 10 I (the relative differences in elongation of 0.01% ) is produced using the profile control system in 1 400 mm cold rolling mill of aluminium strip and foil.

  8. Robust Fault-Tolerant Control for Satellite Attitude Stabilization Based on Active Disturbance Rejection Approach with Artificial Bee Colony Algorithm

    Directory of Open Access Journals (Sweden)

    Fei Song

    2014-01-01

    Full Text Available This paper proposed a robust fault-tolerant control algorithm for satellite stabilization based on active disturbance rejection approach with artificial bee colony algorithm. The actuating mechanism of attitude control system consists of three working reaction flywheels and one spare reaction flywheel. The speed measurement of reaction flywheel is adopted for fault detection. If any reaction flywheel fault is detected, the corresponding fault flywheel is isolated and the spare reaction flywheel is activated to counteract the fault effect and ensure that the satellite is working safely and reliably. The active disturbance rejection approach is employed to design the controller, which handles input information with tracking differentiator, estimates system uncertainties with extended state observer, and generates control variables by state feedback and compensation. The designed active disturbance rejection controller is robust to both internal dynamics and external disturbances. The bandwidth parameter of extended state observer is optimized by the artificial bee colony algorithm so as to improve the performance of attitude control system. A series of simulation experiment results demonstrate the performance superiorities of the proposed robust fault-tolerant control algorithm.

  9. New approaches in intelligent control techniques, methodologies and applications

    CERN Document Server

    Kountchev, Roumen

    2016-01-01

    This volume introduces new approaches in intelligent control area from both the viewpoints of theory and application. It consists of eleven contributions by prominent authors from all over the world and an introductory chapter. This volume is strongly connected to another volume entitled "New Approaches in Intelligent Image Analysis" (Eds. Roumen Kountchev and Kazumi Nakamatsu). The chapters of this volume are self-contained and include summary, conclusion and future works. Some of the chapters introduce specific case studies of various intelligent control systems and others focus on intelligent theory based control techniques with applications. A remarkable specificity of this volume is that three chapters are dealing with intelligent control based on paraconsistent logics.

  10. Multi-time-step ahead daily and hourly intermittent reservoir inflow prediction by artificial intelligent techniques using lumped and distributed data

    Science.gov (United States)

    Jothiprakash, V.; Magar, R. B.

    2012-07-01

    SummaryIn this study, artificial intelligent (AI) techniques such as artificial neural network (ANN), Adaptive neuro-fuzzy inference system (ANFIS) and Linear genetic programming (LGP) are used to predict daily and hourly multi-time-step ahead intermittent reservoir inflow. To illustrate the applicability of AI techniques, intermittent Koyna river watershed in Maharashtra, India is chosen as a case study. Based on the observed daily and hourly rainfall and reservoir inflow various types of time-series, cause-effect and combined models are developed with lumped and distributed input data. Further, the model performance was evaluated using various performance criteria. From the results, it is found that the performances of LGP models are found to be superior to ANN and ANFIS models especially in predicting the peak inflows for both daily and hourly time-step. A detailed comparison of the overall performance indicated that the combined input model (combination of rainfall and inflow) performed better in both lumped and distributed input data modelling. It was observed that the lumped input data models performed slightly better because; apart from reducing the noise in the data, the better techniques and their training approach, appropriate selection of network architecture, required inputs, and also training-testing ratios of the data set. The slight poor performance of distributed data is due to large variations and lesser number of observed values.

  11. Evaluation of techniques for enrichment and isolation of Escherichia coli O157:H7 from artificially contaminated sprouts.

    Science.gov (United States)

    Weagant, S D; Bound, A J

    2001-12-04

    Because sprouted seed products are kept wet during and after production, have high levels of nutrients, and a neutral pH, they are subject to the outgrowth of pathogens such as Escherichia coli O157:H7. For these same reasons, these products also contain high levels of heterotrophic organisms and in particular coliform bacteria. Recent outbreaks have focused attention on the need to improve methodology for isolating this pathogen from sprouts. When 40 E. coli O157:H7 strains were grown in pure culture in enterohemorrhagic E. coli enrichment broth (EEB) as prescribed in the U.S. FDA-Bacteriological Analytical Manual (FDA-BAM) and in EEB modified by varying the cefixime concentration, outgrowth for all strains in EEB was inhibited at 0.05 mg/l but for only 2 of 40 strains when the cefixime level was adjusted to 0.0125 mg/l. These two enrichment formulae were compared to modified E. coli broth (mEC), modified Tryptic Soy Broth with 20 mg/l novobiocin (mTSB + N), modified Buffered Peptone Water (mBPW), and mBPW with added 10 mg/l acriflavin, 10 mg/l cefsulodin, and 8 mg/l vancomycin (mBPW + ACV) for isolation of E. coli O157:H7 from sprouts. These comparisons were performed using low-level (0.12 to 0.42 cfu/g) artificially contaminated alfalfa and mixed salad sprouts. After enrichment, two isolation methods were compared for recovery; direct plating to Tellurite-Cefixime Sorbitol MacConkey agar (TCSMAC) and immunomagnetic separation (IMS) (Dynabeads anti-E. coli O157, Dynal, Oslo, Norway) followed by plating to TCSMAC. In addition, an immunoprecipitin detection kit, VIP (BioControl, Bellevue, WA), was evaluated for detection after enrichment. We found that five of the six enrichments were equivalent for detection or recovery while one enrichment (mTSB + N without agitation) was less productive. Incubation for 24 h was more effective in recovering E. coli O157:H7 from sprouts than 6 h for all enrichment broths. Plating after IMS was more productive than direct plating

  12. Algorithms for a Single Hormone Closed-Loop Artificial Pancreas: Challenges Pertinent to Chemical Process Operations and Control

    Directory of Open Access Journals (Sweden)

    B. Wayne Bequette

    2016-10-01

    Full Text Available The development of a closed-loop artificial pancreas to regulate the blood glucose concentration of individuals with type 1 diabetes has been a focused area of research for over 50 years, with rapid progress during the past decade. The daily control challenges faced by someone with type 1 diabetes include asymmetric objectives and risks, and one-sided manipulated input action with frequent relatively fast disturbances. The major automation steps toward a closed-loop artificial pancreas include (i monitoring and overnight alarms for hypoglycemia (low blood glucose; (ii overnight low glucose suspend (LGS systems to prevent hypoglycemia; and (iii fully closed-loop systems that adjust insulin (and perhaps glucagon to maintain desired blood glucose levels day and night. We focus on the steps that we used to develop and test a probabilistic, risk-based, model predictive control strategy for a fully closed-loop artificial pancreas. We complete the paper by discussing ramifications of lessons learned for chemical process systems applications.

  13. Selective Attention and Control of Action: Comparative Psychology of an Artificial, Evolved Agent and People

    Science.gov (United States)

    Ward, Robert; Ward, Ronnie

    2008-01-01

    This study examined the selective attention abilities of a simple, artificial, evolved agent and considered implications of the agent's performance for theories of selective attention and action. The agent processed two targets in continuous time, catching one and then the other. This task required many cognitive operations, including prioritizing…

  14. Biosolar cells: global artificial photosynthesis needs responsive matrices with quantum coherent kinetic control for high yield.

    Science.gov (United States)

    Purchase, R L; de Groot, H J M

    2015-06-06

    This contribution discusses why we should consider developing artificial photosynthesis with the tandem approach followed by the Dutch BioSolar Cells consortium, a current operational paradigm for a global artificial photosynthesis project. We weigh the advantages and disadvantages of a tandem converter against other approaches, including biomass. Owing to the low density of solar energy per unit area, artificial photosynthetic systems must operate at high efficiency to minimize the land (or sea) area required. In particular, tandem converters are a much better option than biomass for densely populated countries and use two photons per electron extracted from water as the raw material into chemical conversion to hydrogen, or carbon-based fuel when CO2 is also used. For the average total light sum of 40 mol m(-2) d(-1) for The Netherlands, the upper limits are many tons of hydrogen or carbon-based fuel per hectare per year. A principal challenge is to forge materials for quantitative conversion of photons to chemical products within the physical limitation of an internal potential of ca 2.9 V. When going from electric charge in the tandem to hydrogen and back to electricity, only the energy equivalent to 1.23 V can be stored in the fuel and regained. A critical step is then to learn from nature how to use the remaining difference of ca 1.7 V effectively by triple use of one overpotential for preventing recombination, kinetic stabilization of catalytic intermediates and finally generating targeted heat for the release of oxygen. Probably the only way to achieve this is by using bioinspired responsive matrices that have quantum-classical pathways for a coherent conversion of photons to fuels, similar to what has been achieved by natural selection in evolution. In appendix A for the expert, we derive a propagator that describes how catalytic reactions can proceed coherently by a convergence of time scales of quantum electron dynamics and classical nuclear dynamics. We

  15. Artificial vision.

    Science.gov (United States)

    Zarbin, M; Montemagno, C; Leary, J; Ritch, R

    2011-09-01

    A number treatment options are emerging for patients with retinal degenerative disease, including gene therapy, trophic factor therapy, visual cycle inhibitors (e.g., for patients with Stargardt disease and allied conditions), and cell transplantation. A radically different approach, which will augment but not replace these options, is termed neural prosthetics ("artificial vision"). Although rewiring of inner retinal circuits and inner retinal neuronal degeneration occur in association with photoreceptor degeneration in retinitis pigmentosa (RP), it is possible to create visually useful percepts by stimulating retinal ganglion cells electrically. This fact has lead to the development of techniques to induce photosensitivity in cells that are not light sensitive normally as well as to the development of the bionic retina. Advances in artificial vision continue at a robust pace. These advances are based on the use of molecular engineering and nanotechnology to render cells light-sensitive, to target ion channels to the appropriate cell type (e.g., bipolar cell) and/or cell region (e.g., dendritic tree vs. soma), and on sophisticated image processing algorithms that take advantage of our knowledge of signal processing in the retina. Combined with advances in gene therapy, pathway-based therapy, and cell-based therapy, "artificial vision" technologies create a powerful armamentarium with which ophthalmologists will be able to treat blindness in patients who have a variety of degenerative retinal diseases.

  16. L2-gain and passivity techniques in nonlinear control

    CERN Document Server

    van der Schaft, Arjan

    2017-01-01

    This standard text gives a unified treatment of passivity and L2-gain theory for nonlinear state space systems, preceded by a compact treatment of classical passivity and small-gain theorems for nonlinear input-output maps. The synthesis between passivity and L2-gain theory is provided by the theory of dissipative systems. Specifically, the small-gain and passivity theorems and their implications for nonlinear stability and stabilization are discussed from this standpoint. The connection between L2-gain and passivity via scattering is detailed. Feedback equivalence to a passive system and resulting stabilization strategies are discussed. The passivity concepts are enriched by a generalised Hamiltonian formalism, emphasising the close relations with physical modeling and control by interconnection, and leading to novel control methodologies going beyond passivity. The potential of L2-gain techniques in nonlinear control, including a theory of all-pass factorizations of nonlinear systems, and of parametrization...

  17. Integrated controlling technique of ecological environment in Shendong Mining Area

    Institute of Scientific and Technical Information of China (English)

    ZHANG Dong-sheng; LIU Yu-de; WANG An; WANG Yi

    2007-01-01

    To enclose the interactive relation between the underground mining with suitable protection for surface ecological environments and surface prevention of ecological environments adapting to mining disturbing was researched and developed core of this technique. There are three aspects of controlling ecological environments, to dispose and renew before exploitation, to protect surface ecological environments in the exploitative process and to repair and build up after exploitation. Based on the moving law of overburden strata in shallow seam, the surface subsidence law and the growth law of vegetation in subsidence mine area, the integrated controlling technique has been developed synthetically by methods of theoretic analysis, laboratory simulation, numerical calculation,commercial test etc.. It includes the key techniques of aquifer-protective mining, filtering and purging of mine water through goaf, preventing and extinguishing fire in shallow seam,no-rock roadway layout and waste disposal in underground, frame-building ecological functional sphere before exploitation, frame-building the ecological cycle using system after mining and so on.

  18. Application of altitude control techniques for low altitude earth satellites

    Science.gov (United States)

    Nickerson, K. G.; Herder, R. W.; Glass, A. B.; Cooley, J. L.

    1977-01-01

    The applications sensors of many low altitude earth satellites designed for recording surface or atmospheric data require near zero orbital eccentricities for maximum usefulness. Coverage patterns and altitude profiles require specified values of orbit semimajor axis. Certain initial combinations of semimajor axis, eccentricity, and argument of perigee can produce a so called 'frozen orbit' and minimum altitude variation which enhances sensor coverage. This paper develops information on frozen orbits and minimum altitude variation for all inclinations, generalizing previous results. In the altitude regions where most of these satellites function (between 200 and 1000 kilometers) strong atmospheric drag effects influence the evolution of the initial orbits. Active orbital maneuver control techniques to correct evolution of orbit parameters while minimizing the frequency of maneuvers are presented. The paper presents the application of theoretical techniques for control of near frozen orbits and expands upon the methods useful for simultaneously targeting several inplane orbital parameters. The applications of these techniques are illustrated by performance results from the Atmosphere Explorer (AE-3 and -5) missions and in preflight maneuver analysis and plans for the Seasat Oceanographic Satellite.

  19. A New Mathematical Modeling Technique for Pull Production Control Systems

    Directory of Open Access Journals (Sweden)

    O. Srikanth

    2013-12-01

    Full Text Available The Kanban Control System widely used to control the release of parts of multistage manufacturing system operating under a pull production control system. Most of the work on Kanban Control System deals with multi-product manufacturing system. In this paper, we are proposing a regression modeling technique in a multistage manufacturing system is to be coordinates the release of parts into each stage of the system with the arrival of customer demands for final products. And also comparing two variants stages of the Kanban Control System model and combines with mathematical and Simulink model for the production coordination of parts in an assembly manufacturing systems. In both variants, the production of a new subassembly is authorized only when an assembly Kanban is available. Assembly kanbans become available when finished product is consumed. A simulation environment for the product line system has to generate with the proposed model and the mathematical model have to give implementation against the simulation model in the working platform of MATLAB. Both the simulation and model outputs have provided an in depth analysis of each of the resulting control system for offering model of a product line system.

  20. Reinforcement learning techniques for controlling resources in power networks

    Science.gov (United States)

    Kowli, Anupama Sunil

    As power grids transition towards increased reliance on renewable generation, energy storage and demand response resources, an effective control architecture is required to harness the full functionalities of these resources. There is a critical need for control techniques that recognize the unique characteristics of the different resources and exploit the flexibility afforded by them to provide ancillary services to the grid. The work presented in this dissertation addresses these needs. Specifically, new algorithms are proposed, which allow control synthesis in settings wherein the precise distribution of the uncertainty and its temporal statistics are not known. These algorithms are based on recent developments in Markov decision theory, approximate dynamic programming and reinforcement learning. They impose minimal assumptions on the system model and allow the control to be "learned" based on the actual dynamics of the system. Furthermore, they can accommodate complex constraints such as capacity and ramping limits on generation resources, state-of-charge constraints on storage resources, comfort-related limitations on demand response resources and power flow limits on transmission lines. Numerical studies demonstrating applications of these algorithms to practical control problems in power systems are discussed. Results demonstrate how the proposed control algorithms can be used to improve the performance and reduce the computational complexity of the economic dispatch mechanism in a power network. We argue that the proposed algorithms are eminently suitable to develop operational decision-making tools for large power grids with many resources and many sources of uncertainty.

  1. The Use of Management Control Systems and Operations Management Techniques

    Directory of Open Access Journals (Sweden)

    Edelcio Koitiro Nisiyama

    2016-01-01

    Full Text Available It is well known that both management control systems (MCSs and operations management (OM are related to firm performance; however, an integrated st udy that involves MCS and OM within the context of firm performance is still lacking. This research aimed to examine the relationships among the use of MCSs and OM techniques and firm performance in the Brazilian auto parts industry. Simons’ levers of cont rol framework was used to characterise the uses of MCSs, and OM techniques, such as total quality management (TQM and continuous improvement programmes, were adopted. The results obtained through the structural equation modelling indicated that the diagno stic use of MCSs is positively associated with the goals of cost reduction. In addition, the interactive use of MCSs is positively associated with the objectives of introducing new products, which is consistent with previous research. Additionally, OM tech niques are positively related to cost reduction but have no direct relationship with the introduction of new products.

  2. Artificial neural network implementation of a near-ideal error prediction controller

    Science.gov (United States)

    Mcvey, Eugene S.; Taylor, Lynore Denise

    1992-01-01

    A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error

  3. HRCT: hop-by-hop rate control technique for congestion control in wireless sensor network

    Science.gov (United States)

    Chakravarthi, Rekha; Cidambaram, Gomathy

    2011-12-01

    In Wireless Sensor Networks, congestion occurs when the traffic rate is high. This happens when the an event is detected in a network. Congestion causes packet loss thus degrading the performance of the network. Hence it necessitates to develop an effective congestion control technique. This paper focuses on congestion due to concurrent transmission. We have proposed an efficient protocol to detect and control congestion in a MAC. The occurrence of congestion is detected by calculating a new metrics called congestion scale. When the congestion scale exceeds the threshold value it intimates, that, congestion has occurred. Congestion notification signal is send to all the nodes. On receiving the notification signal all nodes adjust their transmission rate to control congestion. We have implemented Hop-by-Hop Rate Control Technique(HRCT) to control congestion and to guarantee both high throughput and minimum delay. This technique is implemented successfully in NS-2 simulator. Finally, simulation results have demonstrated the effectiveness of our proposed algorithm.

  4. Artificial perches as a nucleation technique for restoration of a riparian environment: characterization of the seed rain and of natural regeneration

    Directory of Open Access Journals (Sweden)

    Aline Luiza Tomazi

    2010-09-01

    Full Text Available Riparian habitats are important to the maintenance of ecological processes and environmental services. However, a significant portion of the riparian vegetation in the Brazilian Atlantic forest has been removed in response to increasing human pressure. Therefore, the application of restoration techniques in these habitats becomes essential. In this context, a nucleation model with 18 artificial perches was evaluated for the restoration of a degraded riparian area in Gaspar, Santa Catarina, Brazil, by the characterization of the seed rain and natural regeneration. In two years we collected 21,864 seeds of 51 morphospecies, and recorded 42 colonizing species. Zoochoric seeds belonging to 15 plant families comprised 17% of the seed rain and 19.05% of the spontaneously regenerating plant species. Asteraceae and Poaceae were the most represented families. The artificial perches performed the nucleating function through the increase of zoochoric seed rain. However, possibly due to different barriers that were not evaluated in this study, part of these seeds was not recruited. We recommend the application of this technique for the attraction of dispersers in degraded areas similar to the study site.

  5. Fish recognition based on the combination between robust feature selection, image segmentation and geometrical parameter techniques using Artificial Neural Network and Decision Tree

    CERN Document Server

    Alsmadi, Mutasem Khalil Sari; Noah, Shahrul Azman; Almarashdah, Ibrahim

    2009-01-01

    We presents in this paper a novel fish classification methodology based on a combination between robust feature selection, image segmentation and geometrical parameter techniques using Artificial Neural Network and Decision Tree. Unlike existing works for fish classification, which propose descriptors and do not analyze their individual impacts in the whole classification task and do not make the combination between the feature selection, image segmentation and geometrical parameter, we propose a general set of features extraction using robust feature selection, image segmentation and geometrical parameter and their correspondent weights that should be used as a priori information by the classifier. In this sense, instead of studying techniques for improving the classifiers structure itself, we consider it as a black box and focus our research in the determination of which input information must bring a robust fish discrimination.The main contribution of this paper is enhancement recognize and classify fishes...

  6. Soft conductive elastomer materials for stretchable electronics and voltage controlled artificial muscles.

    Science.gov (United States)

    Stoyanov, Hristiyan; Kollosche, Matthias; Risse, Sebastian; Waché, Rémi; Kofod, Guggi

    2013-01-25

    Block copolymer elastomer conductors (BEC) are mixtures of block copolymers grafted with conducting polymers, which are found to support very large strains, while retaining a high level of conductivity. These novel materials may find use in stretchable electronics. The use of BEC is demonstrated in a capacitive strain sensor and in an artificial muscle of the dielectric elastomer actuator type, supporting more than 100% actuation strain and capacity strain sensitivity up to 300%.

  7. Identification and Control of Non-Linear Time-Varying Dynamical Systems Using Artificial Neural Networks

    Science.gov (United States)

    1992-09-01

    input. The architecture of artificial neural-network has three main levels: topological, data flow, and neurodynamics . The architectural and...and neurodynamics . The presentation here will follow the guidelines of Neural Computing by NeuralWare, Inc. [NC91], who developed the basic software... neurodynamics , describes in detail the operations that act upon the data within a processing element. This level defines the functions and the

  8. Application of Active Flow Control Technique for Gust Load Alleviation

    Institute of Scientific and Technical Information of China (English)

    XU Xiaoping; ZHU Xiaoping; ZHOU Zhou; FAN Ruijun

    2011-01-01

    A new gust load alleviation technique is presented in this paper based on active flow control.Numerical studies are conducted to investigate the beneficial effects on the aerodynamic characteristics of the quasi “Global Hawk” airfoil using arrays of jets during the gust process.Based on unsteady Navier-Stokes equations,the grid-velocity method is introduced to simulate the gust influence,and dynamic response in vertical gust flow perturbation is investigated for the airfoil as well.An unsteady surface transpiration boundary condition is enforced over a user specified portion of the airfoil's surface to emulate the time dependent velocity boundary conditions.Firstly,after applying this method to simulate typical NACA0006 airfoil gust response to a step change in the angle of attack,it shows that the indicial responses of the airfoil make good agreement with the exact theoretical values and the calculated values in references.Furthermore,gust response characteristic for the quasi “Global Hawk” airfoil is analyzed.Five kinds of flow control techniques are introduced as steady blowing,steady suction,unsteady blowing,unsteady suction and synthetic jets.The physical analysis of the influence on the effects of gust load alleviation is proposed to provide some guidelines for practice.Numerical results have indicated that active flow control technique,as a new technology of gust load alleviation,can affect and suppress the fluid disturbances caused by gust so as to achieve the purpose of gust load alleviation.

  9. Randomized Dynamical Decoupling Techniques for Coherent Quantum Control

    CERN Document Server

    Viola, L; Viola, Lorenza; Santos, Lea F.

    2006-01-01

    The need for strategies able to accurately manipulate quantum dynamics is ubiquitous in quantum control and quantum information processing. We investigate two scenarios where randomized dynamical decoupling techniques become more advantageous with respect to standard deterministic methods in switching off unwanted dynamical evolution in a closed quantum system: when dealing with decoupling cycles which involve a large number of control actions and/or when seeking long-time quantum information storage. Highly effective hybrid decoupling schemes, which combine deterministic and stochastic features are discussed, as well as the benefits of sequentially implementing a concatenated method, applied at short times, followed by a hybrid protocol, employed at longer times. A quantum register consisting of a chain of spin-1/2 particles interacting via the Heisenberg interaction is used as a model for the analysis throughout.

  10. Demand Management Based on Model Predictive Control Techniques

    Directory of Open Access Journals (Sweden)

    Yasser A. Davizón

    2014-01-01

    Full Text Available Demand management (DM is the process that helps companies to sell the right product to the right customer, at the right time, and for the right price. Therefore the challenge for any company is to determine how much to sell, at what price, and to which market segment while maximizing its profits. DM also helps managers efficiently allocate undifferentiated units of capacity to the available demand with the goal of maximizing revenue. This paper introduces control system approach to demand management with dynamic pricing (DP using the model predictive control (MPC technique. In addition, we present a proper dynamical system analogy based on active suspension and a stability analysis is provided via the Lyapunov direct method.

  11. Digital control of high performance aircraft using adaptive estimation techniques

    Science.gov (United States)

    Van Landingham, H. F.; Moose, R. L.

    1977-01-01

    In this paper, an adaptive signal processing algorithm is joined with gain-scheduling for controlling the dynamics of high performance aircraft. A technique is presented for a reduced-order model (the longitudinal dynamics) of a high performance STOL aircraft. The actual controller views the nonlinear behavior of the aircraft as equivalent to a randomly switching sequence of linear models taken from a preliminary piecewise-linear fit of the system nonlinearities. The adaptive nature of the estimator is necessary to select the proper sequence of linear models along the flight trajectory. Nonlinear behavior is approximated by effective switching of the linear models at random times, with durations reflecting aircraft motion in response to pilot commands.

  12. Intention recognition, commitment and their roles in the evolution of cooperation from artificial intelligence techniques to evolutionary game theory models

    CERN Document Server

    Han, The Anh

    2013-01-01

    This original and timely monograph describes a unique self-contained excursion that reveals to the readers the roles of two basic cognitive abilities, i.e. intention recognition and arranging commitments, in the evolution of cooperative behavior. This book analyses intention recognition, an important ability that helps agents predict others’ behavior, in its artificial intelligence and evolutionary computational modeling aspects, and proposes a novel intention recognition method. Furthermore, the book presents a new framework for intention-based decision making and illustrates several ways in which an ability to recognize intentions of others can enhance a decision making process. By employing the new intention recognition method and the tools of evolutionary game theory, this book introduces computational models demonstrating that intention recognition promotes the emergence of cooperation within populations of self-regarding agents. Finally, the book describes how commitment provides a pathway to the evol...

  13. Artificial intelligence in medicine.

    Science.gov (United States)

    Ramesh, A. N.; Kambhampati, C.; Monson, J. R. T.; Drew, P. J.

    2004-01-01

    INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting outcome in many clinical scenarios. METHODS: Medline and internet searches were carried out using the keywords 'artificial intelligence' and 'neural networks (computer)'. Further references were obtained by cross-referencing from key articles. An overview of different artificial intelligent techniques is presented in this paper along with the review of important clinical applications. RESULTS: The proficiency of artificial intelligent techniques has been explored in almost every field of medicine. Artificial neural network was the most commonly used analytical tool whilst other artificial intelligent techniques such as fuzzy expert systems, evolutionary computation and hybrid intelligent systems have all been used in different clinical settings. DISCUSSION: Artificial intelligence techniques have the potential to be applied in almost every field of medicine. There is need for further clinical trials which are appropriately designed before these emergent techniques find application in the real clinical setting. PMID:15333167

  14. Artificial Inductance Concept to Compensate Nonlinear Inductance Effects in the Back EMF-Based Sensorless Control Method for PMSM

    DEFF Research Database (Denmark)

    Lu, Kaiyuan; Lei, Xiao; Blaabjerg, Frede

    2013-01-01

    The back EMF-based sensorless control method is very popular for permanent magnet synchronous machines (PMSMs) in the medium- to high-speed operation range due to its simple structure. In this speed range, the accuracy of the estimated position is mainly affected by the inductance, which varies...... at different loading conditions due to saturation effects. In this paper, a new concept of using a constant artificial inductance to replace the actual varying machine inductance for position estimation is introduced. This facilitates greatly the analysis of the influence of inductance variation...

  15. Power Control Technique for Efficient Call Admission Control in Advanced Wirless Networks

    Directory of Open Access Journals (Sweden)

    Ch. Sreenivasa Rao

    2012-06-01

    Full Text Available In 4G networks, call admission control techniques have been proposed to provide Quality of Service (QoS in a network by restricting the access to network resources. Power control is essential in call admission control in order to provide fair access to all users, improve battery lifetime and system performance. But the existing call admission control algorithms rarely consider the power controlling techniques in the handoff process for different traffic classes. In this paper, we propose to develop a power controlled call admission control scheme for handoff in the advanced wireless networks. The incoming call measures the initial interference on it and then the base station starts transmitting the packets to the new call. The new call is rejected when the interference reaches a threshold value.Whenever an existing call meets the power constraint, the transmit power is decremented based on thetraffic class and incoming call obtains this information by monitoring the interference received on it. Theconvergence of the power control algorithm is checked and the power levels of all incoming calls areadjusted. From our simulation results we prove that this power control technique provides efficienthandoff in the 4G networks by increasing the throughput and reducing the delay of the existing users.

  16. The artificial and natural isotopes distribution in sedge (Carex L.) biomass from the Yenisei River flood-plain: Adaptation of the sequential elution technique.

    Science.gov (United States)

    Kropacheva, Marya; Melgunov, Mikhail; Makarova, Irina

    2017-02-01

    The study of migration pathways of artificial isotopes in the flood-plain biogeocoenoses, impacted by the nuclear fuel cycle plants, requires determination of isotope speciations in the biomass of higher terrestrial plants. The optimal method for their determination is the sequential elution technique (SET). The technique was originally developed to study atmospheric pollution by metals and has been applied to lichens, terrestrial and aquatic bryophytes. Due to morphological and physiological differences, it was necessary to adapt SET for new objects: coastal macrophytes growing on the banks of the Yenisei flood-plain islands in the near impact zone of Krasnoyarsk Mining and Chemical Combine (KMCC). In the first version of SET, 20 mM Na2EDTA was used as a reagent at the first stage; in the second version of SET, it was 1 M CH3COONH4. Four fractions were extracted. Fraction I included elements from the intercellular space and those connected with the outer side of the cell wall. Fraction II contained intracellular elements; fraction III contained elements firmly bound in the cell wall and associated structures; fraction IV contained insoluble residue. Adaptation of SET has shown that the first stage should be performed immediately after sampling. Separation of fractions III and IV can be neglected, since the output of isotopes into the IV fraction is at the level of error detection. The most adequate version of SET for terrestrial vascular plants is the version using 20 mM Na2EDTA at the first stage. Isotope (90)Sr is most sensitive to the technique changes. Its distribution depends strongly on both the extractant used at stage 1 and duration of the first stage. Distribution of artificial radionuclides in the biomass of terrestrial vascular plants can vary from year to year and depends significantly on the age of the plant.

  17. Controlling the pKa of the bacteriorhodopsin Schiff base by use of artificial retinal analogues.

    OpenAIRE

    1986-01-01

    Artificial bacteriorhodopsin pigments based on synthetic retinal analogues carrying an electron-withdrawing CF3 substituent group were prepared. The effects of CF3 on the spectra, photocycles, and Schiff base pKa values of the pigments were analyzed. A reduction of 5 units in the pKa of the Schiff base is observed when the CF3 substituent is located at the C-13 polyene position, in the vicinity of the protonated Schiff base nitrogen. The results lead to the unambiguous characterization of the...

  18. Artificial intelligence

    CERN Document Server

    Hunt, Earl B

    1975-01-01

    Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet

  19. Una Técnica de Inteligencia Artificial para el Ajuste de uno de los Elementos que Definen una B-Spline Racional No Uniforme (NURBS A Technique of Artificial Intelligence to Fit one of the Elements that Define a Non-Uniform Rational B-Spline (NURBS

    Directory of Open Access Journals (Sweden)

    Sandra P Mateus

    2010-01-01

    Full Text Available Dentro de las técnicas existentes de Inteligencia Artificial, se escogieron y adaptaron dos Redes Neuronales Artificiales (RNA para realizar el ajuste de uno de los elementos que definen una B-Spline Racional No Uniforme (NURBS y con ello obtener un modelado adecuado de la NURBS. Los elementos escogidos fueron los puntos de control. Las RNA utilizadas son las de Función de Base Radial y las de Kohonen o Mapas Auto-organizativos. Con base en el análisis de resultados y la caracterización de las RNA, la Función de Base Radial tuvo un desempeño más adecuado y óptimo para un número elevado de datos, lo cual es una desventaja de los Mapas Auto-organizativos. En este modelo se tiene que realizar procesos extras para determinar la neurona ganadora y realizar el reajuste de los pesos.In the existing techniques of Artificial Intelligence, two Artificial Neural Networks (ANN were selected and adapted to fit one of the elements that define a Non-Uniform Rational B-Spline (NURBS and thus obtaining an appropriate modeling of the NURBS. The selected elements were the checkpoints. The ANN used were the Radial Basis Function and the Kohonen model or Self-Organizing Maps. Based on the analysis of the results and characterization of the ANN the Radial Basis Function had a more appropriate and optimum performance for a large number of data, which is a disadvantage of the Self-Organizing Maps. In this model, additional processes must be done to determine the winning neuron and the weights must be refitted.

  20. Time-Based Dithering Algorithm and Frame Rate Control Technique for STN LCD Controller

    Institute of Scientific and Technical Information of China (English)

    LEIJianming; ZOUXuechen

    2004-01-01

    Time-based dithering algorithm and Frame rate control (FRC) technique applied to the STN liquid crystal display controller are presented. The dithering unit performs time-based dithering algorithm on pixel data to advantageously increase smoothness of an image displayed. The frame rate control unit is responsive to the dithering unit and performs frame rate controlling to generate more gray-shades, which may reduce flicker and visual artifacts. Results show that the gray shades displayed on images can be up to 256 for monochrome STN LCD panels or 2563 colors for color STN LCD panels respectively by using timebased dithering algorithm and frame rate control technique if each encoded pixel data is 8 bits. The images displayed on the STN liquid crystal display can get desirable grayshades and very little flicker and visual artifacts.

  1. Prediction of Heavy Metal Removal by Different Liner Materials from Landfill Leachate: Modeling of Experimental Results Using Artificial Intelligence Technique

    Science.gov (United States)

    Turan, Nurdan Gamze; Gümüşel, Emine Beril; Ozgonenel, Okan

    2013-01-01

    An intensive study has been made to see the performance of the different liner materials with bentonite on the removal efficiency of Cu(II) and Zn(II) from industrial leachate. An artificial neural network (ANN) was used to display the significant levels of the analyzed liner materials on the removal efficiency. The statistical analysis proves that the effect of natural zeolite was significant by a cubic spline model with a 99.93% removal efficiency. Optimization of liner materials was achieved by minimizing bentonite mixtures, which were costly, and maximizing Cu(II) and Zn(II) removal efficiency. The removal efficiencies were calculated as 45.07% and 48.19% for Cu(II) and Zn(II), respectively, when only bentonite was used as liner material. However, 60% of natural zeolite with 40% of bentonite combination was found to be the best for Cu(II) removal (95%), and 80% of vermiculite and pumice with 20% of bentonite combination was found to be the best for Zn(II) removal (61.24% and 65.09%). Similarly, 60% of natural zeolite with 40% of bentonite combination was found to be the best for Zn(II) removal (89.19%), and 80% of vermiculite and pumice with 20% of bentonite combination was found to be the best for Zn(II) removal (82.76% and 74.89%). PMID:23844384

  2. Intelligent PID controller based on ant system algorithm and fuzzy inference and its application to bionic artificial leg

    Institute of Scientific and Technical Information of China (English)

    谭冠政; 曾庆冬; 李文斌

    2004-01-01

    A designing method of intelligent proportional-integral-derivative(PID) controllers was proposed based on the ant system algorithm and fuzzy inference. This kind of controller is called Fuzzy-ant system PID controller. It consists of an off-line part and an on-line part. In the off-line part, for a given control system with a PID controller,by taking the overshoot, setting time and steady-state error of the system unit step response as the performance indexes and by using the ant system algorithm, a group of optimal PID parameters K*p , Ti* and T*d can be obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-line part, based on Kp* , Ti*and Td* and according to the current system error e and its time derivative, a specific program is written, which is used to optimize and adjust the PID parameters on-line through a fuzzy inference mechanism to ensure that the system response has optimal transient and steady-state performance. This kind of intelligent PID controller can be used to control the motor of the intelligent bionic artificial leg designed by the authors. The result of computer simulation experiment shows that the controller has less overshoot and shorter setting time.

  3. Microscope-controlled glass bead blasting: a new technique

    Directory of Open Access Journals (Sweden)

    Peter Kotschy

    2011-01-01

    Full Text Available Peter Kotschy1, Sascha Virnik2, Doris Christ3, Alexander Gaggl21Private Practice, Vienna, Austria; 2Department of Oral and Maxillofacial Surgery, Central Hospital, Klagenfurt, Austria; 3Klagenfurt, AustriaObjective: The aim of periodontal therapy is the healing of periodontal inflammation; the protection of the attachment and the alveolar bone; and the regeneration of the periodontal structures. In the therapy of periodontitis, supra- and subgingival scaling and root planing plays a main role. The procedure described combines perfect root cleaning without scaling and root planing and minimal invasive periodontal surgery without a scalpel.Material and methods: Glass beads of 90 µm were used with the kinetic preparation unit PrepStart® under a pressure of 0.5–5 bar. This technique was practised only under visual control using the OPMI® PRO Magis microscope. Seven examinations were carried out at baseline after 3, 6, 12, 18, 24, and 36 months.Results: Time shows a statistically significant influence on all of the considered target variables (P < 0.0001 for all. As the according estimate is negative, probing depth decreases over time. The major decrease seems to be during the first 6 months. Considering probing depth, plaque on the main effect root shows significant influence (again, P < 0.0001 for all. Observations with high probing depth at the beginning were faster than those with low probing depth. The same characteristic appears by attachment level. Patients with more loss of attachment show more gain.Conclusions: Using microscope-controlled glass bead blasting results in a perfectly clean root surface using visual control (magnification 20×. Microscope-controlled glass bead blasting is therefore a good alternative to periodontal surgery.Keywords: periodontal therapy, microscope, periodontitis

  4. Assessment of Climatological Trends of Sea Level over the Indian Coast Using Artificial Neural Network and Wavelet Techniques

    Science.gov (United States)

    Sudha Rani, N. N. V.; Satyanarayana, A. N. V.; Bhaskaran, Prasad Kumar

    2017-02-01

    In the present study, an attempt has been made to understand the variability of mean sea level (MSL) over east and west coast of India during 1973-2010. For this purpose, the monthly tide gauge data available over Kandla, Mumbai and Cochin along west coast and Diamond Harbour, Haldia, Visakhapatnam and Chennai along east coast obtained from PSMSL data archives has been considered. Sea level data from the tide gauge records show loss of data due to any disfunctioning of equipment or upgrade of the tide gauge resulting loss of data. It requires no gaps in the time series of MSL during the study period, and needs to be filled with better accuracy and hence artificial neural networks was implemented. To examine any periodicities of MSL variability, continuous wavelet analysis was conducted. The interrelationships between the stations in time-frequency space were examined, using cross and coherence wavelet analysis as well. The study reveals notable interannual variability of MSL. An observational analysis was done to understand the relation between inter-annual variability of MSL anomalies and ENSO. During positive (negative) SOI as associated with positive (negative) MSL anomaly was noticed significantly for the winter season over east (west) coast, where as during post-monsoon season this was observed for east coast and is less prevalent along the west coast. The observational analysis revealed that for the west (east) coast positive IOD showed significantly increased (decreased) MSL anomalies and negative IOD showed significantly decreased (increased) MSL anomalies. It is also found that the concurrent ENSO and IOD may have a different impact on MSL. The observations also reveal an increase of 1.353 mm/year on the east coast and observed a total 0.372 mm/year on the west coast.

  5. Identification and Position Control of Marine Helm using Artificial Neural Network Neural Network

    Directory of Open Access Journals (Sweden)

    Hui ZHU

    2008-02-01

    Full Text Available If nonlinearities such as saturation of the amplifier gain and motor torque, gear backlash, and shaft compliances- just to name a few - are considered in the position control system of marine helm, traditional control methods are no longer sufficient to be used to improve the performance of the system. In this paper an alternative approach to traditional control methods - a neural network reference controller - is proposed to establish an adaptive control of the position of the marine helm to achieve the controlled variable at the command position. This neural network controller comprises of two neural networks. One is the plant model network used to identify the nonlinear system and the other the controller network used to control the output to follow the reference model. The experimental results demonstrate that this adaptive neural network reference controller has much better control performance than is obtained with traditional controllers.

  6. Using an Artificial Neural Bypass to Restore Cortical Control of Rhythmic Movements in a Human with Quadriplegia

    Science.gov (United States)

    Sharma, Gaurav; Friedenberg, David A.; Annetta, Nicholas; Glenn, Bradley; Bockbrader, Marcie; Majstorovic, Connor; Domas, Stephanie; Mysiw, W. Jerry; Rezai, Ali; Bouton, Chad

    2016-09-01

    Neuroprosthetic technology has been used to restore cortical control of discrete (non-rhythmic) hand movements in a paralyzed person. However, cortical control of rhythmic movements which originate in the brain but are coordinated by Central Pattern Generator (CPG) neural networks in the spinal cord has not been demonstrated previously. Here we show a demonstration of an artificial neural bypass technology that decodes cortical activity and emulates spinal cord CPG function allowing volitional rhythmic hand movement. The technology uses a combination of signals recorded from the brain, machine-learning algorithms to decode the signals, a numerical model of CPG network, and a neuromuscular electrical stimulation system to evoke rhythmic movements. Using the neural bypass, a quadriplegic participant was able to initiate, sustain, and switch between rhythmic and discrete finger movements, using his thoughts alone. These results have implications in advancing neuroprosthetic technology to restore complex movements in people living with paralysis.

  7. Control selectivo por visión artificial del brazo Robotnik

    OpenAIRE

    Marín Guillén, Alberto

    2015-01-01

    La intención directa del presente proyecto es la de adquirir conocimientos de manera autónoma sobre materias de robótica y visión artificial, materias que no se imparten como tales en el itinerario de un graduado en G.I.T.I. y que siempre me han llamado la atención e interesado. Esto culminaría con la realización de una aplicación práctica que coordine las diferentes técnicas estudiadas. Se pretende obtener la solución de un problema real en que el papel de la visión sea tanto selectivo co...

  8. Controlled shear filtration: A novel technique for animal cell separation.

    Science.gov (United States)

    Vogel, J H; Kroner, K H

    1999-06-20

    A novel rotary microfiltration technique specifically suited for the separation of animal cells has been developed. The concept allows the independent adjustment of wall shear stress, transmembrane pressure, and residence time, allowing straightforward optimization of the microfiltration process. By using a smooth, conically shaped rotor, it is possible to establish a controlled shear field in which animal cells experience a significant hydrodynamic lift away from the membrane surface. It is shown in preliminary experiments that shear-induced cell-rupture speeds up membrane clogging and that cell debris poses the most significant problem in harvesting of BHK cell cultures by dynamic microfiltration. However, a threshold value of shear stability exists which depends on the frequency of passing the shear field, the residence time in the shear field, as well as on cell status. By operating close to this threshold value, cell viability can be maintained while concentration polarization is efficiently minimized. By applying this concept, it is possible to attain flux rates several times higher compared to conventional crossflow filtration. Controlled shear filtration (CSF) can be used for batch harvesting as well as for cell retention in high cell density systems. In batch harvesting of hIL-2 from rBHK cell culture, a constant flux rate of 290 L h-1 m-2 has been adjusted without indication of membrane clogging or fouling.

  9. 工程降水中人工回灌综合技术%Integrated technique of artificial recharge in engineering dewatering

    Institute of Scientific and Technical Information of China (English)

    冶雪艳; 耿冬青; 杜新强; 王福刚; 曹东军

    2011-01-01

    建筑工程降水往往伴生水资源浪费和地面变形等环境问题,人工回灌是解决这些问题的有效手段之一.影响工程降水中人工回灌的条件有回灌场地水文地质条件、回灌水源水质和水量及回灌方案的经济可行性等因素.就工程降水中出现的问题,提出资源补充型回灌和应力稳定型回灌方法,并给出了适用条件;根据工程降水水质特点及现有的地下水人工回灌相关水质标准,提出工程降水回灌水质的控制指标主要为悬浮物、浊度、一般污染性指标、微生物指标及重金属等.针对目前人工回灌在工程中存在的可回灌性低的问题,进行了影响入渗速率因素研究,为今后开展促渗关键技术提供理论支持.%The waste of water resources, ground deformation and other environmental issues are often associated with construction industry dewatering. Artificial recharge is an effective mean to solve these problems. Influential factors of artificial recharge in engineering dewatering are hydrogeological conditions of recharge site, water quality and quantity of recharge and the economic feasibility of recharge program. For the problems in the engineering dewatering, the authors propose two kinds of recharge methods including water resources supplement recharge and stress stable recharge, and propose the applicable conditions. According to the features of construction dewatering and the artificial recharge standards of native grounduater, it was suggested that the water quality control indicators of engineering dewatering are suspended solids, turbidity, general pollution indexes, microbial indexes and heavy metals. Aiming at the problem of low recharge in artificial recharge of construction, the factors that affect the infiltration rate is studied to give theoretical support of the key technology of promotion infiltration in future.

  10. Speed Control of a DC Motor for the Orientation of a Heliostat in a Solar Tower Power Plant using Artificial Intelligence Systems (FLC and NC

    Directory of Open Access Journals (Sweden)

    Abdelfettah Zeghoudi

    2015-06-01

    Full Text Available Recent research in the field of motor controls is becoming more interesting especially with the developments of new control methods. This study shows a comparative study between two artificial intelligence methods namely neural networks and fuzzy logic for the speed control of a DC motor for the orientation of a heliostat in a solar tower power plant. The speed controller of DC motor is performed using two Fuzzy Logic Configuration (FLC1 and FLC2 and neural controller in MATLAB environment. The simulation results are used to make sure the real possibility of using artificial intelligence systems to identify and control this type of installation. The performance of the Fuzzy Logic Controller and Neural control are compared using different errors metrics. The results show that Fuzzy logic method is more efficient compared with neural controller method.

  11. Estimation of global solar radiation using an artificial neural network based on an interpolation technique in southeast China

    Science.gov (United States)

    Zou, Ling; Wang, Lunche; Lin, Aiwen; Zhu, Hongji; Peng, Yuling; Zhao, Zhenzhen

    2016-08-01

    Solar radiation plays important roles in energy application, vegetation growth and climate change. Empirical relations and machine-learning methods have been widely used to estimate global solar radiation (GSR) in recent years. An artificial neural network (ANN) based on spatial interpolation is developed to estimate GSR in southeast China. The improved Bristow-Campbell (IBC) model and the improved Ångström-Prescott (IA-P) model are compared with the ANN model to explore the best model in solar radiation modeling. Daily meteorological parameters, such as sunshine duration hours, mean temperature, maximum temperature, minimum temperature, relative humidity, precipitation, air pressure, water vapor pressure, and wind speed, along with station-measured GSR and a daily surface GSR dataset over China obtained from the Data Assimilation and Modeling Center for Tibetan Multi-spheres (DAM), are used to predict GSR and to validate the models in this work. The ANN model with the network of 9-17-1 provides better accuracy than the two improved empirical models in GSR estimation. The root-mean-square error (RMSE), mean bias error (MBE), and determination coefficient (R2) are 2.65 MJ m-2, -0.94 MJ m-2, and 0.68 in the IA-P model; 2.19 MJ m-2, 1.11 MJ m-2, and 0.83 in the IBC model; 1.34 MJ m-2, -0.11 MJ m-2, and 0.91 in the ANN model, respectively. The regional monthly mean GSR in the measured dataset, DAM dataset, and ANN model is analyzed. The RMSE (RMSE %) is 1.07 MJ m-2 (8.91%) and the MBE (MBE %) is -0.62 MJ m-2 (-5.21%) between the measured and ANN-estimated GSR. The statistical errors of RMSE (RMSE %) are 0.91 MJ m-2 (7.28%) and those of MBE (MBE %) are -0.15 MJ m-2 (-1.20%) between DAM and ANN-modeled GSR. The correlation coefficients and R2 are larger than 0.95. The regional mean GSR is 12.58 MJ m-2. The lowest GSR is observed in the northwest area, and it increases from northwest to southeast. The annual mean GSR decreases by 0.02 MJ m-2 decade-1 over the entire

  12. Artificial Intelligence.

    Science.gov (United States)

    Waltz, David L.

    1982-01-01

    Describes kinds of results achieved by computer programs in artificial intelligence. Topics discussed include heuristic searches, artificial intelligence/psychology, planning program, backward chaining, learning (focusing on Winograd's blocks to explore learning strategies), concept learning, constraint propagation, language understanding…

  13. New techniques to control salinity-wastewater reuse interactions in golf courses of the Mediterranean regions

    Science.gov (United States)

    Beltrao, J.; Costa, M.; Rosado, V.; Gamito, P.; Santos, R.; Khaydarova, V.

    2003-04-01

    or artificial leaching remained; 3) Enhanced fertilization increases turfgrass tolerance to salinity, but the contamination will be increased by other hazardous chemicals such as nitrate; 4) Use of salt tolerant turfgrass species this technique will be very useful to the plants, but does not solve the problem os soil or groundwater contamination. When reusing treated wastewater in the Mediterranean areas, the only way to control the salination process and to maintain the sustainability of golf courses is to combat the salination problems by environmentally safe and clean techniques. These new clean techniques include: 1) Use of salt removing turfgrass species; 2) Use of drought tolerant turfgrass species - reduction of salt application by deficit irrigation; 3) Reuse of minimal levels of wastewater enough to obtain a good visual appearance GVA of the turfgrass. Regarding these new clean techniques, experiments were carried out in golf courses of Algarve, Portugal, the most southwest part of Europe. It was shown: 1) Use of salt removing turfgrass species - 3 sprinkle irrigated cultivars were studied (Agrostis solonífera L.; Cynodon dactylon, L. and Penninsetum clandestinum Hochst ex Chiov). 2) Use of drought tolerant turfgrass species -responses to several levels of sprinkle irrigation wastewater and potable water (with and without fertilization). An experimental design, known as sprinkle point source was specially used to simulate the several levels of water application, expressed by the crop coefficient kc and by the crop evapotranspiration rate ETc. Turfgrass yield was enhanced linearly with the increased application of treated wastewater. 3) Reuse of minimal levels of wastewater enough to obtain a good visual appearance GVA of the turfgrass - The minimal crop coefficient kc for a good visual appearance GVA of the turfgrass was around 1.0 to potable water irrigated mixed cultivars (with 30 kg nitrogen ha-1 month-1) and 1.2 to wastewater irrigated Bermuda grass

  14. Improvement of Power System Stability using Artificial Neural Network based HVDC Controls

    Directory of Open Access Journals (Sweden)

    Nagu Bhookya

    2013-06-01

    Full Text Available In this paper, investigation is carried out for the improvement of power system stability by utilizing auxiliary controls for controlling HVDC power flow. The current controller model and the line dynamics are considered in the stability analysis. Transient stability analysis is done on a multi-machine system, where, a neural network controller is developed to improve the stability of the power system and to improve the response time of the controller to the changing conditions in power system. The results show the application of the neural network controller in AC-DC power systems.

  15. Start of reproduction and allozyme heterozygosity in Pinus sibirica under different techniques of artificial forest stand establishment

    Directory of Open Access Journals (Sweden)

    S.N. Velisevich

    2013-12-01

    Full Text Available Siberian stone pine (Pinus sibirica Du Tour is one of the main forest-forming tree species in boreal forests of Eurasia. Large edibleseeds of this species have an important resource value because of their high nutritious properties. Development of approaches toestablishment of early cone producing Siberian stone pine stands including utilization of corresponding genetic background is one of the priorities of forest resource management. The goal of our study was to evaluate the effect of stand density on the differentiation of trees bythe age of first reproduction and the relationship of allozyme heterozygosity and morphological traits variability in Siberian stone pine.Morphological and allozyme variability in artificial Pinus sibirica stands with high and low density was investigated. In the high-densitystand the distance between trees was 0.7 and 3 meters (4080 trees per ha while in the lowdensity stand it was 8 and 8 meters (144 treesper ha. Age of formation of first male and female cones was evaluated by retrospective method based on analysis of tracks of cones ona shoot bark. Tree height, diameter and number of male, female and vegetative shoots in a crown of model trees were measured.Genotypes of the trees were determined by 29 isozyme loci coding for 16 enzymes (ADH, FDH, FEST, GDH, GOT, IDH, LAP, MDH, MNR, PEPCA, 6-PGD, PGI, PGM, SDH, SKDH, SOD. In the low-density stand, the portion of generative trees was higher and differentiation of trees by age of reproduction starting was lower in spite of the smaller age of trees as compared to the high-density stand. Inboth samples, the age of formation of first generative organs was related negatively with stem height, stem diameter and number offemale shoots. In the high-density stand, positive relation of age of first reproduction with total number of shoots and number ofmale shoots was found. In both samples nonreproductive trees were less heterozygous at

  16. An osseointegrated human-machine gateway for long-term sensory feedback and motor control of artificial limbs.

    Science.gov (United States)

    Ortiz-Catalan, Max; Håkansson, Bo; Brånemark, Rickard

    2014-10-08

    A major challenge since the invention of implantable devices has been a reliable and long-term stable transcutaneous communication. In the case of prosthetic limbs, existing neuromuscular interfaces have been unable to address this challenge and provide direct and intuitive neural control. Although prosthetic hardware and decoding algorithms are readily available, there is still a lack of appropriate and stable physiological signals for controlling the devices. We developed a percutaneous osseointegrated (bone-anchored) interface that allows for permanent and unlimited bidirectional communication with the human body. With this interface, an artificial limb can be chronically driven by implanted electrodes in the peripheral nerves and muscles of an amputee, outside of controlled environments and during activities of daily living, thus reducing disability and improving quality of life. We demonstrate in one subject, for more than 1 year, that implanted electrodes provide a more precise and reliable control than surface electrodes, regardless of limb position and environmental conditions, and with less effort. Furthermore, long-term stable myoelectric pattern recognition and appropriate sensory feedback elicited via neurostimulation was demonstrated. The opportunity to chronically record and stimulate the neuromuscular system allows for the implementation of intuitive control and naturally perceived sensory feedback, as well as opportunities for the prediction of complex limb motions and better understanding of sensory perception. The permanent bidirectional interface presented here is a critical step toward more natural limb replacement, by combining stable attachment with permanent and reliable human-machine communication.

  17. An Artificial Neural Network Compensated Output Feedback Power-Level Control for Modular High Temperature Gas-Cooled Reactors

    Directory of Open Access Journals (Sweden)

    Zhe Dong

    2014-02-01

    Full Text Available Small modular reactors (SMRs could be beneficial in providing electricity power safely and also be viable for applications such as seawater desalination and heat production. Due to its inherent safety features, the modular high temperature gas-cooled reactor (MHTGR has been seen as one of the best candidates for building SMR-based nuclear power plants. Since the MHTGR dynamics display high nonlinearity and parameter uncertainty, it is necessary to develop a nonlinear adaptive power-level control law which is not only beneficial to the safe, stable, efficient and autonomous operation of the MHTGR, but also easy to implement practically. In this paper, based on the concept of shifted-ectropy and the physically-based control design approach, it is proved theoretically that the simple proportional-differential (PD output-feedback power-level control can provide asymptotic closed-loop stability. Then, based on the strong approximation capability of the multi-layer perceptron (MLP artificial neural network (ANN, a compensator is established to suppress the negative influence caused by system parameter uncertainty. It is also proved that the MLP-compensated PD power-level control law constituted by an experientially-tuned PD regulator and this MLP-based compensator can guarantee bounded closed-loop stability. Numerical simulation results not only verify the theoretical results, but also illustrate the high performance of this MLP-compensated PD power-level controller in suppressing the oscillation of process variables caused by system parameter uncertainty.

  18. Artificial Intelligence in Space Platforms.

    Science.gov (United States)

    1984-12-01

    computer algorithms, there still appears to be a need for Artificial Inteligence techniques in the navigation area. The reason is that navigaion, in...RD-RI32 679 ARTIFICIAL INTELLIGENCE IN SPACE PLRTFORNSMU AIR FORCE 1/𔃼 INST OF TECH WRIGHT-PRTTERSON AFB OH SCHOOL OF ENGINEERING M A WRIGHT DEC 94...i4 Preface The purpose of this study was to analyze the feasibility of implementing Artificial Intelligence techniques to increase autonomy for

  19. Channel Based Adaptive Rate Control Technique for MANET

    Directory of Open Access Journals (Sweden)

    R. Bharathiraja

    2014-04-01

    Full Text Available In Mobile Ad hoc Networks (MANET, most of the existing works does not consider energy efficiency during selecting the appropriate route. Hence in MANET selecting the appropriate route and also maintaining energy efficiency is very important. Hence in order to overcome these issues, in this study we propose Channel Based Adaptive Rate Control technique for MANET. Here the most appropriate links is selected to transmit the node with efficient power consumption. The node broadcasts the information of its outgoing and incoming links in NSET instead of waiting for the feedback informattion from receiver. The number of packets transmitted in a channel access time is maximized by implementing the benefit ratio in rate selection algorithm. This study also introduces node cooperation, in node cooperation the node determines the feasibility of new rate setting determined by rate selection algorithm and it carries out new setting if it is feasible by following help, ack, reject and accept method. By simulation results we show that the proposed approach is power efficient and also increases the trasmission rate.

  20. Selective attention and control of action: comparative psychology of an artificial, evolved agent and people.

    Science.gov (United States)

    Ward, Robert; Ward, Ronnie

    2008-10-01

    This study examined the selective attention abilities of a simple, artificial, evolved agent and considered implications of the agent's performance for theories of selective attention and action. The agent processed two targets in continuous time, catching one and then the other. This task required many cognitive operations, including prioritizing the first target (T1) over the second (T2); selectively focusing responses on T1, while preventing T2 from interfering with responses; creating a memory for the unselected T2 item, so that it could be efficiently processed later; and reallocating processing towards T2 after catching T1. The evolved agent demonstrated all these abilities. Analysis shows that the agent used reactive inhibition to selectively focus behavior. That is, the more salient T2, the more strongly responses towards T2 were inhibited and the slower the agent was to subsequently reallocate processing towards T2. Reactive inhibition was also suggested in two experiments with people, performing a virtually identical catch task. The presence of reactive inhibition in the simple agent and in people suggests that it is an important mechanism for selective processing.

  1. Blood glucose control using an artificial pancreas reduces the workload of ICU nurses.

    Science.gov (United States)

    Mibu, Kiyo; Yatabe, Tomoaki; Hanazaki, Kazuhiro

    2012-03-01

    Blood glucose management is one of the important therapies in the intensive care unit (ICU). However, blood glucose management using the sliding-scale method increases the workload of ICU nurses. An artificial pancreas, STG-22, has been developed to continuously monitor blood glucose levels and to maintain them at appropriate levels. In this study, we examined the hypothesis that compared to conventional methods, blood glucose management using the STG-22 reduces the workload of ICU nurses and has a positive impact on awareness regarding the management of blood glucose. This study included 45 patients who underwent elective surgery and were treated at the ICU postoperatively. The patients were separated into the following two groups: (1) blood glucose was maintained using the STG-22 (AP group) and (2) blood glucose was maintained using the sliding-scale method (SS group). In addition, a questionnaire was developed for an awareness survey of ICU nurses (N = 20). The frequency of blood sampling and number of double checks were significantly lower in the AP group (1.3 ± 1.4 vs. 8.9 ± 8.1 times/admission, P blood glucose.

  2. The effect of antioxidant selenium nanoparticles on the parameters of young and old mice sperm using the techniques of artificial intelligence network

    Directory of Open Access Journals (Sweden)

    Pedram Yaghmouri

    2016-11-01

    Full Text Available Introduction: It seems that investigating the Parameters related to sperm be useful to assess the impactof age onsemen quality.Factors such asdrug dosage, how to get and duration ofmedication use andevenphysiological conditions(sex andage of the animal alsoaffects onthe outcome. Usingthe wrongdoseor inappropriately duration of treatment, causing adverse effects on the antioxidants. The main goal of this study is Using artificial neural network techniques answer this main question that whether Selenium nanoparticles Such account of spermatozoon, percentage of stimulation, sperm viability percentage are effective on mouse sperm parameters or not ? Research method: in this study , In order to predictthenumber ofspermatozoain mice , Mousesperm viabilityand Stimulationpercentage ofMouse , Some of the important propertiessuch as mouse age and The amount of silicananoparticles presence were used As inputs to the neural network Findings. By calculating theparameters such as Matchingcoefficient, the square root oferror, etc., the accuracy and validity of results was evaluated. ANNmodeloptimizedstructure wascalculatedfor predicting the count of spermatozoon, percentage of stimulation, sperm viability percentage withformat2: 7: 1, 6: 2: 1and2: 7: 1respectively. Conclusion: The results of neural network techniques showed that antioxidant selenium nanoparticles affects the parameters of mouse sperm such as count of spermatozoon, percentage of stimulation, sperm viability percentage .

  3. A GIS based hydrogeomorphic approach for identification of site-specific artificial-recharge techniques in the Deccan Volcanic Province

    Indian Academy of Sciences (India)

    M N Ravi Shankar; G Mohan

    2005-10-01

    The Deccan Volcanic Province (DVP)of India,as a whole,faces a severe shortage of water despite receiving a high annual rainfall,this is primarily due to excess runoff and lack of water conservation practices.In this study,an attempt is made to identify zones favourable for the application and adaptation of site-specific artificial-recharge techniques for augmentation of groundwater through a Geographical Information System (GIS)based hydrogeomorphic approach in the Bhatsa and Kalu river basins of Thane district,in western DVP.The criteria adopted for the GIS analysis were based on the hydrogeomorphological characteristics of both basins extracted from the IRS- 1C LISS-III data supported by information on drainage pattern,DEM derived slope,lineament density,drainage density,and groundwater condition.The integrated study helps design a suitable groundwater management plan for a basaltic terrain.

  4. Development of a novel optimization tool for electron linacs inspired by artificial intelligence techniques in video games

    Energy Technology Data Exchange (ETDEWEB)

    Meier, E., E-mail: evelyne.meier@synchrotron.org.a [School of Physics, Monash University, Wellington Rd, Clayton VIC 3800 (Australia) and Australian Synchrotron, 800 Blackburn Rd, Clayton VIC 3168 (Australia) and FERMI-Elettra, Sincrotrone Trieste, S.S. 14 km 163.5 in AREA Science Park, 34012 Basovizza, Trieste (Italy); Biedron, S.G., E-mail: biedron@anl.go [Department of Defense Project Office, Argonne National Laboratory, IL 60439 (United States); FERMI-Elettra, Sincrotrone Trieste, S.S. 14 km 163.5 in AREA Science Park, 34012 Basovizza, Trieste (Italy); LeBlanc, G., E-mail: greg.leblanc@synchrotron.org.a [Australian Synchrotron, 800 Blackburn Rd, Clayton VIC 3168 (Australia); Morgan, M.J., E-mail: Michael.J.Morgan@monash.ed [School of Physics, Monash University, Wellington Rd, Clayton VIC 3800 (Australia)

    2011-03-11

    This paper reports the results of an advanced algorithm for the optimization of electron beam parameters in Free Electron Laser (FEL) Linacs. In the novel approach presented in this paper, the system uses state of the art developments in video games to mimic an operator's decisions to perform an optimization task when no prior knowledge, other than constraints on the actuators is available. The system was tested for the simultaneous optimization of the energy spread and the transmission of the Australian Synchrotron Linac. The proposed system successfully increased the transmission of the machine from 90% to 97% and decreased the energy spread of the beam from 1.04% to 0.91%. Results of a control experiment performed at the new FERMI-Elettra FEL is also reported, suggesting the adaptability of the scheme for beam-based control.

  5. Development of a novel optimization tool for electron linacs inspired by artificial intelligence techniques in video games

    Science.gov (United States)

    Meier, E.; Biedron, S. G.; LeBlanc, G.; Morgan, M. J.

    2011-03-01

    This paper reports the results of an advanced algorithm for the optimization of electron beam parameters in Free Electron Laser (FEL) Linacs. In the novel approach presented in this paper, the system uses state of the art developments in video games to mimic an operator's decisions to perform an optimization task when no prior knowledge, other than constraints on the actuators is available. The system was tested for the simultaneous optimization of the energy spread and the transmission of the Australian Synchrotron Linac. The proposed system successfully increased the transmission of the machine from 90% to 97% and decreased the energy spread of the beam from 1.04% to 0.91%. Results of a control experiment performed at the new FERMI@Elettra FEL is also reported, suggesting the adaptability of the scheme for beam-based control.

  6. Tight glycemic control using an artificial endocrine pancreas may play an important role in preventing infection after pancreatic resection

    Institute of Scientific and Technical Information of China (English)

    Kazuhiro Hanazaki

    2012-01-01

    It is well known that perioperative hyperglycemia is the main cause of infectious complications after surgery.To improve perioperative glycemic control,we wish to highlight and comment on an interesting paper published recently by the Annals of Surgery entitled:"Early postoperative hyperglycemia is associated with postoperative complications after pancreatoduodenectomy (PD)" by Eshuis et al.The authors concluded that early postoperative glucose levels more than 140mg/dL was significantly associated with complications after PD.Since we recommend that perioperative tight glycemic control (TGC) is an effective method to prevent postoperative complications including surgical site infection after distal,proximal,and total pancreatic resection,we support strongly this conclusion drawn in this article.However,if early postoperative glucose control in patients undergoing PD was administrated by conventional method such as sliding scale approach as described in this article,it is difficult to maintain TGC.Therefore,we introduce a novel perioperative glycemic control using an artificial endocrine pancreas against pancreatogenic diabetes after pancreatic resection including PD.

  7. A Real-Time and Closed-Loop Control Algorithm for Cascaded Multilevel Inverter Based on Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    Libing Wang

    2014-01-01

    Full Text Available In order to control the cascaded H-bridges (CHB converter with staircase modulation strategy in a real-time manner, a real-time and closed-loop control algorithm based on artificial neural network (ANN for three-phase CHB converter is proposed in this paper. It costs little computation time and memory. It has two steps. In the first step, hierarchical particle swarm optimizer with time-varying acceleration coefficient (HPSO-TVAC algorithm is employed to minimize the total harmonic distortion (THD and generate the optimal switching angles offline. In the second step, part of optimal switching angles are used to train an ANN and the well-designed ANN can generate optimal switching angles in a real-time manner. Compared with previous real-time algorithm, the proposed algorithm is suitable for a wider range of modulation index and results in a smaller THD and a lower calculation time. Furthermore, the well-designed ANN is embedded into a closed-loop control algorithm for CHB converter with variable direct voltage (DC sources. Simulation results demonstrate that the proposed closed-loop control algorithm is able to quickly stabilize load voltage and minimize the line current’s THD (<5% when subjecting the DC sources disturbance or load disturbance. In real design stage, a switching angle pulse generation scheme is proposed and experiment results verify its correctness.

  8. A Fast Adaptive Artificial Neural Network Controller for Flexible Link Manipulators

    OpenAIRE

    Amin Riad Maouche; Hosna Meddahi

    2016-01-01

    This paper describes a hybrid approach to the problem of controlling flexible link manipulators in the dynamic phase of the trajectory. A flexible beam/arm is an appealing option for civil and military applications, such as space-based robot manipulators. However, flexibility brings with it unwanted oscillations and severe chattering which may even lead to an unstable system. To tackle these challenges, a novel control architecture scheme is presented. First, a neural network controller based...

  9. Quality control of the sheep bacterial artificial chromosome library, CHORI-243

    Directory of Open Access Journals (Sweden)

    Kirkness Ewen F

    2010-12-01

    Full Text Available Abstract Background The sheep CHORI-243 bacterial artificial chromosome (BAC library is being used in the construction of the virtual sheep genome, the sequencing and construction of the actual sheep genome assembly and as a source of DNA for regions of the genome of biological interest. The objective of our study is to assess the integrity of the clones and plates which make up the CHORI-243 library using the virtual sheep genome. Findings A series of analyses were undertaken based on the mapping the sheep BAC-end sequences (BESs to the virtual sheep genome. Overall, very few plate specific biases were identified, with only three of the 528 plates in the library significantly affected. The analysis of the number of tail-to-tail (concordant BACs on the plates identified a number of plates with lower than average numbers of such BACs. For plates 198 and 213 a partial swap of the BESs determined with one of the two primers appear to have occurred. A third plate, 341, also with a significant deficit in tail-to-tail BACs, appeared to contain a substantial number of sequences determined from contaminating eubacterial 16 S rRNA DNA. Additionally a small number of eubacterial 16 S rRNA DNA sequences were present on two other plates, 111 and 338, in the library. Conclusions The comparative genomic approach can be used to assess BAC library integrity in the absence of fingerprinting. The sequences of the sheep CHORI-243 library BACs have high integrity, especially with the corrections detailed above. The library represents a high quality resource for use by the sheep genomics community.

  10. Artificial intelligence programming with LabVIEW: genetic algorithms for instrumentation control and optimization.

    Science.gov (United States)

    Moore, J H

    1995-06-01

    A genetic algorithm for instrumentation control and optimization was developed using the LabVIEW graphical programming environment. The usefulness of this methodology for the optimization of a closed loop control instrument is demonstrated with minimal complexity and the programming is presented in detail to facilitate its adaptation to other LabVIEW applications. Closed loop control instruments have variety of applications in the biomedical sciences including the regulation of physiological processes such as blood pressure. The program presented here should provide a useful starting point for those wishing to incorporate genetic algorithm approaches to LabVIEW mediated optimization of closed loop control instruments.

  11. Artificial Diets for Mosquitoes

    Directory of Open Access Journals (Sweden)

    Kristina K. Gonzales

    2016-12-01

    Full Text Available Mosquito-borne diseases are responsible for more than a million human deaths every year. Modern mosquito control strategies such as sterile insect technique (SIT, release of insects carrying a dominant lethal (RIDL, population replacement strategies (PR, and Wolbachia-based strategies require the rearing of large numbers of mosquitoes in culture for continuous release over an extended period of time. Anautogenous mosquitoes require essential nutrients for egg production, which they obtain through the acquisition and digestion of a protein-rich blood meal. Therefore, mosquito mass production in laboratories and other facilities relies on vertebrate blood from live animal hosts. However, vertebrate blood is expensive to acquire and hard to store for longer times especially under field conditions. This review discusses older and recent studies that were aimed at the development of artificial diets for mosquitoes in order to replace vertebrate blood.

  12. Performance Enhancement of PID Controllers by Modern Optimization Techniques for Speed Control of PMBL DC Motor

    Directory of Open Access Journals (Sweden)

    M. Antony Freeda Rani

    2015-08-01

    Full Text Available Permanent Magnet Brushless DC motor (PMBL DC is used in a large number of industrial and automotive applications because of their high efficiency, compactness and excellent reliability. However to design an efficient PMBL DC motor, it is necessary to provide an effective controller that has to reduce the overshoot, settling and rise time. In this study, an improved PID controller has been designed by optimizing the parameters of PID controller based on two advanced optimization techniques ANFIS and Cuckoo Search optimization for speed control of a PMBL DC motor. The proposed approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency. The PMBL DC motor is modeled in SIMULINK implementing the algorithms in MATLAB and the performance evaluation has been studied.

  13. Perioperative glycemic control using an artificial endocrine pancreas in patients undergoing total pancreatectomy: tight glycemic control may be justified in order to avoid brittle diabetes.

    Science.gov (United States)

    Hanazaki, Kazuhiro; Yatabe, Tomoaki; Kobayashi, Masaki; Tsukamoto, Yuuki; Kinoshita, Yoshihiko; Munekage, Masaya; Kitagawa, Hiroyuki

    2013-01-01

    I dedicate this paper to the late Prof. Yukihiko Nosé with all my heart. In 2001, under the direction of Prof. Nosé and Prof. Brunicardi at Baylor College of Medicine, we published a review article entitled "Artificial endocrine pancreas" in JACS. Subsequently, we reported that perioperative tight glycemic control (TGC) using an artificial pancreas (AP) with a closed-loop system could stably maintain near-normoglycemia in total-pancreatectomized dogs. Based on this experimental study in Houston, since 2006, we have introduced perioperative TGC using an AP into clinical use in Kochi. As of 2011, this novel TGC method has provided safe and stable blood glucose levels in more than 400 surgical patients. In this paper, we report new clinical findings regarding perioperative TGC using an AP in total-pancreatectomized patients. TGC using an AP enables us to achieve stable glycemic control not only without hypoglycemia and hyperglycemia but also with less variation in blood glucose concentration from the target blood glucose range, even in patients with the most serious form of diabetes, so-called "brittle diabetes", undergoing total pancreatectomy. To the best of our knowledge, this is the first clinical report of TGC using an AP in patients undergoing total pancreatic resection.

  14. A Fast Adaptive Artificial Neural Network Controller for Flexible Link Manipulators

    Directory of Open Access Journals (Sweden)

    Amin Riad Maouche

    2016-01-01

    Full Text Available This paper describes a hybrid approach to the problem of controlling flexible link manipulators in the dynamic phase of the trajectory. A flexible beam/arm is an appealing option for civil and military applications, such as space-based robot manipulators. However, flexibility brings with it unwanted oscillations and severe chattering which may even lead to an unstable system. To tackle these challenges, a novel control architecture scheme is presented. First, a neural network controller based on the robot’s dynamic equation of motion is elaborated. Its aim is to produce a fast and stable control of the joint position and velocity and damp the vibration of each arm. Then, an adaptive Cerebellar Model Articulation Controller (CMAC is implemented to balance unmodeled dynamics, enhancing the precision of the control. Efficiency of the new controller obtained is tested on a two-link flexible manipulator. Simulation results on a dynamic trajectory with a sinusoidal form show the effectiveness of the proposed control strategy.

  15. Integrating sampling techniques and inverse virtual screening: toward the discovery of artificial peptide-based receptors for ligands.

    Science.gov (United States)

    Pérez, Germán M; Salomón, Luis A; Montero-Cabrera, Luis A; de la Vega, José M García; Mascini, Marcello

    2016-05-01

    A novel heuristic using an iterative select-and-purge strategy is proposed. It combines statistical techniques for sampling and classification by rigid molecular docking through an inverse virtual screening scheme. This approach aims to the de novo discovery of short peptides that may act as docking receptors for small target molecules when there are no data available about known association complexes between them. The algorithm performs an unbiased stochastic exploration of the sample space, acting as a binary classifier when analyzing the entire peptides population. It uses a novel and effective criterion for weighting the likelihood of a given peptide to form an association complex with a particular ligand molecule based on amino acid sequences. The exploratory analysis relies on chemical information of peptides composition, sequence patterns, and association free energies (docking scores) in order to converge to those peptides forming the association complexes with higher affinities. Statistical estimations support these results providing an association probability by improving predictions accuracy even in cases where only a fraction of all possible combinations are sampled. False positives/false negatives ratio was also improved with this method. A simple rigid-body docking approach together with the proper information about amino acid sequences was used. The methodology was applied in a retrospective docking study to all 8000 possible tripeptide combinations using the 20 natural amino acids, screened against a training set of 77 different ligands with diverse functional groups. Afterward, all tripeptides were screened against a test set of 82 ligands, also containing different functional groups. Results show that our integrated methodology is capable of finding a representative group of the top-scoring tripeptides. The associated probability of identifying the best receptor or a group of the top-ranked receptors is more than double and about 10 times higher

  16. Induction motor control and speed estimation via adaptive and artificial intelligence method

    OpenAIRE

    Kamenko, Ilija; Nikolić, Perica; Matić, Dragan; Bugarski, Vladimir

    2011-01-01

    This paper shows the optimization of the parameters of PI controllers in the application of vector control of a three-phase induction motor by genetic algorithm for the set optimality criterion. There is also the projecting procedure as well as the comparative analysis of the performances of speed estimator based on MRAS observer and speed estimator based on ANN. The basis of the research is a mathematical model of vector control of a three-phase induction motor, which was developed in MATLAB...

  17. Integrated control of sun shades, daylight and artificial light; Integreret regulering af solafskaermning, dagslys og kunstlys

    Energy Technology Data Exchange (ETDEWEB)

    Johnsen, K.; Christoffersen, J.; Soerensen, Henrik; Jessen, G.

    2011-07-01

    The project established a basis of calculation and a practical basis for optimum choice of solar shading and integrated control strategies for both new buildings and for office, commercial and institutional buildings to be renovated with new calculation models for controlling solar shading integrated in the BSim program. A complete and applicable model for optimum, integrated solar shading control was established, focusing on thermal and visual comfort criteria towards energy consumption for heating, cooling and lighting. A prototype was tested in the daylight laboratory at Danish Building Research Institute-Aalborg University and at University of Southern Denmark. (LN)

  18. Visión artificial aplicada al control de la calidad

    OpenAIRE

    GARCÍA FUENTES, JORGE; NAVALÓN DAVÓ, ABRAHAM; Jordà Reolid, Antoni; Juárez Varón, David

    2014-01-01

    [EN] In the last years production systems have significantly evolved by seeking to maximize productivity. All new philosophies and manufacturing techniques are among its main targets to maximize quality, a key factor for improving competitiveness. In this article the main systems of vision quality processes are discussed, focusing on three key areas: textile industry, food industry and medical applications; analyzing current applications, seeking the advantages and disadvantages obtained. ...

  19. Tuning fractional PID controllers for a Steward platform based on frequency domain and artificial intelligence methods

    Science.gov (United States)

    Copot, Cosmin; Zhong, Yu; Ionescu, Clara; Keyser, Robin

    2013-06-01

    In this paper, two methods to tune a fractional-order PI λ D μ controller for a mechatronic system are presented. The first method is based on a genetic algorithm to obtain the parameter values for the fractionalorder PI λ D μ controller by global optimization. The second method used to design the fractional-order PI λ D μ controller relies on an auto-tuning approach by meeting some specifications in the frequency domain. The real-time experiments are conducted using a Steward platform which consists of a table tilted by six servo-motors with a ball on the top of the table. The considered system is a 6 degrees of freedom (d.o.f.) motion platform. The feedback on the position of the ball is obtained from images acquired by a visual sensor mounted above the platform. The fractional-order controllers were implemented and the performances of the steward platform are analyzed.

  20. Application of Adaptive Techniques to Problems in Control and Communication.

    Science.gov (United States)

    1982-01-01

    IEEE Transactions on Automatic Control in 1982. (2...signals in the adaptive system. These results will appear in the IEEE Transactions on Automatic Control . A brief comparison of the two schemes described...Model Reference Adaptive Control in the Presence of Bounded Disturbances" S&IS Report No. 8103, March 1981 (to appear in IEEE Transactions on Automatic Control )

  1. An Experimental Study on Direct Load Control of Residential Air-conditioning Units from a Viewpoint of Short-period Controllability in Artificial Climate Chamber

    Science.gov (United States)

    Sugihara, Hideharu; Funaki, Tsuyoshi; Ueno, Kiyotaka

    Recently, much attention in Japan has been given to photovoltaic (PV) systems, which are being rapidly installed in ever greater numbers on homes. However, various concerns over potential adverse implications on the secure operation of the power systems that could result from large-scale installation of PV systems have been identified, such as large-scale PV causing frequency variations or causing voltage variations in distribution networks. This study presents findings on performing direct load control in an artificial climate chamber capable of constant outside air temperature control, and focuses on the potential for using load-variable residential Air-Conditioning (AC) units in order to promote the large-scale introduction of PV. Specifically, measurements were taken of power consumption, room temperature, suction air temperature, and blow air temperature while altering inside air temperature over several minute intervals, and the power consumption variability of AC unit was assessed, while also evaluating the effects on thermal comfort index inside the room.

  2. Volcanic Monitoring Techniques Applied to Controlled Fragmentation Experiments

    Science.gov (United States)

    Kueppers, U.; Alatorre-Ibarguengoitia, M. A.; Hort, M. K.; Kremers, S.; Meier, K.; Scharff, L.; Scheu, B.; Taddeucci, J.; Dingwell, D. B.

    2010-12-01

    Volcanic eruptions are an inevitable natural threat. The range of eruptive styles is large and short term fluctuations of explosivity or vent position pose a large risk that is not necessarily confined to the immediate vicinity of a volcano. Explosive eruptions rather may also affect aviation, infrastructure and climate, regionally as well as globally. Multiparameter monitoring networks are deployed on many active volcanoes to record signs of magmatic processes and help elucidate the secrets of volcanic phenomena. However, our mechanistic understanding of many processes hiding in recorded signals is still poor. As a direct consequence, a solid interpretation of the state of a volcano is still a challenge. In an attempt to bridge this gap, we combined volcanic monitoring and experimental volcanology. We performed 15 well-monitored, field-based, experiments and fragmented natural rock samples from Colima volcano (Mexico) by rapid decompression. We used cylindrical samples of 60 mm height and 25 mm and 60 mm diameter, respectively, and 25 and 35 vol.% open porosity. The applied pressure range was from 4 to 18 MPa. Using different experimental set-ups, the pressurised volume above the samples ranged from 60 - 170 cm3. The experiments were performed at ambient conditions and at controlled sample porosity and size, confinement geometry, and applied pressure. The experiments have been thoroughly monitored with 1) Doppler Radar (DR), 2) high-speed and high-definition cameras, 3) acoustic and infrasound sensors, 4) pressure transducers, and 5) electrically conducting wires. Our aim was to check for common results achieved by the different approaches and, if so, calibrate state-of-the-art monitoring tools. We present how the velocity of the ejected pyroclasts was measured by and evaluated for the different approaches and how it was affected by the experimental conditions and sample characteristics. We show that all deployed instruments successfully measured the pyroclast

  3. 78 FR 34306 - Approval and Promulgation of Air Quality Implementation Plans: North Carolina; Control Techniques...

    Science.gov (United States)

    2013-06-07

    ... nonattainment area. List of Subjects in 40 CFR Part 52 Environmental protection, Air pollution control... AGENCY 40 CFR Part 52 Approval and Promulgation of Air Quality Implementation Plans: North Carolina; Control Techniques Guidelines and Reasonably Available Control Technology AGENCY: Environmental...

  4. Object-Oriented Control System Design Using On-Line Training of Artificial Neural Networks

    Science.gov (United States)

    Rubaai, Ahmed

    1997-01-01

    This report deals with the object-oriented model development of a neuro-controller design for permanent magnet (PM) dc motor drives. The system under study is described as a collection of interacting objects. Each object module describes the object behaviors, called methods. The characteristics of the object are included in its variables. The knowledge of the object exists within its variables, and the performance is determined by its methods. This structure maps well to the real world objects that comprise the system being modeled. A dynamic learning architecture that possesses the capabilities of simultaneous on-line identification and control is incorporated to enforce constraints on connections and control the dynamics of the motor. The control action is implemented "on-line", in "real time" in such a way that the predicted trajectory follows a specified reference model. A design example of controlling a PM dc motor drive on-line shows the effectiveness of the design tool. This will therefore be very useful in aerospace applications. It is expected to provide an innovative and noval software model for the rocket engine numerical simulator executive.

  5. Control of a Uniform Step Asymmetrical 9-Level Inverter Based on Artificial Neural Network Strategy

    Directory of Open Access Journals (Sweden)

    Rachid Taleb

    2009-12-01

    Full Text Available A neural implementation of a harmonic elimination strategy for the control auniform step asymmetrical 9-level inverter is proposed and described in this paper. AMulti-Layer Perceptrons (MLP neural network is used to approximate the mappingbetween the modulation rate and the required switching angles. After learning, the neuralnetwork generates the appropriate switching angles for the inverter. This leads to a lowcomputational-cost neural controller which is therefore well suited for real-timeapplications. This neural approach is compared to the well-known Multi-Carrier Pulse-Width Modulation (MCPWM. Simulation results demonstrate the technical advantages ofthe neural implementation of the harmonic elimination strategy over the conventionalmethod for the control of an uniform step asymmetrical 9-level inverter. The approach isused to supply an asynchronous machine and results show that the neural method ensures ahighest quality torque by efficiently canceling the harmonics generated by the inverter.

  6. Adaptive control in an artificial pancreas for people with type 1 diabetes

    DEFF Research Database (Denmark)

    Boiroux, Dimitri; Duun-Henriksen, Anne Katrine; Schmidt, Signe;

    2017-01-01

    In this paper, we discuss overnight blood glucose stabilization in patients with type 1 diabetes using a Model Predictive Controller (MPC). We compute the model parameters in the MPC using a simple and systematic method based on a priori available patient information. We describe and compare 3...... control strategies using a virtual clinic of 100 randomly generated patients with a representative inter-subject variability. This virtual clinic is based on the Hovorka model. We consider the case where only half of the meal bolus is administered at mealtime, and the case where the insulin sensitivity...

  7. The need for artificial intelligence as an aid in controlling a manufacturing operation

    Science.gov (United States)

    Weyand, J.

    AI applications to industrial production and planning are discussed and illustrated with diagrams and drawings. Applications examined include flexible automation of manufacturing processes (robots with open manual control, robots programmable to meet product specifications, self-regulated robots, and robots capable of learning), flexible fault detection and diagnostics, production control, and overall planning and management (product strategies, marketing, determination of development capacity, site selection, project organization, and technology investment strategies). For the case of robots, problems in the design and operation of a state-of-the-art machine-tool cell (for hole boring, milling, and joining) are analyzed in detail.

  8. Advanced solutions in power systems HVDC, facts, and artificial intelligence

    CERN Document Server

    Liu, Chen-Ching; Edris, Abdel-Aty

    2016-01-01

    Provides insight on both classical means and new trends in the application of power electronic and artificial intelligence techniques in power system operation and control This book presents advanced solutions for power system controllability improvement, transmission capability enhancement and operation planning. The book is organized into three parts. The first part describes the CSC-HVDC and VSC-HVDC technologies, the second part presents the FACTS devices, and the third part refers to the artificial intelligence techniques. All technologies and tools approached in this book are essential for power system development to comply with the smart grid requirements.

  9. Zinc finger artificial transcription factor-based nearest inactive analogue/nearest active analogue strategy used for the identification of plant genes controlling homologous recombination

    NARCIS (Netherlands)

    Jia, Qi; van Verk, Marcel C.; Pinas, Johan E.; Lindhout, Beatrice I.; Hooykaas, Paul J.J.; Van der Zaal, Bert J.

    2013-01-01

    In previous work, we selected a particular transcription factor, designated VP16-HRU, from a pool of zinc finger artificial transcription factors (ZF-ATFs) used for genome interrogation. When expressed in Arabidopsis thaliana under control of the ribosomal protein S5A promoter, the RPS5A::VP16-HRU c

  10. vitisFlower®: Development and Testing of a Novel Android-Smartphone Application for Assessing the Number of Grapevine Flowers per Inflorescence Using Artificial Vision Techniques

    Science.gov (United States)

    Aquino, Arturo; Millan, Borja; Gaston, Daniel; Diago, María-Paz; Tardaguila, Javier

    2015-01-01

    Grapevine flowering and fruit set greatly determine crop yield. This paper presents a new smartphone application for automatically counting, non-invasively and directly in the vineyard, the flower number in grapevine inflorescence photos by implementing artificial vision techniques. The application, called vitisFlower®, firstly guides the user to appropriately take an inflorescence photo using the smartphone’s camera. Then, by means of image analysis, the flowers in the image are detected and counted. vitisFlower® has been developed for Android devices and uses the OpenCV libraries to maximize computational efficiency. The application was tested on 140 inflorescence images of 11 grapevine varieties taken with two different devices. On average, more than 84% of flowers in the captures were found, with a precision exceeding 94%. Additionally, the application’s efficiency on four different devices covering a wide range of the market’s spectrum was also studied. The results of this benchmarking study showed significant differences among devices, although indicating that the application is efficiently usable even with low-range devices. vitisFlower is one of the first applications for viticulture that is currently freely available on Google Play. PMID:26343664

  11. vitisFlower®: Development and Testing of a Novel Android-Smartphone Application for Assessing the Number of Grapevine Flowers per Inflorescence Using Artificial Vision Techniques.

    Science.gov (United States)

    Aquino, Arturo; Millan, Borja; Gaston, Daniel; Diago, María-Paz; Tardaguila, Javier

    2015-08-28

    Grapevine flowering and fruit set greatly determine crop yield. This paper presents a new smartphone application for automatically counting, non-invasively and directly in the vineyard, the flower number in grapevine inflorescence photos by implementing artificial vision techniques. The application, called vitisFlower(®), firstly guides the user to appropriately take an inflorescence photo using the smartphone's camera. Then, by means of image analysis, the flowers in the image are detected and counted. vitisFlower(®) has been developed for Android devices and uses the OpenCV libraries to maximize computational efficiency. The application was tested on 140 inflorescence images of 11 grapevine varieties taken with two different devices. On average, more than 84% of flowers in the captures were found, with a precision exceeding 94%. Additionally, the application's efficiency on four different devices covering a wide range of the market's spectrum was also studied. The results of this benchmarking study showed significant differences among devices, although indicating that the application is efficiently usable even with low-range devices. vitisFlower is one of the first applications for viticulture that is currently freely available on Google Play.

  12. vitisFlower®: Development and Testing of a Novel Android-Smartphone Application for Assessing the Number of Grapevine Flowers per Inflorescence Using Artificial Vision Techniques

    Directory of Open Access Journals (Sweden)

    Arturo Aquino

    2015-08-01

    Full Text Available Grapevine flowering and fruit set greatly determine crop yield. This paper presents a new smartphone application for automatically counting, non-invasively and directly in the vineyard, the flower number in grapevine inflorescence photos by implementing artificial vision techniques. The application, called vitisFlower®, firstly guides the user to appropriately take an inflorescence photo using the smartphone’s camera. Then, by means of image analysis, the flowers in the image are detected and counted. vitisFlower® has been developed for Android devices and uses the OpenCV libraries to maximize computational efficiency. The application was tested on 140 inflorescence images of 11 grapevine varieties taken with two different devices. On average, more than 84% of flowers in the captures were found, with a precision exceeding 94%. Additionally, the application’s efficiency on four different devices covering a wide range of the market’s spectrum was also studied. The results of this benchmarking study showed significant differences among devices, although indicating that the application is efficiently usable even with low-range devices. vitisFlower is one of the first applications for viticulture that is currently freely available on Google Play.

  13. Artificial neural networks environmental forecasting in comparison with multiple linear regression technique: From heavy metals to organic micropollutants screening in agricultural soils

    Science.gov (United States)

    Bonelli, Maria Grazia; Ferrini, Mauro; Manni, Andrea

    2016-12-01

    The assessment of metals and organic micropollutants contamination in agricultural soils is a difficult challenge due to the extensive area used to collect and analyze a very large number of samples. With Dioxins and dioxin-like PCBs measurement methods and subsequent the treatment of data, the European Community advises the develop low-cost and fast methods allowing routing analysis of a great number of samples, providing rapid measurement of these compounds in the environment, feeds and food. The aim of the present work has been to find a method suitable to describe the relations occurring between organic and inorganic contaminants and use the value of the latter in order to forecast the former. In practice, the use of a metal portable soil analyzer coupled with an efficient statistical procedure enables the required objective to be achieved. Compared to Multiple Linear Regression, the Artificial Neural Networks technique has shown to be an excellent forecasting method, though there is no linear correlation between the variables to be analyzed.

  14. Nonlinear systems techniques for dynamical analysis and control

    CERN Document Server

    Lefeber, Erjen; Arteaga, Ines

    2017-01-01

    This treatment of modern topics related to the control of nonlinear systems is a collection of contributions celebrating the work of Professor Henk Nijmeijer and honoring his 60th birthday. It addresses several topics that have been the core of Professor Nijmeijer’s work, namely: the control of nonlinear systems, geometric control theory, synchronization, coordinated control, convergent systems and the control of underactuated systems. The book presents recent advances in these areas, contributed by leading international researchers in systems and control. In addition to the theoretical questions treated in the text, particular attention is paid to a number of applications including (mobile) robotics, marine vehicles, neural dynamics and mechanical systems generally. This volume provides a broad picture of the analysis and control of nonlinear systems for scientists and engineers with an interest in the interdisciplinary field of systems and control theory. The reader will benefit from the expert participan...

  15. Upper Extremity Artificial Limb Control as an Issue Related to Movement and Mobility in Daily Living

    Science.gov (United States)

    Wallace, Steve; Anderson, David I.; Trujillo, Michael; Weeks, Douglas L.

    2005-01-01

    The 1992 NIH Research Planning Conference on Prosthetic and Orthotic Research for the 21st Century (Childress, 1992) recognized that the field of prosthetics lacks theoretical understanding and empirical studies on learning to control an upper-extremity prosthesis. We have addressed this problem using a novel approach in which persons without…

  16. Artificial and Natural Sensors in FES-assisted Human Movement Control

    NARCIS (Netherlands)

    Veltink, Peter H.; Sinkjaer, Thomas; Baten, Chris T.M.; Bergveld, Piet; Spek, van der Jaap; Haugland, Morten

    1998-01-01

    The availability of small and light micromachined sensors for human use and the demonstration that useful signals can be derived from the natural sensors of the human body have enabled new developments in the area of feedback controlled FES assistance of human movements. This paper presents the need

  17. Signal sampling techniques for data acquisition in process control

    OpenAIRE

    Laan, Marten Derk van der

    1995-01-01

    In computing sytems employed for data acquisition and process control, communication with the controlled processes is mainly taking place via analog signal lines. In this situation, the quality of data acquired by A/D-converters and the generation of analog control signals by D/A-converters is of major importance for the overall performance of a system. ... Zie: Summary

  18. Signal sampling techniques for data acquisition in process control

    NARCIS (Netherlands)

    Laan, Marten Derk van der

    1995-01-01

    In computing sytems employed for data acquisition and process control, communication with the controlled processes is mainly taking place via analog signal lines. In this situation, the quality of data acquired by A/D-converters and the generation of analog control signals by D/A-converters is of ma

  19. Developing an Intelligent Reservoir Flood Control Decision Support System through Integrating Artificial Neural Networks

    Science.gov (United States)

    Chang, L. C.; Kao, I. F.; Tsai, F. H.; Hsu, H. C.; Yang, S. N.; Shen, H. Y.; Chang, F. J.

    2015-12-01

    Typhoons and storms hit Taiwan several times every year and cause serious flood disasters. Because the mountainous terrain and steep landform rapidly accelerate the speed of flood flow, rivers cannot be a stable source of water supply. Reservoirs become one of the most important and effective floodwater storage facilities. However, real-time operation for reservoir flood control is a continuous and instant decision-making process based on rules, laws, meteorological nowcast, in addition to the immediate rainfall and hydrological data. The achievement of reservoir flood control can effectively mitigate flood disasters and store floodwaters for future uses. In this study, we construct an intelligent decision support system for reservoir flood control through integrating different types of neural networks and the above information to solve this problem. This intelligent reservoir flood control decision support system includes three parts: typhoon track classification, flood forecast and adaptive water release models. This study used the self-organizing map (SOM) for typhoon track clustering, nonlinear autoregressive with exogenous inputs (NARX) for multi-step-ahead reservoir inflow prediction, and adaptive neuro-fuzzy inference system (ANFIS) for reservoir flood control. Before typhoons landfall, we can estimate the entire flood hydrogragh of reservoir inflow by using SOM and make a pre-release strategy and real-time reservoir flood operating by using ANFIS. In the meanwhile, NARX can be constantly used real-time five-hour-ahead inflow prediction for providing the newest flood information. The system has been successfully implemented Typhoons Trami (2013), Fitow (2013) and Matmo (2014) in Shihmen Reservoir.

  20. AC electric motors control advanced design techniques and applications

    CERN Document Server

    Giri, Fouad

    2013-01-01

    The complexity of AC motor control lies in the multivariable and nonlinear nature of AC machine dynamics. Recent advancements in control theory now make it possible to deal with long-standing problems in AC motors control. This text expertly draws on these developments to apply a wide range of model-based control designmethods to a variety of AC motors. Contributions from over thirty top researchers explain how modern control design methods can be used to achieve tight speed regulation, optimal energetic efficiency, and operation reliability and safety, by considering online state var

  1. Techniques of artificial intelligence applied to the electric power expansion distribution system planning problem; Tecnicas de inteligencia artificial aplicadas ao problema de planejamento da expansao do sistema de distribuicao de energia eletrica

    Energy Technology Data Exchange (ETDEWEB)

    Froes, Salete Maria

    1996-07-01

    A tool named Constrained Decision Problem (CDP), which is based on Artificial Intelligence and a specific application to Distribution System Planning is described. The CDP allows multiple objective optimization that does not, necessarily, result in a single optimal solution. First, a literature review covers published works related to Artificial Intelligence applications to Electric Power Distribution Systems, emphasizing feeder restoration and reconfiguration. Some concepts related to Artificial Intelligence are described, with particular attention to Planning and to Constrained Decision Problems. Following, an Electric Power System planning model is addressed by using the CDP tool. Some case studies illustrate the Distribution Planning model, which are compared with standard optimization models. Concluding, some comments establishing the possibilities of CDP applications are followed by a view on future developments. (author)

  2. A supervision and control tool based on artificial intelligence for high cell density cultivations

    Directory of Open Access Journals (Sweden)

    A. C. L. Horta

    2014-06-01

    Full Text Available High cell density cultivations of recombinant E. coli have been increasingly used for the production of heterologous proteins. However, it is a challenge to maintain these cultivations within the desired conditions, given that some variables such as dissolved oxygen concentration (DOC and feed flow rate are difficult to control. This paper describes the software SUPERSYS_HCDC, a tool developed to supervise fed-batch cultures of rE. coli with biomass concentrations up to 150 gDCW/L and cell productivities up to 9 gDCW.L-1.h-1. The tool includes automatic control of the DOC by integrated action of the stirrer speed as well as of the air and oxygen flow rates; automatic start-up of the feed flow of fresh medium (system based on a neural network committee; and automatic slowdown of feeding when oxygen consumption exceeds the maximum capacity of the oxygen supply.

  3. [Controlling of artificial blood pumps after total heart replacement - an example of disregulation (author's transl)].

    Science.gov (United States)

    Hennig, E; Affeld, K; Kless, H; Mohnhaupt, A; Mohhaupt, R; Clevert, D; Keibach, H; Krautzberger, W; Kleine, H O; Weidemann, H; Bücherl, E S

    1976-12-01

    This is a report on the special regulation problem of the left blood pump after replacement of the natural heart by incorporated extracorporally driven blood pumps in an animal experiment. The consequence of the peripheral self-regulation on the transporting capacity of the bloodpumps considering the driving pressure and the systemic pressure losses has been investigated. Two possible controlling principles and the respective fields of application are discussed on the example of a lung oedema.

  4. The use of controlled microbial cenoses in producers' link to increase steady functioning of artificial ecosystems

    Science.gov (United States)

    Somova, Lydia; Mikheeva, Galina; Somova, Lydia

    The life support systems (LSS) for long-term missions are to use cycling-recycling systems, including biological recycling. Simple ecosystems include 3 links: producers (plants), consumers (man, animals) and reducers (microorganisms). Microorganisms are substantial component of every link of LSS. Higher plants are the traditional regenerator of air and producer of food. They should be used in many successive generations of their reproduction in LSS. Controlled microbiocenoses can increase productivity of producer's link and protect plants from infections. The goal of this work was development of methodological bases of formation of stable, controlled microbiocenoses, intended for increase of productivity of plants and for obtaining ecologically pure production of plants. Main results of our investigations: 1. Experimental microbiocenoses, has been produced in view of the developed methodology on the basis of natural association of microorganisms by long cultivation on specially developed medium. Dominating groups are bacteria of genera: Lactobacillus, Streptococcus, Leuconostoc, Bifidobacterium, Rhodopseudomonas and yeast of genera: Kluyveromyces, Saccharomyces, Torulopsis. 2. Optimal parameters of microbiocenosis cultivation (t, pH, light exposure, biogenic elements concentrations) were experimentally established. Conditions of cultivation on which domination of different groups of microbiocenosis have been found. 3. It was shown, that processing of seeds of wheat, oats, bulbs and plants Allium cepa L. (an onions) with microbial association raised energy of germination of seeds and bulbs and promoted the increase (on 20-30 %) of growth green biomass and root system of plants in comparison with the control. This work is supported by grant, Yenissey , 07-04-96806

  5. Artificial Sun synchronous frozen orbit control scheme design based on J2 perturbation

    Institute of Scientific and Technical Information of China (English)

    Gong-Bo Wang; Yun-He Meng; Wei Zheng; Guo-Jian Tang

    2011-01-01

    Sun synchronous orbit and frozen orbit formed due to J2 perturbation have very strict constraints on orbital parameters,which have restricted the application a lot.In this paper,several control strategies were illustrated to realize Sun synchronous frozen orbit with arbitrary orbital elements using continuous low-thrust.Firstly,according to mean element method,the averaged rate of change of the orbital elements,originating from disturbing constant accelerations over one orbital period,was derived from Gauss' variation of parameters equations.Then,we proposed that binormal acceleration could be used to realize Sun synchronous orbit,and radial or transverse acceleration could be adopted to eliminate the rotation of the argument of the perigee.Finally,amending methods on the control strategies mentioned above were presented to eliminate the residual secular growth.Simulation results showed that the control strategies illustrated in this paper could realize Sun synchronous frozen orbit with arbitrary orbital elements,and can save much more energy than the schemes presented in previous studies,and have no side effect on other orbital parameters' secular motion.

  6. Effects of Artificial Gravity and Bed Rest on Spatial Orientation and Balance Control

    Science.gov (United States)

    Paloski, William H.; Moore, S. T.; Feiveson, A. H.; Taylor, L. C.

    2007-01-01

    While the vestibular system should be well-adapted to bed rest (a condition it experiences approximately 8/24 hrs each day), questions remain regarding the degree to which repeated exposures to the unusual gravito-inertial force environment of a short-radius centrifuge might affect central processing of vestibular information used in spatial orientation and balance control. Should these functions be impaired by intermittent AG, its feasibility as a counter-measure would be diminished. We, therefore, examined the effects of AG on spatial orientation and balance control in 15 male volunteers before and after 21 days of 6 HDT bed rest (BR). Eight of the subjects were treated with daily 1hr AG exposures (2.5g at the feet; 1.0g at the heart) aboard a short radius (3m) centrifuge, while the other seven served as controls (C). Spatial orientation was assessed by measures of ocular counter-rolling (OCR; rotation of the eye about the line of sight, an otolith-mediated reflex) and subjective visual vertical (SVV; perception of the spatial upright). Both OCR and SVV measurements were made with the subject upright, lying on their left sides, and lying on their right sides. OCR was measured from binocular eye orientation recordings made while the subjects fixated for 10s on a point target directly in front of the face at a distance of 1 m. SVV was assessed by asking subjects (in the dark) to adjust to upright (using a handheld controller) the orientation of a luminous bar randomly perturbed (15) to either side of the vertical meridian. Balance control performance was assessed using a computerized dynamic posturography (CDP) protocol similar to that currently required for all returning crew members. During each session, the subjects completed a combination of trials of sensory organization test (SOT) 2 (eyes closed, fixed platform) and SOT 5 (eyes closed, sway-referenced platform) with and without static and dynamic pitch plane head movements (plus or minus 20 deg., dynamic

  7. Principal Component Analysis Coupled with Artificial Neural Networks—A Combined Technique Classifying Small Molecular Structures Using a Concatenated Spectral Database

    Directory of Open Access Journals (Sweden)

    Mihail Lucian Birsa

    2011-10-01

    Full Text Available In this paper we present several expert systems that predict the class identity of the modeled compounds, based on a preprocessed spectral database. The expert systems were built using Artificial Neural Networks (ANN and are designed to predict if an unknown compound has the toxicological activity of amphetamines (stimulant and hallucinogen, or whether it is a nonamphetamine. In attempts to circumvent the laws controlling drugs of abuse, new chemical structures are very frequently introduced on the black market. They are obtained by slightly modifying the controlled molecular structures by adding or changing substituents at various positions on the banned molecules. As a result, no substance similar to those forming a prohibited class may be used nowadays, even if it has not been specifically listed. Therefore, reliable, fast and accessible systems capable of modeling and then identifying similarities at molecular level, are highly needed for epidemiological, clinical, and forensic purposes. In order to obtain the expert systems, we have preprocessed a concatenated spectral database, representing the GC-FTIR (gas chromatography-Fourier transform infrared spectrometry and GC-MS (gas chromatography-mass spectrometry spectra of 103 forensic compounds. The database was used as input for a Principal Component Analysis (PCA. The scores of the forensic compounds on the main principal components (PCs were then used as inputs for the ANN systems. We have built eight PC-ANN systems (principal component analysis coupled with artificial neural network with a different number of input variables: 15 PCs, 16 PCs, 17 PCs, 18 PCs, 19 PCs, 20 PCs, 21 PCs and 22 PCs. The best expert system was found to be the ANN network built with 18 PCs, which accounts for an explained variance of 77%. This expert system has the best sensitivity (a rate of classification C = 100% and a rate of true positives TP = 100%, as well as a good selectivity (a rate of true negatives TN

  8. Bayesian artificial intelligence

    CERN Document Server

    Korb, Kevin B

    2003-01-01

    As the power of Bayesian techniques has become more fully realized, the field of artificial intelligence has embraced Bayesian methodology and integrated it to the point where an introduction to Bayesian techniques is now a core course in many computer science programs. Unlike other books on the subject, Bayesian Artificial Intelligence keeps mathematical detail to a minimum and covers a broad range of topics. The authors integrate all of Bayesian net technology and learning Bayesian net technology and apply them both to knowledge engineering. They emphasize understanding and intuition but also provide the algorithms and technical background needed for applications. Software, exercises, and solutions are available on the authors' website.

  9. Higher-order techniques for some problems of nonlinear control

    Directory of Open Access Journals (Sweden)

    Sarychev Andrey V.

    2002-01-01

    Full Text Available A natural first step when dealing with a nonlinear problem is an application of some version of linearization principle. This includes the well known linearization principles for controllability, observability and stability and also first-order optimality conditions such as Lagrange multipliers rule or Pontryagin's maximum principle. In many interesting and important problems of nonlinear control the linearization principle fails to provide a solution. In the present paper we provide some examples of how higher-order methods of differential geometric control theory can be used for the study nonlinear control systems in such cases. The presentation includes: nonlinear systems with impulsive and distribution-like inputs; second-order optimality conditions for bang–bang extremals of optimal control problems; methods of high-order averaging for studying stability and stabilization of time-variant control systems.

  10. Fuzzy Technique Tracking Control for Multiple Unmanned Ships

    OpenAIRE

    Ramzi Fraga; Liu Sheng

    2013-01-01

    A Fuzzy logic control law is presented and implemented for trajectory tracking of multiple under actuated autonomous surface vessels. In this study, an individual unmanned ship is used to be the leader that tracks the desired path; other unmanned ships are used to be the followers which track the leader only by using its position. A fuzzy controller was implemented for the ship leader position with a constant velocity; however, the ship follower needed a fuzzy controller for the position and ...

  11. Development of Cooling Process Control Technique in Hot Strip Mill

    Institute of Scientific and Technical Information of China (English)

    HAN Bin; LIU Xiang-hua; WANG Guo-dong; SHE Guang-fu

    2005-01-01

    In order to ensure required mechanical properties of steel strip, various innovations in the cooling process control on the run-out table of a hot strip mill were actively promoted. The recent progress of process mathematical model and the new cooling strategy and equipment were discussed. The computer control system of high performance was introduced. The development trend in cooling process control was given.

  12. Implementation Of The Artificial Neural Networks To Control The Springback Of Metal Sheets

    Science.gov (United States)

    Crina, Axinte

    2007-05-01

    Geometrical inaccuracy of sheet metal parts due to the springback phenomenon is the reason for considerable efforts in tools and process development. Prediction of springback is a key issue to design the tools and control the process parameters in order to obtain close tolerances in the formed parts. The objective of this paper is to use simulation procedure coupled with neural networks method to get the best relation between process parameters and tools geometry in order to minimize the shape deviations of the formed parts related to the target geometry.

  13. Glucose-responsive artificial promoter-mediated insulin gene transfer improves glucose control in diabetic mice

    Institute of Scientific and Technical Information of China (English)

    Jaeseok Han; Eung-Hwi Kim; Woohyuk Choi; Hee-Sook Jun

    2012-01-01

    AIM:To investigate the effect of insulin gene therapy using a glucose-responsive synthetic promoter in type 2 diabetic obese mice.METHODS:We employed a recently developed novel insulin gene therapy strategy using a synthetic promoter that regulates insulin gene expression in the liver in response to blood glucose level changes.We intravenously administered a recombinant adenovirus expressing furin-cleavable rat insulin under the control of the synthetic promoter (rAd-SP-rINSfur) into diabetic Leprdb/db mice.A recombinant adenovirus expressing β-galactosidase under the cytomegalovirus promoter was used as a control (rAd-CMV-βgal).Blood glucose levels and body weights were monitored for 50 d.Glucose and insulin tolerance tests were performed.Immunohistochemical staining was performed to investigate islet morphology and insulin content.RESULTS:Administration of rAd-SP-rINSfur lowered blood glucose levels and normoglycemia was maintained for 50 d,whereas the rAd-CMV-βgal control virus-injected mice remained hyperglycemic.Glucose tolerance tests showed that rAd-SP-rINSfur-treated mice cleared exogenous glucose from the blood more efficiently than control virus-injected mice at 4 wk [area under the curve (AUC):21 508.80 ± 2248.18 vs 62 640.00 ± 5014.28,P < 0.01] and at 6 wk (AUC:29 956.60 ± 1757.33 vs 60 016.60 ± 3794.47,P < 0.01).In addition,insulin sensitivity was also significantly improved in mice treated with rAd-SP-rINSfur compared with rAd-CMV-βgal-treated mice (AUC:9150.17±1007.78 vs 11 994.20 ± 474.40,P < 0.05).The islets from rAd-SP-rINSfur-injected mice appeared to be smaller and to contain a higher concentration of insulin than those from rAd-CMV-βgal-injected mice.CONCLUSION:Based on these results,we suggest that insulin gene therapy might be one therapeutic option for remission of type 2 diabetes.

  14. Neuro-prosthetic interplay. Comment on "Hand synergies: Integration of robotics and neuroscience for understanding the control of biological and artificial hands" by M. Santello et al.

    Science.gov (United States)

    Schieber, Marc H.

    2016-07-01

    Control of the human hand has been both difficult to understand scientifically and difficult to emulate technologically. The article by Santello and colleagues in the current issue of Physics of Life Reviews[1] highlights the accelerating pace of interaction between the neuroscience of controlling body movement and the engineering of robotic hands that can be used either autonomously or as part of a motor neuroprosthesis, an artificial body part that moves under control from a human subject's own nervous system. Motor neuroprostheses typically involve a brain-computer interface (BCI) that takes signals from the subject's nervous system or muscles, interprets those signals through a decoding algorithm, and then applies the resulting output to control the artificial device.

  15. Detection, Deterrence, Docility: Techniques of Control by Surveillance Cameras

    NARCIS (Netherlands)

    Balamir, S.

    2013-01-01

    In spite of the growing omnipresence of surveillance cameras, not much is known by the general public about their background. While many disciplines have scrutinised the techniques and effects of surveillance, the object itself remains somewhat of a mystery. A design typology of surveillance cameras

  16. Analytical techniques and quality control in biomedical trace element research

    DEFF Research Database (Denmark)

    Heydorn, K.

    1994-01-01

    The small number of analytical results in trace element research calls for special methods of quality control. It is shown that when the analytical methods are in statistical control, only small numbers of duplicate or replicate results are needed to ascertain the absence of systematic errors cau...

  17. Design and Comparison Direct Torque Control Techniques for Induction Motors

    DEFF Research Database (Denmark)

    Blaabjerg, Frede; Kazmierkowski, Marian P.; Zelechowski, Marcin

    2005-01-01

    In this paper a comparison of two significant control methods of induction motor are presented. The first one is a classical Direct Torque and Flux Control (DTC) and is compared with a scheme, which uses Space Vector Modulator (DTC-SVM). A comparison in respect to dynamic and steady state...

  18. Linear Control Technique for Anti-Lock Braking System

    Directory of Open Access Journals (Sweden)

    Chankit Jain

    2014-08-01

    Full Text Available Antilock braking systems are used in modern cars to prevent the wheels from locking after brakes are applied. The dynamics of the controller needed for antilock braking system depends on various factors. The vehicle model often is in nonlinear form. Controller needs to provide a controlled torque necessary to maintain optimum value of the wheel slip ratio. The slip ratio is represented in terms of vehicle speed and wheel rotation. In present work first of all system dynamic equations are explained and a slip ratio is expressed in terms of system variables namely vehicle linear velocity and angular velocity of the wheel. By applying a bias braking force system, response is obtained using Simulink models. Using the linear control strategies like PI-type the effectiveness of maintaining desired slip ratio is tested. It is always observed that a steady state error of 10% occurring in all the control system models.

  19. Software factory techniques applied to Process Control at CERN

    CERN Multimedia

    Dutour, MD

    2007-01-01

    The CERN Large Hadron Collider (LHC) requires constant monitoring and control of quantities of parameters to guarantee operational conditions. For this purpose, a methodology called UNICOS (UNIfied Industrial COntrols Systems) has been implemented to standardize the design of process control applications. To further accelerate the development of these applications, we migrated our existing UNICOS tooling suite toward a software factory in charge of assembling project, domain and technical information seamlessly into deployable PLC (Programmable logic Controller) – SCADA (Supervisory Control And Data Acquisition) systems. This software factory delivers consistently high quality by reducing human error and repetitive tasks, and adapts to user specifications in a cost-efficient way. Hence, this production tool is designed to encapsulate and hide the PLC and SCADA target platforms, enabling the experts to focus on the business model rather than specific syntaxes and grammars. Based on industry standard software...

  20. Software factory techniques applied to process control at CERN

    CERN Document Server

    Dutour, Mathias D

    2008-01-01

    The CERN Large Hadron Collider (LHC) requires constant monitoring and control of quantities of parameters to guarantee operational conditions. For this purpose, a methodology called UNICOS (UNIfied Industrial COntrols Systems) has been implemented to standardize the design of process control applications. To further accelerate the development of these applications, we migrated our existing UNICOS tooling suite toward a software factory in charge of assembling project, domain and technical information seamlessly into deployable PLC (Programmable logic Controller) - SCADA (Supervisory Control And Data Acquisition) systems. This software factory delivers consistently high quality by reducing human error and repetitive tasks, and adapts to user specifications in a cost-efficient way. Hence, this production tool is designed to encapsulate and hide the PLC and SCADA target platforms, enabling the experts to focus on the business model rather than specific syntaxes and grammars. Based on industry standard software, ...

  1. Artificial blood

    Directory of Open Access Journals (Sweden)

    Sarkar Suman

    2008-01-01

    Full Text Available Artificial blood is a product made to act as a substitute for red blood cells. While true blood serves many different functions, artificial blood is designed for the sole purpose of transporting oxygen and carbon dioxide throughout the body. Depending on the type of artificial blood, it can be produced in different ways using synthetic production, chemical isolation, or recombinant biochemical technology. Development of the first blood substitutes dates back to the early 1600s, and the search for the ideal blood substitute continues. Various manufacturers have products in clinical trials; however, no truly safe and effective artificial blood product is currently marketed. It is anticipated that when an artificial blood product is available, it will have annual sales of over $7.6 billion in the United States alone.

  2. Artificial blood.

    Science.gov (United States)

    Sarkar, Suman

    2008-07-01

    Artificial blood is a product made to act as a substitute for red blood cells. While true blood serves many different functions, artificial blood is designed for the sole purpose of transporting oxygen and carbon dioxide throughout the body. Depending on the type of artificial blood, it can be produced in different ways using synthetic production, chemical isolation, or recombinant biochemical technology. Development of the first blood substitutes dates back to the early 1600s, and the search for the ideal blood substitute continues. Various manufacturers have products in clinical trials; however, no truly safe and effective artificial blood product is currently marketed. It is anticipated that when an artificial blood product is available, it will have annual sales of over $7.6 billion in the United States alone.

  3. An Artificial Neural Network Modeling for Force Control System of a Robotic Pruning Machine

    Directory of Open Access Journals (Sweden)

    Ali Hashemi

    2014-06-01

    Full Text Available Nowadays, there has been an increasing application of pruning robots for planted forests due to the growing concern on the efficiency and safety issues. Power consumption and working time of agricultural machines have become important issues due to the high value of energy in modern world. In this study, different multi-layer back-propagation networks were utilized for mapping the complex and highly interactive of pruning process parameters and to predict power consumption and cutting time of a force control equipped robotic pruning machine by knowing input parameters such as: rotation speed, stalk diameter, and sensitivity coefficient. Results showed significant effects of all input parameters on output parameters except rotational speed on cutting time. Therefore, for reducing the wear of cutting system, a less rotational speed in every sensitivity coefficient should be selected.

  4. Controlling contagious agalactia in artificial insemination centers for goats and detection of Mycoplasma mycoides subspecies capri in semen.

    Science.gov (United States)

    Gómez-Martín, A; Corrales, J C; Amores, J; Sánchez, A; Contreras, A; Paterna, A; De la Fe, C

    2012-04-01

    Many goat artificial insemination (AI) centers in Spain have adopted new measures to control contagious agalactia (CA). To avoid the introduction of male goats carrying mycoplasma organisms subclinically in their external ear canal (auricular carriers) in these centers, two ear swabs and a blood sample are obtained from all candidate animals for polymerase chain reaction (PCR), culture (swabs) and serologic tests to detect the presence of mycoplasmas. In addition, the semen produced at these centers is routinely cultured and PCR tested also to detect the presence of mycoplasmas. One y after the introduction of this program, we tested 48 ear swabs and 24 blood samples from 24 candidates for admission to these AI Centers. Three of these ear swab samples (3/48, 6.25%) scored positive for the presence of mycoplasmas; Mycoplasma agalactiae (Ma) was detected in two samples and Mycoplasma mycoides subsp. capri (Mmc) in one. All animals were serologically negative for Ma. Also, out of 173 semen samples obtained from 137 admitted animals (2 and 3 samples were obtained in 16 and 10 bucks, respectively), one (1/173, 0.56%) was positive for Mmc. Our findings suggest that ear swab and semen samples are useful tools to control CA at AI Centers. The introduction of this program has also resulted in the first detection of Mmc in semen from a naturally infected goat, confirming the ability of this mycoplasma to colonize the reproductive tract of male goats. These results highlight the need to improve control measures in semen producing centers to minimize the risk of CA transmission.

  5. Welfare aspects of vertebrate pest control and culling: ranking control techniques for humaneness.

    Science.gov (United States)

    Littin, K; Fisher, P; Beausoleil, N J; Sharp, T

    2014-04-01

    The management of vertebrate pests depends on the use of traps, pesticides, repellents and other methods, each of which can cause varying levels of pain and other negative experiences to animals. Vertebrate pest control is essential for managing the impacts of unwanted or over-abundant animals on human and animal health, ecological balance and economic interests. As the need for this management is unlikely to diminish over time, a framework has been developed for assessing the humaneness of each technique by considering their negative impacts on animal welfare so that these can be included in decision-making about the selection of techniques for a specific control operation. This information can also support evidence-based regulations directed at managing such animal welfare impacts. In this paper, the authors discuss this assessment framework, briefly review two assessments conducted using the framework and discuss ways in which Competent Authorities and others can use it and other means to improve animal welfare in vertebrate pest management.

  6. Modeling and Analysis of Mechanical Properties of Aluminium Alloy (A413 Processed through Squeeze Casting Route Using Artificial Neural Network Model and Statistical Technique

    Directory of Open Access Journals (Sweden)

    R. Soundararajan

    2015-01-01

    Full Text Available Artificial Neural Network (ANN approach was used for predicting and analyzing the mechanical properties of A413 aluminum alloy produced by squeeze casting route. The experiments are carried out with different controlled input variables such as squeeze pressure, die preheating temperature, and melt temperature as per Full Factorial Design (FFD. The accounted absolute process variables produce a casting with pore-free and ideal fine grain dendritic structure resulting in good mechanical properties such as hardness, ultimate tensile strength, and yield strength. As a primary objective, a feed forward back propagation ANN model has been developed with different architectures for ensuring the definiteness of the values. The developed model along with its predicted data was in good agreement with the experimental data, inferring the valuable performance of the optimal model. From the work it was ascertained that, for castings produced by squeeze casting route, the ANN is an alternative method for predicting the mechanical properties and appropriate results can be estimated rather than measured, thereby reducing the testing time and cost. As a secondary objective, quantitative and statistical analysis was performed in order to evaluate the effect of process parameters on the mechanical properties of the castings.

  7. Fuzzy Technique Tracking Control for Multiple Unmanned Ships

    Directory of Open Access Journals (Sweden)

    Ramzi Fraga

    2013-01-01

    Full Text Available A Fuzzy logic control law is presented and implemented for trajectory tracking of multiple under actuated autonomous surface vessels. In this study, an individual unmanned ship is used to be the leader that tracks the desired path; other unmanned ships are used to be the followers which track the leader only by using its position. A fuzzy controller was implemented for the ship leader position with a constant velocity; however, the ship follower needed a fuzzy controller for the position and the forward velocity. Simulation results show that the fuzzy method presents an interesting robustness against the environmental disturbances and effective tracking results.

  8. A 21st century technique for food control: Electronic noses

    Energy Technology Data Exchange (ETDEWEB)

    Peris, Miguel, E-mail: mperist@qim.upv.es [Departamento de Quimica, Universidad Politecnica de Valencia, 46071 Valencia (Spain); Escuder-Gilabert, Laura [Departamento de Quimica Analitica, Universitat de Valencia, C/Vicente Andres Estelles s/n, E-46100 Burjasot, Valencia (Spain)

    2009-04-06

    This work examines the main features of modern electronic noses (e-noses) and their most important applications in food control in this new century. The three components of an electronic nose (sample handling system, detection system, and data processing system) are described. Special attention is devoted to the promising mass spectrometry based e-noses, due to their advantages over the more classical gas sensors. Applications described include process monitoring, shelf-life investigation, freshness evaluation, authenticity assessment, as well as other general aspects of the utilization of electronic noses in food control. Finally, some interesting remarks concerning the strengths and weaknesses of electronic noses in food control are also mentioned.

  9. TiO2 as a photocatalyst for control of the aquatic invasive alga, Cladophora, under natural and artificial light

    Science.gov (United States)

    Peller, J.R.; Whitman, R.L.; Griffith, S.; Harris, P.; Peller, C.; Scalzitti, J.

    2007-01-01

    Cladophora, a nuisance and invasive, filamentous algae (Chlorophyta), massively accumulates along the shores of the lower Great Lakes each summer causing great economic damage and compromising recreational opportunity and perhaps public health. In vitro experiments showed that Cladophora samples were physically and biologically degraded when subjected to TiO2-mediated photocatalysis. For the most successful photocatalytic process, TiO2 was immobilized on a glass surface and used in combination with either sunlight or artificial UV light. The loss of vital algal pigments was monitored using UV–vis spectrophotometry, and cell structural changes were determined by microscopic observation. Cladophora, in the presence of TiO2-covered glass beads, experienced a loss of chloroplast pigments after 2 h of UV lamp light irradiation. In a separate experiment, sunlight exposure over 4 days (∼24 h) resulted in the complete oxidative degradation of the green chloroplast pigments, verified by the UV spectra of the algal extracts. These results suggest that TiO2, mobilized on sunlit silicates may be useful in controlling growth and survival of this alga in the Great Lakes, thus mitigating many of the economic, aesthetic ecological impacts of this invasive alga.

  10. Operant conditioning: a minimal components requirement in artificial spiking neurons designed for bio-inspired robot's controller.

    Science.gov (United States)

    Cyr, André; Boukadoum, Mounir; Thériault, Frédéric

    2014-01-01

    In this paper, we investigate the operant conditioning (OC) learning process within a bio-inspired paradigm, using artificial spiking neural networks (ASNN) to act as robot brain controllers. In biological agents, OC results in behavioral changes learned from the consequences of previous actions, based on progressive prediction adjustment from rewarding or punishing signals. In a neurorobotics context, virtual and physical autonomous robots may benefit from a similar learning skill when facing unknown and unsupervised environments. In this work, we demonstrate that a simple invariant micro-circuit can sustain OC in multiple learning scenarios. The motivation for this new OC implementation model stems from the relatively complex alternatives that have been described in the computational literature and recent advances in neurobiology. Our elementary kernel includes only a few crucial neurons, synaptic links and originally from the integration of habituation and spike-timing dependent plasticity as learning rules. Using several tasks of incremental complexity, our results show that a minimal neural component set is sufficient to realize many OC procedures. Hence, with the proposed OC module, designing learning tasks with an ASNN and a bio-inspired robot context leads to simpler neural architectures for achieving complex behaviors.

  11. The application of ANN technique to automatic generation control for multi-area power system

    Energy Technology Data Exchange (ETDEWEB)

    Zeynelgil, H.L.; Demiroren, A.; Sengor, N.S. [Istanbul Technical Univ., Maslak (Turkey). Electrical and Electronic Faculty

    2002-06-01

    This paper presents an application of layered artificial neural network controller (ANN) to study automatic generation control (AGC) problem in a four-area interconnected power system that three areas include steam turbines and the other area includes a hydro turbine. Each area of steam turbine in the system contains the reheat effect non-linearity of the steam turbine and the area of hydro turbine contains upper and lower constraints for generation rate. Only one ANN controller, which controls the inputs of each area in the power system together, is considered. In the study, back propagation-through-time algorithm is used as ANN learning rule. By comparing the results for both cases, the performance of ANN controller is better than conventional controllers. (author)

  12. A Model-Following Technique for Insensitive Aircraft Control Systems.

    Science.gov (United States)

    1981-01-01

    Harvey and Pope(131 and Vinkler[301 compared several different methods in their works, while Shenkar [261 and Ashkenazi[2i extended the most promising...Following for In- sensitive Control works, let us consider the simple, first-order system used by Shenkar [261. The plant is described by x -(1 + Ar)x + u...representative of the methods of Vinkler, Asikenazi, and Shenkar ), and Model Following for Insensitive Control (MrIC). For the LQR design, we assume that our

  13. Study of RSSI Ranging Optimization Techniques by Using Artificial Neural Networks%利用人工神经网络的RSSI测距优化技术研究

    Institute of Scientific and Technical Information of China (English)

    贲伟; 王敬东

    2012-01-01

    Ranging technology based on RSS1 (received signal strength indication) is a distance measurement technique with the features of low cost and low complexity. It is widely used in indoor wireless location. Ranging error is relatively large with the impact of NLOS indoor and multipath transmission. For this reason this paper presents a screening strategy, which successfully combined recursive average filter and Gaussian models. A measuring method of artificial neural network distance has been proposed as well. According to the result of the Experiments, RSSI ranging accuracy and anti-jamming capability have been significantly improved by this method.%基于RSSI(接收信号强度指示)的测距技术是一项低成本和低复杂度的距离测量技术,被广泛应用于基于测距的无线传感器网络的定位技术中.由于室内环境中存在非视距和多径传输的影响,测距误差比较大.针对这个问题,本文提出了一种递推平均滤波和高斯模型相结合的R值筛选策略以及一种利用人工神经网络的距离估计方法.实验表明:通过合理的R值筛选策略和距离估计算法,RSSI测距的精度和抗干扰能力得到了明显的提高.

  14. Review of artificial wetland treatment technique for initial rainwater runoff pollutant removal%人工湿地技术削减雨水初期径流污染负荷研究进展

    Institute of Scientific and Technical Information of China (English)

    钱嫦萍; 陈振楼; 曹承进; 王军

    2011-01-01

    拟从技术特点、技术流程、技术原理、技术参数、技术使用中存在的问题以及技术的应用前景等方面对雨水初期径流污染人工湿地技术进行分析和描述.介绍了该技术在国内和国外的研究现状,并展望了其未来研究方向.以期为我国城市雨水初期径流污染控制工程提供参考依据.%This paper analyzed and described the technical characteristics, technical procedures,technical principles, technical parameters, technical problems and technology prospects in the artificial wetland treatment. The development prospect of the technique at home and abroad was also anticipated. This investigation will provide references for the project of controlling the city black-odor river pollution.

  15. Study on modeling of vehicle dynamic stability and control technique

    Institute of Scientific and Technical Information of China (English)

    GAO Yun-ting; LI Pan-feng

    2012-01-01

    In order to solve the problem of enhancing the vehicle driving stability and safety,which has been the hot question researched by scientific and engineering in the vehicle industry,the new control method was investigated.After the analysis of tire moving characteristics and the vehicle stress analysis,the tire model based on the extension pacejka magic formula which combined longitudinal motion and lateral motion was developed and a nonlinear vehicle dynamical stability model with seven freedoms was made.A new model reference adaptive control project which made the slip angle and yaw rate of vehicle body as the output and feedback variable in adjusting the torque of vehicle body to control the vehicle stability was designed.A simulation model was also built in Matlab/Simulink to evaluate this control project.It was made up of many mathematical subsystem models mainly including the tire model module,the yaw moment calculation module,the center of mass parameter calculation module,tire parameter calculation module of multiple and so forth.The severe lane change simulation result shows that this vehicle model and the model reference adaptive control method have an excellent performance.

  16. GPU-Based Optimal Control Techniques for Resistive Wall Mode Control on DIII-D

    Science.gov (United States)

    Clement, M.; Navratil, G. A.; Hanson, J. M.; Strait, E. J.

    2014-10-01

    The DIII-D tokamak can excite strong, locked or nearly locked kink modes whose rotation frequencies do not evolve quickly and are slow compared to their growth rates. To control such modes, DIII-D plans to implement a Graphical Processing Unit (GPU) based feedback control system in a low-latency architecture based on system developed on the HBT-EP tokamak. Up to 128 local magnetic sensors will be used to extrapolate the state of the rotating kink mode, which will be used by the feedback algorithm to calculate the required currents for the internal and/or external control coils. Offline techniques for resolving the mode structure of the resistive wall mode (RWM) will be presented and compared along with the proposed GPU implementation scheme and potential real-time estimation algorithms for RWM feedback. Work supported by the US Department of Energy under DE-FG02-07ER54917, DE-FG02-04ER54761, and DE-FC02-04ER54698.

  17. Artificial intelligence

    CERN Document Server

    Ennals, J R

    1987-01-01

    Artificial Intelligence: State of the Art Report is a two-part report consisting of the invited papers and the analysis. The editor first gives an introduction to the invited papers before presenting each paper and the analysis, and then concludes with the list of references related to the study. The invited papers explore the various aspects of artificial intelligence. The analysis part assesses the major advances in artificial intelligence and provides a balanced analysis of the state of the art in this field. The Bibliography compiles the most important published material on the subject of

  18. Artificial urushi.

    Science.gov (United States)

    Kobayashi, S; Uyama, H; Ikeda, R

    2001-11-19

    A new concept for the design and laccase-catalyzed preparation of "artificial urushi" from new urushiol analogues is described. The curing proceeded under mild reaction conditions to produce the very hard cross-linked film (artificial urushi) with a high gloss surface. A new cross-linkable polyphenol was synthesized by oxidative polymerization of cardanol, a phenol derivative from cashew-nut-shell liquid, by enzyme-related catalysts. The polyphenol was readily cured to produce the film (also artificial urushi) showing excellent dynamic viscoelasticity.

  19. Heidegger and artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Diaz, G.

    1987-01-01

    The discipline of Artificial Intelligence, in its quest for machine intelligence, showed great promise as long as its areas of application were limited to problems of a scientific and situation neutral nature. The attempts to move beyond these problems to a full simulation of man's intelligence has faltered and slowed it progress, largely because of the inability of Artificial Intelligence to deal with human characteristic, such as feelings, goals, and desires. This dissertation takes the position that an impasse has resulted because Artificial Intelligence has never been properly defined as a science: its objects and methods have never been identified. The following study undertakes to provide such a definition, i.e., the required ground for Artificial Intelligence. The procedure and methods employed in this study are based on Heidegger's philosophy and techniques of analysis as developed in Being and Time. Results of this study show that both the discipline of Artificial Intelligence and the concerns of Heidegger in Being and Time have the same object; fundamental ontology. The application of Heidegger's conclusions concerning fundamental ontology unites the various aspects of Artificial Intelligence and provides the articulation which shows the parts of this discipline and how they are related.

  20. Electromagnetic techniques for industrial plant process measurements and quality control

    Energy Technology Data Exchange (ETDEWEB)

    Bramanti, M. (Consiglio Nazionale delle Ricerche, Pisa (Italy). Ist. di Elaborazione della Informazione)

    1992-04-01

    In recent years, new real time non-destructive measuring techniques have been developed based on the use of miniaturized components capable of generating, amplifying and elaborating microwave signals (within the range of tenths of a volt and hundreds of milliamps). All these techniques for the measurement of typical process parameters or the non-destructive testing of materials are based on the interaction of radiation with the material or system under examination and make use of the most modern types of data acquisition technology. This article surveys the sensors and measuring instruments which make use of electromagnetic radiation to acquire information concerning the properties of an examined material or system based on their interactions with electromagnetic fields. A few applications are illustrated, e.g., the measurement of unburnt coal in power plant fly ash, the measurement of the quantity of solid particles present in fluidized beds and the verification of the properties of dielectric materials. In each case, the optimum degree of resolution of these devices is made evident.

  1. Design of a Fractional Order PID Controller Using Particle Swarm Optimization Technique

    CERN Document Server

    Maiti, Deepyaman; Konar, Amit

    2008-01-01

    Particle Swarm Optimization technique offers optimal or suboptimal solution to multidimensional rough objective functions. In this paper, this optimization technique is used for designing fractional order PID controllers that give better performance than their integer order counterparts. Controller synthesis is based on required peak overshoot and rise time specifications. The characteristic equation is minimized to obtain an optimum set of controller parameters. Results show that this design method can effectively tune the parameters of the fractional order controller.

  2. Cells, Agents, and Support Vectors in Interaction - Modeling Urban Sprawl based on Machine Learning and Artificial Intelligence Techniques in a Post-Industrial Region

    Science.gov (United States)

    Rienow, A.; Menz, G.

    2015-12-01

    Since the beginning of the millennium, artificial intelligence techniques as cellular automata (CA) and multi-agent systems (MAS) have been incorporated into land-system simulations to address the complex challenges of transitions in urban areas as open, dynamic systems. The study presents a hybrid modeling approach for modeling the two antagonistic processes of urban sprawl and urban decline at once. The simulation power of support vector machines (SVM), cellular automata (CA) and multi-agent systems (MAS) are integrated into one modeling framework and applied to the largest agglomeration of Central Europe: the Ruhr. A modified version of SLEUTH (short for Slope, Land-use, Exclusion, Urban, Transport, and Hillshade) functions as the CA component. SLEUTH makes use of historic urban land-use data sets and growth coefficients for the purpose of modeling physical urban expansion. The machine learning algorithm of SVM is applied in order to enhance SLEUTH. Thus, the stochastic variability of the CA is reduced and information about the human and ecological forces driving the local suitability of urban sprawl is incorporated. Subsequently, the supported CA is coupled with the MAS ReHoSh (Residential Mobility and the Housing Market of Shrinking City Systems). The MAS models population patterns, housing prices, and housing demand in shrinking regions based on interactions between household and city agents. Semi-explicit urban weights are introduced as a possibility of modeling from and to the pixel simultaneously. Three scenarios of changing housing preferences reveal the urban development of the region in terms of quantity and location. They reflect the dissemination of sustainable thinking among stakeholders versus the steady dream of owning a house in sub- and exurban areas. Additionally, the outcomes are transferred into a digital petri dish reflecting a synthetic environment with perfect conditions of growth. Hence, the generic growth elements affecting the future

  3. The technique of sand control with expandable screens

    Energy Technology Data Exchange (ETDEWEB)

    Zhao, P. [Petrochina, Liaohe (China). Liaohe Oilfield Co.

    2009-07-01

    Sand production in heavy oil reservoirs can limit the normal production of oil wells. In this study, expandable screens were used as a sand control mechanism by filtering the sand as it entered the wellbore. The screen systems consists of an expandable outer housing, an expandable base pipe and a filtering layer. The screen expands radially through an expandable cone and presses into the casing well. Axial tension is used to shrink the screens radially through a fishing anchor in order to remove them from the well. The lack of a sand ring between the screen and the casing increases the flow area of the oil and reduces flow resistance caused by fine silt blockages. A series of laboratory experiments were conducted to study the expansion and shrinkage properties of the screens. A field test conducted at a well located in the Liaohe oilfield in China demonstrated that good sand control results can be obtained without the need for pump checking. It was concluded that the sand control method is easy to use and provides good sand control results in large open flow areas. 2 refs., 2 tabs., 3 figs.

  4. Observations of artificial satellites

    Directory of Open Access Journals (Sweden)

    A. MAMMANO

    1964-06-01

    Full Text Available The following publication gives the results of photographic
    observations of artificial satellites made at Asiago during the second
    and third year of this programme. The fixed camera technique and that
    with moving film (the latter still in its experimental stage have been used.

  5. Drug-induced sleep endoscopy: conventional versus target controlled infusion techniques--a randomized controlled study.

    Science.gov (United States)

    De Vito, Andrea; Agnoletti, Vanni; Berrettini, Stefano; Piraccini, Emanuele; Criscuolo, Armando; Corso, Ruggero; Campanini, Aldo; Gambale, Giorgio; Vicini, Claudio

    2011-03-01

    Understanding the sites of pharyngeal collapse is mandatory for surgical treatment decision-making in obstructive sleep-apnea-hypopnea syndrome patients. Drug-induced sleep endoscopy (DISE) allows for the direct observation of the upper airway during sedative-induced sleep. In order to re-create snoring and apnea patterns related to a spontaneous sleep situation, the authors used a target-controlled infusion (TCI) sleep endoscopy (DISE-TCI), comparing this technique to conventional DISE, in which sedation was reached by a manual bolus injection. The authors conducted a prospective, randomized, unicenter study. The apneic event observation and its correlation with pharyngeal collapse patterns is the primary endpoint; secondary endpoints are defined as stability and safety of sedation plans of DISE-TCI technique. From January 2009 to June 2009, 40 OSAHS patients were included in the study and randomized allocated in two groups: the bolus injection conventional DISE group and the DISE-TCI group. We recorded the complete apnea event at the oropharynx and hypopharynx levels in 4 patients of the conventional DISE group (20%) and in 17 patients of the DISE-TCI group (85%) (P DISE group because of severe desaturation that resulted from the first bolus of propofol (1 mg/kg) (P = 0.4872 ns). We recorded the instability of the sedation plan in 13 patients from the conventional DISE group (65%) and 1 patient from the DISE-TCI group (5%) (P = 0.0001). Our results suggest that the DISE-TCI technique should be the first choice in performing sleep endoscopy because of its increased accuracy, stability and safety.

  6. Control and switching synchronization of fractional order chaotic systems using active control technique

    KAUST Repository

    Radwan, A.G.

    2013-03-13

    This paper discusses the continuous effect of the fractional order parameter of the Lü system where the system response starts stable, passing by chaotic behavior then reaching periodic response as the fractional-order increases. In addition, this paper presents the concept of synchronization of different fractional order chaotic systems using active control technique. Four different synchronization cases are introduced based on the switching parameters. Also, the static and dynamic synchronizations can be obtained when the switching parameters are functions of time. The nonstandard finite difference method is used for the numerical solution of the fractional order master and slave systems. Many numeric simulations are presented to validate the concept for different fractional order parameters.

  7. Control and switching synchronization of fractional order chaotic systems using active control technique

    Directory of Open Access Journals (Sweden)

    A.G. Radwan

    2014-01-01

    Full Text Available This paper discusses the continuous effect of the fractional order parameter of the Lü system where the system response starts stable, passing by chaotic behavior then reaching periodic response as the fractional-order increases. In addition, this paper presents the concept of synchronization of different fractional order chaotic systems using active control technique. Four different synchronization cases are introduced based on the switching parameters. Also, the static and dynamic synchronizations can be obtained when the switching parameters are functions of time. The nonstandard finite difference method is used for the numerical solution of the fractional order master and slave systems. Many numeric simulations are presented to validate the concept for different fractional order parameters.

  8. AN IMPLEMENTATION OF ADVANCED TRAFFIC CONTROL TECHNIQUES IN MANET

    Directory of Open Access Journals (Sweden)

    Babita

    2012-09-01

    Full Text Available Mobile Ad hoc Networks (MANET has become an exciting and important technology in recent years because of the rapid proliferation of wireless devices. A mobile adhoc network (MANET is a self-configuring network of mobile routers (and associated hosts connected by wireless links - the union of which form an arbitrary topology. Secured ad hoc routing protocols are a necessity forsecuring the routing of data. To have security in the routing, one should sacrifice the performance of the data transmission. This shows that in the secure routing protocols, the usage of security techniques like digital signatures, authentications and hash chains have major impacts on the performance since it will use moreprocessing power and time. Secure routing protocols available today (such as SAODV still need further optimizations to minimize the processing overhead, delays and to maximize the routing throughputs.

  9. Artificial Limbs

    Science.gov (United States)

    ... diabetes. They may cause you to need an amputation. Traumatic injuries, including from traffic accidents and military combat Cancer Birth defects If you are missing an arm or leg, an artificial limb can sometimes replace it. The device, which is ...

  10. Natural - synthetic - artificial!

    DEFF Research Database (Denmark)

    Nielsen, Peter E

    2010-01-01

    The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life.......The terms "natural," "synthetic" and "artificial" are discussed in relation to synthetic and artificial chromosomes and genomes, synthetic and artificial cells and artificial life....

  11. Contribution of semen trait selection, artificial insemination technique, and semen dose to the profitability of pig production systems: A simulation study.

    Science.gov (United States)

    Gonzalez-Pena, Dianelys; Knox, Robert V; Rodriguez-Zas, Sandra L

    2016-01-15

    The economic impact of selection for semen traits on pig production systems and potential interaction with artificial insemination (AI) technique and semen dose remains partially understood. The objectives of this study were to compare the financial indicators (gross return, net profit, cost) in a three-tier pig production system under one of two selection strategies: a traditional strategy including nine paternal and maternal traits (S9) and an advanced strategy that adds four semen traits (S13). Maternal traits included the number of pigs born alive, litter birth weight, adjusted 21-day litter weight, and the number of pigs at 21 days, and paternal traits included days to 113.5 kg, back fat, average daily gain, feed efficiency, and carcass lean percentage. The four semen traits included volume, concentration, progressive motility of spermatozoa, and abnormal spermatozoa. Simultaneously, the impact of two AI techniques and a range of fresh refrigerated semen doses including cervical AI with 3 × 10(9) (CAI3) and 2 × 10(9) (CAI2) sperm cells/dose, and intrauterine AI with 1.5 × 10(9) (IUI1.5), 0.75 × 10(9) (IUI0.75), and 0.5 × 10(9) (IUI0.5) sperm cells/dose were evaluated. These factors were also evaluated using a range of farrowing rates (60%-90%), litter sizes (8-14 live-born pigs), and a selected semen collection frequency. The financial impact of the factors was assessed through simulation of a three-way crossbreeding system (maternal nucleus lines A and B and paternal nucleus line C) using ZPLAN. The highest return on investment (profit/cost) of boars was observed at 2.33 collections/wk (three periods of 24 hours between collections). Under this schedule, a significant (P < 0.0001) interaction between the selection strategy and the AI technique-dose combination was identified for the gross return; meanwhile, significant (P < 0.0001) additive effects of the selection strategy and AI technique-dose combination were observed for the net

  12. Optimal PID control of a brushless DC motor using PSO and BF techniques

    Directory of Open Access Journals (Sweden)

    H.E.A. Ibrahim

    2014-06-01

    Full Text Available This paper presents a Particle Swarm Optimization (PSO technique and bacterial foraging (BF technique for determining the optimal parameters of (PID controller for speed control of a brushless DC motor (BLDC where the (BLDC motor is modeled in simulink in Matlab. The proposed technique was more efficient in improving the step response characteristics as well as reducing the steady-state error, rise time, settling time and maximum overshoot.

  13. Exploration on artificial bored pile construction quality control methods%人工挖孔桩施工质量控制方法探讨

    Institute of Scientific and Technical Information of China (English)

    何文斌

    2015-01-01

    The thesis describes merits and defects of artificial bored pile,and illustrates artificial bored pile construction technology procedures. Starting from three aspects of construction organization design compilation,construction scheme technology discloser and construction examination system compilation,it introduces artificial bored pile construction quality control measures,and puts forward corresponding processing counter-measures to existing construction problems,so as to guarantee artificial bored pile construction quality.%简述了人工挖孔灌注桩的优缺点,概括了人工挖孔桩施工的工艺流程,从施工组织设计的编制、施工方案的技术交底、施工检查制度的制定三方面,介绍了人工挖孔桩施工的质量控制措施,并针对施工中存在的问题,提出了相应的处理对策,确保了人工挖孔桩的施工质量。

  14. Artificial locomotion control

    DEFF Research Database (Denmark)

    Azevedo, Christine; Poignet, Philippe; Espiau, Bernard

    2004-01-01

    through coherent physical inequality constraints. Dynamic model and internal limitations of the system are part of the problem constraints. This work is validated by simulation results obtained for the Bip and Rabbit biped robots in various walking and standing situations and compared to human data...

  15. 人工内分泌系统调节人工神经网络的控制模型%A dynamic control model for modulating using artificial neural networks using the artificial endocrine system

    Institute of Scientific and Technical Information of China (English)

    林广栋; 王煦法

    2012-01-01

    人体的内分泌系统是一个复杂的控制系统,与神经系统、免疫系统一起维持机体的内平衡.受内分泌系统与神经系统的相互作用机制启发,提出一种内分泌系统调节神经网络系统的EMNCS(endocrine modulated neural control system)控制模型.EMNCS模型中,内分泌系统可以根据环境变化动态调节神经网络系统,达到动态控制的目的.把该模型应用于动态环境下的机器人控制系统,实验表明,EMNCS模型能有效提高机器人在动态环境下的适应能力.%The endocrine system in the human body is a complex control system and cooperates with the neural and immune systems to maintain homeostasis. Inspired by the mechanism by which the endocrine system interacts with neural system, an EMNCS (endocrine modulated neural control system) model was proposed in which the artificial endocrine system modulated and artificial neural system. In EMNCS, the endocrine system could modulate the parameters and structures of the neural system in order to achieve dynamic control. The algorithm was applied in the robot system and experimental results show that EMNCS model can improve performance and enhance its adaptability.

  16. Feasibility of Applying Controllable Lubrication Techniques to Reciprocating Machines

    DEFF Research Database (Denmark)

    Pulido, Edgar Estupinan

    modified hydrostatic lubrication. In this case, the hydrostatic lubrication is modified by injecting oil at controllable pressures, through orifices circumferentially located around the bearing surface. In order to study the performance of journal bearings of reciprocating machines, operating under...... conventional lubrication conditions, a mathematical model of a reciprocating mechanism connected to a rigid / flexible rotor via thin fluid films was developed. The mathematical model involves the use of multibody dynamics theory for the modelling of the reciprocating mechanism (rigid bodies), finite elements...... of the reciprocating engine, obtained with the help of multibody dynamics (rigid components) and finite elements method (flexible components), and the global system of equations is numerically solved. The analysis of the results was carried out with focus on the behaviour of the journal orbits, maximum fluid film...

  17. Beaconless adaptive-optics technique for HEL beam control

    Science.gov (United States)

    Khizhnyak, Anatoliy; Markov, Vladimir

    2016-05-01

    Effective performance of forthcoming laser systems capable of power delivery on a distant target requires an adaptive optics system to correct atmospheric perturbations on the laser beam. The turbulence-induced effects are responsible for beam wobbling, wandering, and intensity scintillation, resulting in degradation of the beam quality and power density on the target. Adaptive optics methods are used to compensate for these negative effects. In its turn, operation of the AOS system requires a reference wave that can be generated by the beacon on the target. This report discusses a beaconless approach for wavefront correction with its performance based on the detection of the target-scattered light. Postprocessing of the beacon-generated light field enables retrieval and detailed characterization of the turbulence-perturbed wavefront -data that is essential to control the adaptive optics module of a high-power laser system.

  18. Self Tuning Techniques on PLC Background and Control Systems With Self Tuning Methods Design

    Directory of Open Access Journals (Sweden)

    Jiri Koziorek

    2010-01-01

    Full Text Available Advanced Process Control techniques have become standard functions of distributed control systems. Self tuning methods belong to Advanced Process Control (APC techniques. APC techniques contain software packages for advanced control based on mathematical methods. APC tools are designed to increase the process capacity, yield and quality of products. Most of nowadays digital industry regulators and PLCs are provided with some kind of the self tuning constant algorithm. Practical part of the paper deals with design of the control systems which contain self tuning regulator. A control system with PID Self Tuner by Siemens and with visualization in WinCC is designed. There is a description of an implementation of the PID regulator as a function block which can be also used for extension control functions. Control systems for relay and moment self tuner with visualizations in WinCC are also designed.

  19. HPLC-MS technique for radiopharmaceuticals analysis and quality control

    Science.gov (United States)

    Macášek, F.; Búriová, E.; Brúder, P.; Vera-Ruiz, H.

    2003-01-01

    Potentialities of liquid chromatography with mass spectrometric detector (MSD) were investigated with the objective of quality control of radiopharmaceuticals; 2-deoxy-2-[18F]fluoro-D-glucose (FDG) being an example. Screening of suitable MSD analytical lines is presented. Mass-spectrometric monitoring of acetonitrile— aqueous ammonium formate eluant by negatively charged FDG.HCO2 - ions enables isotope analysis (specific activity) of the radiopharmaceutical at m/z 227 and 226. Kryptofix® 222 provides an intense MSD signal of the positive ion associated with NH4 + at m/z 394. Expired FDG injection samples contain decomposition products from which at least one labelled by 18F and characterised by signal of negative ions at m/z 207 does not correspond to FDG fragments but to C5 decomposition products. A glucose chromatographic peak, characterised by m/z 225 negative ion is accompanied by a tail of a component giving a signal of m/z 227, which can belong to [18O]glucose; isobaric sorbitol signals were excluded but FDG-glucose association occurs in the co-elution of separation of model mixtures. The latter can actually lead to a convoluted chromatographic peak, but the absence of 18F makes this inconsistent. Quantification and validation of the FDG component analysis is under way.

  20. Speed Control of DC Motor using AC/AC/DC Converter Based on Intelligent Techniques

    Directory of Open Access Journals (Sweden)

    Rakan Kh Antar

    2013-05-01

    Full Text Available    This paper describes the application of ac/ac/dc and ac/dc converters to control the speed of a separately excited DC motor. Artificial neural network and PI controller are trained to select the desired values of firing angles for triggering thyristors of the ac/ac/dc and ac/dc bridge converters in order to control the speed of the dc motor at a desired value with constant and different load torques in order to obtain the best speed response. Simulation results show that the rising time for ac/dc and ac/ac/dc converters at 250rpm are reduced about 79% and 89% respectively, while delay time it reduced about 69% and 64% respectively. Therefore, speed response of the dc motor is more efficient for closed loop system compared with open loop also the response of ac/ac/dc converter is better than ac/dc converter.

  1. Modeling and adaptive control of a camless engine using neural networks and estimation techniques

    Energy Technology Data Exchange (ETDEWEB)

    Ashhab, S. [Hashemite Univ., Zarqa (Jordan). Dept. of Mechanical Engineering

    2007-08-09

    A system to control the cylinder air charge (CAC) in a camless internal combustion (IC) engine was recently developed. The performance of an IC engine connected to an adaptive artificial neural network (ANN) based feedback controller was then investigated. A control oriented model for the engine intake process was created based on thermodynamics laws and was validated against engine experimental data. Input-output data at a speed of 1500 RPM was generated and used to train an ANN model for the engine. The inputs were the intake valve lift (IVL) and closing timing (IVC). The output was the CAC. The controller consisted of a feedforward controller, CAC estimator, and on-line ANN parameter estimator. The feedforward controller provided IVL and IVC that satisfied the driver's torque demand and was the inverse of the engine ANN model. The on-line ANN used the error between the CAC measurement from the CAC estimator and its predicted value from the ANN to update the network's parameters. The feedforward controller was therefore adapted since its operation depended on the ANN model. The adaptation scheme improved the ANN prediction accuracy when the engine parts degraded, the speed changed or when modeling errors occurred. The engine controller exhibited good CAC tracking performance. Computer simulation demonstrated the capability of the camless engine controller. 17 refs., 5 figs.

  2. Cell-level battery charge/discharge protection system. [electronic control techniques

    Science.gov (United States)

    Donovan, R. L.; Imamura, M. S.

    1977-01-01

    The paper describes three design approaches to individual cell monitoring and control for sealed secondary battery cells. One technique involves a modular strap-on single cell protector which contains all the electronics required for monitoring cell voltage, responding to external commands, and forming a bypass circuit for the cell. A second technique, the multiplexed cell protector, uses common circuitry to monitor and control each cell in a battery pack. The third technique, the computerized cell protector, by replacing the hard-wired logic of the multiplexed cell protector with a microprocessor, achieves greatest control flexibility and inherent computational capability with a minimum parts count implementation.

  3. Experimental evaluation of optimal Vehicle Dynamic Control based on the State Dependent Riccati Equation technique

    NARCIS (Netherlands)

    Alirezaei, M.; Kanarachos, S.A.; Scheepers, B.T.M.; Maurice, J.P.

    2013-01-01

    Development and experimentally evaluation of an optimal Vehicle Dynamic Control (VDC) strategy based on the State Dependent Riccati Equation (SDRE) control technique is presented. The proposed nonlinear controller is based on a nonlinear vehicle model with nonlinear tire characteristics. A novel ext

  4. A randomized controlled, non-inferiority trial of modified natural versus artificial cycle for cryo-thawed embryo transfer

    NARCIS (Netherlands)

    Groenewoud, E. R.; Cohlen, B. J.; Al-Oraiby, A.; Brinkhuis, E. A.; Broekmans, F. J M; De Bruin, J. P.; Van Den Dool, G.; Fleisher, K.; Friederich, J.; Goddijn, M.; Hoek, A.; Hoozemans, D. A.; Kaaijk, E. M.; Koks, C. A M; Laven, J. S E; Van Der Linden, P. J Q; Manger, A. P.; Slappendel, E.; Spinder, T.; Kollen, B. J.; Macklon, N. S.

    2016-01-01

    studyquestion: Are live birth rates (LBRs) after artificial cycle frozen-thawed embryo transfer (AC-FET) non-inferior to LBRs after modified natural cycle frozen-thawed embryo transfer (mNC-FET)? summaryanswer: AC-FET is non-inferior to mNC-FET with regard to LBRs, clinical and ongoing pregnancy rat

  5. Artificial intelligence methods applied in the controlled synthesis of polydimethilsiloxane - poly (methacrylic acid) copolymer networks with imposed properties

    Science.gov (United States)

    Rusu, Teodora; Gogan, Oana Marilena

    2016-05-01

    This paper describes the use of artificial intelligence method in copolymer networks design. In the present study, we pursue a hybrid algorithm composed from two research themes in the genetic design framework: a Kohonen neural network (KNN), path (forward problem) combined with a genetic algorithm path (backward problem). The Tabu Search Method is used to improve the performance of the genetic algorithm path.

  6. Myoelectric control of a computer animated hand: a new concept based on the combined use of a tree-structured artificial neural network and a data glove.

    Science.gov (United States)

    Sebelius, F; Eriksson, L; Balkenius, C; Laurell, T

    2006-01-01

    This paper proposes a new learning set-up in the field of control systems for multifunctional hand prostheses. Two male subjects with a traumatic one-hand amputation performed simultaneous symmetric movements with the healthy and the phantom hand. A data glove on the healthy hand was used as a reference to train the system to perform natural movements. Instead of a physical prosthesis with limited degrees of freedom, a virtual (computer-animated) hand was used as the target tool. Both subjects successfully performed seven different motoric actions with the fingers and wrist. To reduce the training time for the system, a tree-structured, self-organizing, artificial neural network was designed. The training time never exceeded 30 seconds for any of the configurations used, which is three to four times faster than most currently used artificial neural network (ANN) architectures.

  7. Artificial Intelligence

    CERN Document Server

    Warwick, Kevin

    2011-01-01

    if AI is outside your field, or you know something of the subject and would like to know more then Artificial Intelligence: The Basics is a brilliant primer.' - Nick Smith, Engineering and Technology Magazine November 2011 Artificial Intelligence: The Basics is a concise and cutting-edge introduction to the fast moving world of AI. The author Kevin Warwick, a pioneer in the field, examines issues of what it means to be man or machine and looks at advances in robotics which have blurred the boundaries. Topics covered include: how intelligence can be defined whether machines can 'think' sensory

  8. Artificial sweeteners

    DEFF Research Database (Denmark)

    Raben, Anne Birgitte; Richelsen, Bjørn

    2012-01-01

    Artificial sweeteners can be a helpful tool to reduce energy intake and body weight and thereby risk for diabetes and cardiovascular diseases (CVD). Considering the prevailing diabesity (obesity and diabetes) epidemic, this can, therefore, be an important alternative to natural, calorie-containin......Artificial sweeteners can be a helpful tool to reduce energy intake and body weight and thereby risk for diabetes and cardiovascular diseases (CVD). Considering the prevailing diabesity (obesity and diabetes) epidemic, this can, therefore, be an important alternative to natural, calorie...

  9. Selected applications of photothermal and photoluminescence heterodyne techniques for process control in silicon wafer manufacturing

    Science.gov (United States)

    Ehlert, Andreas; Kerstan, Michael; Lundt, Holger; Huber, Anton; Helmreich, Dieter; Geiler, Hans-Dieter; Karge, Harald; Wagner, Matthias

    1997-02-01

    Two noncontact laser-based heterodyne techniques, photothermal heterodyne (PTH) and photoluminescence heterodyne (PLH), are introduced and applied to processing and quality control in silicon wafer manufacturing. The crystallographic characteristics of process-induced defects in silicon wafers are suitable for the application of PTH and PLH techniques, which are demonstrated on selected examples from different steps of silicon wafer production. Both PLH and PTH techniques meet the demand for nondestructive and on-line-suitable measurement in the semiconductor industry.

  10. Adaptive Input-Output Linearization Technique for Robust Speed Control of Brush less DC Motor

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Kyeong Hwa; Baik, In Cheol; Kim, Hyun Soo; Youn, Myung Joong [Korea Advance Institute of Science and Technology, Taejon (Korea, Republic of)

    1997-06-01

    An adaptive input-output linearization technique for a robust speed control of a brush less DC (BLDC) motor is presented. By using this technique, the nonlinear motor model can be effectively linearized in Brunovski canonical form, and the desired speed dynamics can be obtained based on the linearized model. This control technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions caused by the incomplete linearization. For the robust output response, the controller parameters will be estimated by a model reference adaptive technique where the disturbance torque and flux linkage are estimated. The adaptation laws are derived by the Popov`s hyper stability theory and positivity concept. The proposed control scheme is implemented on a BLDC motor using the software of DSP TMS320C30 and the effectiveness is verified through the comparative simulations and experiments. (author). 14 refs., 12 figs., 1 tab.

  11. Tracer Gas Technique Versus a Control Box Method for Estimating Direct Capture Efficiency of Exhaust Systems

    DEFF Research Database (Denmark)

    Madsen, U.; Aubertin, G.; Breum, N. O.;

    Numerical modelling of direct capture efficiency of a local exhaust is used to compare the tracer gas technique of a proposed CEN standard against a more consistent approach based on an imaginary control box. It is concluded that the tracer gas technique is useful for field applications....

  12. Optimizaton of corrosion control for lead in drinking water using computational modeling techniques

    Science.gov (United States)

    Computational modeling techniques have been used to very good effect in the UK in the optimization of corrosion control for lead in drinking water. A “proof-of-concept” project with three US/CA case studies sought to demonstrate that such techniques could work equally well in the...

  13. Robust control of seismic structures using independent modal-space techniques

    Science.gov (United States)

    Martin, Kerry S.; Rao, Vittal S.; Cheng, Franklin Y.

    1996-04-01

    Active robust structural controls have been utilized in the control of aerospace structures for many years but they have only been recently investigated in the context of control for civil engineering structures. The results of an investigation of the utilization of these methods on building-like structures are presented in this paper. The closed-loop systems take into account the limited available actuation force and are inherently insensitive to parameter variations and modeling uncertainties. Independent modal-space control (IMSC) is a structural control technique where the multi-input-multi-output configuration-space system is transformed into a set of uncoupled single-input-single-output modal-space systems. A modal controller is designed for each modal-space system and the set of modal controllers is transformed back into configuration-space. By combining IMSC with robust control techniques such as LQG/LTR or H(infinity ), a robust structural control design technique is proposed in this paper. Robust IMSC techniques are employed for control of seismic structures where a small number of actuators are used to control the first few modes of the structure. We have designed and implemented robust IMSC controllers on an experimental building-like structure. This structure utilizes torque motor driven active tendons as actuators and rests on a shaking table which is capable of providing one dimensional base excitation similar to earthquake ground motion. A three input-three output model of the structure, including the torque motor actuators, was developed using experimental data. The experimental structural identification technique, based on standard modal analysis methods, provides the mathematical model that describes the behavior of the structure. An H(infinity ) based IMSC controller has been designed and implemented on this structure using a dSPACE control development system. The results show that the performance of the system is satisfactory in the presence of

  14. Application of a sensitivity analysis technique to high-order digital flight control systems

    Science.gov (United States)

    Paduano, James D.; Downing, David R.

    1987-01-01

    A sensitivity analysis technique for multiloop flight control systems is studied. This technique uses the scaled singular values of the return difference matrix as a measure of the relative stability of a control system. It then uses the gradients of these singular values with respect to system and controller parameters to judge sensitivity. The sensitivity analysis technique is first reviewed; then it is extended to include digital systems, through the derivation of singular-value gradient equations. Gradients with respect to parameters which do not appear explicitly as control-system matrix elements are also derived, so that high-order systems can be studied. A complete review of the integrated technique is given by way of a simple example: the inverted pendulum problem. The technique is then demonstrated on the X-29 control laws. Results show linear models of real systems can be analyzed by this sensitivity technique, if it is applied with care. A computer program called SVA was written to accomplish the singular-value sensitivity analysis techniques. Thus computational methods and considerations form an integral part of many of the discussions. A user's guide to the program is included. The SVA is a fully public domain program, running on the NASA/Dryden Elxsi computer.

  15. The application of emulation techniques in the analysis of highly reliable, guidance and control computer systems

    Science.gov (United States)

    Migneault, Gerard E.

    1987-01-01

    Emulation techniques can be a solution to a difficulty that arises in the analysis of the reliability of guidance and control computer systems for future commercial aircraft. Described here is the difficulty, the lack of credibility of reliability estimates obtained by analytical modeling techniques. The difficulty is an unavoidable consequence of the following: (1) a reliability requirement so demanding as to make system evaluation by use testing infeasible; (2) a complex system design technique, fault tolerance; (3) system reliability dominated by errors due to flaws in the system definition; and (4) elaborate analytical modeling techniques whose precision outputs are quite sensitive to errors of approximation in their input data. Use of emulation techniques for pseudo-testing systems to evaluate bounds on the parameter values needed for the analytical techniques is then discussed. Finally several examples of the application of emulation techniques are described.

  16. 无丝3D打印技术常温构建仿生人工骨支架的研究%Fabrication of a bionic artificial bone scaffold using a room temperature three dimensional printing technique

    Institute of Scientific and Technical Information of China (English)

    林楷丰; 何树; 宋岳; 王铮; 毕龙; 裴国献

    2016-01-01

    scaffolds was cocultured with bone mesenchymal stem cells (BMSCs) to evaluate the toxicity of scaffolds.There were 3 experimental groups:blank control with no scaffolds,printed scaffolds group and non-printed scaffolds group.The condition of BMSCs on the scaffolds was observed via scanning electron microscopy(SEM) and immunostaining.3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT) assay and SEM were applied to monitor the proliferation of BMSCs on the scaffolds.At last,alkaline phosphatase (ALP) activity and mRNA expression levels of osteogenesis-related genes were detected to assess the osteoinductive property of the scaffolds.Results The 3D printed scaffolds fabricated in the present study were characterized by highly interconnected pores which were controllable and even in size.The cross section of the scaffolds presented an irregular honeycomb-like microstructure.The porosity of printed 3D scaffolds (71.14% ± 2.24%) was significantly higher than that of non-printed scaffolds (59.04% ±2.98%) (P < 0.05).The physico-chemical structures of the materials were preserved after printing without additional cytotoxicity.The MTT results at 7 and 14 days revealed that the printed scaffolds had a significantly more cell numbers than the non-printed scaffolds(P < 0.05).SEM showed that the BMSCs adhered well onto the printed scaffolds and proliferated and migrated through the pores.Compared with the blank control,the printed scaffolds showed obviously better osteogenic outcomes.Conclusion The 3D bionic artificial bone scaffolds of collagen/hydroxyapatite manufactured by a room temperature 3D printing technique can provide a good extracellular matrix for BMSCs to proliferate and differentiate.

  17. Test and numerical simulation of a new type of hybrid control technique

    Institute of Scientific and Technical Information of China (English)

    Meng Qingli; Zhang Minzheng; Cheng Dong

    2005-01-01

    In this paper, a new hybrid control technique, based on a combination of base-isolation and semi-active variable stiffness/damping in a superstructure, is presented. To illustrate the efficiency of the proposed control system, model tests on a mini-electromagnetic shaking table and a numerical simulation were performed. The test and numerical calculation results indicate that this new hybrid control mode with additional damping and smaller additional stiffness can achieve a better control efficiency.

  18. Temperature Control of Gas Chromatograph Based on Switched Delayed System Techniques

    Directory of Open Access Journals (Sweden)

    Xiao-Liang Wang

    2014-01-01

    Full Text Available We address the temperature control problem of the gas chromatograph. We model the temperature control system of the gas chromatograph into a switched delayed system and analyze the stability by common Lyapunov functional technique. The PI controller parameters can be given based on the proposed linear matrix inequalities (LMIs condition and the designed controller can make the temperature of gas chromatograph track the reference signal asymptotically. An experiment is given to illustrate the effectiveness of the stability criterion.

  19. 管角螺规模化人工育苗技术研究%Technique Probe:Artificial Hatching for Seawater Snail Hemifusus tuba at Industrialized Scale

    Institute of Scientific and Technical Information of China (English)

    阮鹏; 蒋霞敏; 彭瑞冰; 黎盛

    2015-01-01

    探究管角螺工厂化人工繁育技术,于2014年3~8月在象山来发水产育苗场,采用单因子试验方法进行了不同孵化密度(1、1.5、2、2.5、3 kg·筐-1)、稚螺不同培养密度(2.5×103、3.75×103、5.0×103、6.25×103 ind·m-2)、不同开口饵料(底栖硅藻、缢蛏肉、底栖硅藻+缢蛏肉、鱼肉)和水泥池规模化人工育苗技术研究.结果表明:当壳高小于1 cm 时,稚螺培养密度以3.75×103 ind·m-2为宜,大于1 cm时,其培养密度控制在大约1×103 ind·m-2;开口饵料以底栖硅藻+缢蛏为佳.实验共收集卵荚650 kg,获初孵稚螺(平均质量(0.003±0.001)g,壳高在0.4~0.5 cm)238.10×104 ind,在水温25~30℃和盐度25~30的条件下,培养15~16 d,育出平均壳高1.1~1.2 cm 幼螺197.50×104 ind,育成率在79.86%~88.50%,平均育成率达83.34%.%To rehabilitate the natural resources of Hemifusus tuba, artificial breeding technique of Hemifusus tuba at industrialized scale was investigated from March to August in 2014, in Xiangshan Laifa aquatic hatchery farm. Single factor test was performed to test the effects of influencing factors on the growth and survival rate of the snail, including incubation density (1, 1.5, 2, 2.5, 3 kg·frame-1), juvenile culture density (2.5×103, 3.75×103, 5.0×103, 6.25×103 ind·m-2) and weaning food (benthic diatoms, meat of Sinonovacula constrzcta, benthic diatoms and meat of Sinonovacula constrzcta, trash fish). The results show that the culture density for juvenile snails less than 1 cm and larger than 1 cm is 3.75×103 and 1×103 ind·m-2, respectively. The best weaning food is the combination of benthic diatoms and meat of Sinonovacula constrzcta. A total of 650 kg egg pod and 238.10×104 juvenile snails (the average weight of (0.003±0.001)g, shell height in 0.4-0.5 cm) are collected. In all, 197.50×104 individuals survived after 15-16 days of culture at the temperature of 25-30 ℃ and the salinity of 25-30. The survival rate is 79

  20. Neuro-Fuzzy Computational Technique to Control Load Frequency in Hydro-Thermal Interconnected Power System

    Science.gov (United States)

    Prakash, S.; Sinha, S. K.

    2015-09-01

    In this research work, two areas hydro-thermal power system connected through tie-lines is considered. The perturbation of frequencies at the areas and resulting tie line power flows arise due to unpredictable load variations that cause mismatch between the generated and demanded powers. Due to rising and falling power demand, the real and reactive power balance is harmed; hence frequency and voltage get deviated from nominal value. This necessitates designing of an accurate and fast controller to maintain the system parameters at nominal value. The main purpose of system generation control is to balance the system generation against the load and losses so that the desired frequency and power interchange between neighboring systems are maintained. The intelligent controllers like fuzzy logic, artificial neural network (ANN) and hybrid fuzzy neural network approaches are used for automatic generation control for the two area interconnected power systems. Area 1 consists of thermal reheat power plant whereas area 2 consists of hydro power plant with electric governor. Performance evaluation is carried out by using intelligent (ANFIS, ANN and fuzzy) control and conventional PI and PID control approaches. To enhance the performance of controller sliding surface i.e. variable structure control is included. The model of interconnected power system has been developed with all five types of said controllers and simulated using MATLAB/SIMULINK package. The performance of the intelligent controllers has been compared with the conventional PI and PID controllers for the interconnected power system. A comparison of ANFIS, ANN, Fuzzy and PI, PID based approaches shows the superiority of proposed ANFIS over ANN, fuzzy and PI, PID. Thus the hybrid fuzzy neural network controller has better dynamic response i.e., quick in operation, reduced error magnitude and minimized frequency transients.