WorldWideScience

Sample records for artificial techniques controlling

  1. Artificial intelligence techniques for voltage control

    Energy Technology Data Exchange (ETDEWEB)

    Ekwue, A.; Cheng, D.T.Y.; Macqueen, J.F.

    1997-12-31

    In electric power systems, the advantages of reactive power dispatching or optimisation include improved utilisation of reactive power sources and hence reduction in reactive power flows and real losses of the system; unloading of the system and equipment as a result of reactive flow reduction; the power factors of generation are improved and system security is enhanced; reduced voltage gradients and somewhat higher voltages which result across the system from improved operation; deferred capital investment is new reactive power sources as a result of improved utilisation of existing equipment; and for the National Grid Company plc (NGC), the main advantage is reduced out-of-merit operation. The problem of reactive power control has been studied and widely reported in the literature. Non-linear programming methods as well as linear programming techniques for constraint dispatch have been described. Static optimisation of reactive power sources by the use of sensitivity analysis was described by Kishore and Hill. Long range optimum var planning has been considered and the optimum amount and location of network reactive compensation so as to maintain the system voltage within the desired limits, while operating under normal and various insecurity states, have also been studied using several methods. The objective of this chapter is therefore to review conventional methods as well as AI techniques for reactive power control. (Author)

  2. Nuclear fuel pellet quality control using artificial intelligence techniques

    Science.gov (United States)

    Song, Xiaolong

    Inspection of nuclear fuel pellets is a complex and time-consuming process. At present, quality control in the fuel fabrication field mainly relies on human manual inspection, which is essentially a judgement call. Considering the high quality requirement of fuel pellets in the nuclear industry, pellet inspection systems must have a high accuracy rate in addition to a high inspection speed. Furthermore, any inspection process should have a low rejection rate of good pellets from the manufacturer point of view. It is very difficult to use traditional techniques, such as simple image comparison, to adequately perform the inspection process of the nuclear fuel pellet. Knowledge-based inspection and a defect-recognition algorithm, which maps the human inspection knowledge, is more robust and effective. A novel method is introduced here for pellet image processing. Three artificial intelligence techniques are studied and applied for fuel pellet inspection in this research. They are an artificial neural network, fuzzy logic, and the decision tree method. A dynamic reference model is located on each input fuel pellet image. Then, those pixels that belong to the abnormal defect are enhanced with high speed and high accuracy. Next, the content-based features for the defect are extracted from those abno1mal pixels and used in the inspection algorithm. Finally, an automated inspection prototype system---Visual Inspection Studio---which combines machine vision and these three AI techniques, is developed and tested. The experimental results indicate a very successful system with a high potential for on-line automatic inspection process.

  3. Optimization Techniques For an Artificial Potential Fields Racing Car Controller

    OpenAIRE

    Abdelrasoul, Nader

    2013-01-01

    Context. Building autonomous racing car controllers is a growing field of computer science which has been receiving great attention lately. An approach named Artificial Potential Fields (APF) is used widely as a path finding and obstacle avoidance approach in robotics and vehicle motion controlling systems. The use of APF results in a collision free path, it can also be used to achieve other goals such as overtaking and maneuverability. Objectives. The aim of this thesis is to build an autono...

  4. Application of radioisotope techniques to control flow process during artificial coastal aquifer recharge

    International Nuclear Information System (INIS)

    Radioisotope techniques was applied for studying the flow and transport processes in a coastal confined aquifer during an artificial recharge experiment to check the feasibility of controlling salt water intrusion by a hydrodynamic barrier. As no other water source is available, artificial recharge is done using treated wastewaters. Flow and effective velocity, hydraulic conductivity, transmissivity, diffusivity and effective porosity have been determined by means of I-131 radioisotope in single- and multi-well tests. (author)

  5. 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.

  6. 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.

  7. 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

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

    OpenAIRE

    Khammar, F; N. E. Debbache

    2016-01-01

    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 challeng...

  9. Artificial intelligence techniques in power systems

    Energy Technology Data Exchange (ETDEWEB)

    Laughton, M.A.

    1997-12-31

    Since the early to mid 1980s much of the effort in power systems analysis has turned away from the methodology of formal mathematical modelling which came from the fields of operations research, control theory and numerical analysis to the less rigorous techniques of artificial intelligence (AI). Today the main AI techniques found in power systems applications are those utilising the logic and knowledge representations of expert systems, fuzzy systems, artificial neural networks (ANN) and, more recently, evolutionary computing. These techniques will be outlined in this chapter and the power system applications indicated. (Author)

  10. 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.

  11. 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

  12. Event tree analysis using artificial intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Dixon, B.W.; Hinton, M.F.

    1985-01-01

    Artificial Intelligence (AI) techniques used in Expert Systems and Object Oriented Programming are discussed as they apply to Event Tree Analysis. A SeQUence IMPortance calculator, SQUIMP, is presented to demonstrate the implementation of these techniques. Benefits of using AI methods include ease of programming, efficiency of execution, and flexibility of application. The importance of an appropriate user interface is stressed. 5 figs.

  13. Artificial locomotion control

    DEFF Research Database (Denmark)

    Azevedo, Christine; Poignet, Philippe; Espiau, Bernard

    2004-01-01

    This paper concerns the simultaneous synthesis and control of walking gaits for biped robots. The goal is to propose an adaptable and reactive control law for two-legged machines. The problem is addressed with human locomotion as a reference. The starting point of our work is an analysis of human...... walking from descriptive (biomechanics) as well as explicative (neuroscience and physiology) points of view, the objective being to stress the relevant elements for the approach of robot control. The adopted principles are then: no joint trajectory tracking; explicit distinction and integration of...... postural and walking control; use of evolutive optimization objectives; on-line event handling and environment adaptation and anticipation. This leads to the synthesis of an original control scheme based on non-linear model predictive control: Trajectory Free NMPC. The movement is specified implicitly...

  14. Artificial Intelligence Techniques for Steam Generator Modelling

    CERN Document Server

    Wright, Sarah

    2008-01-01

    This paper investigates the use of different Artificial Intelligence methods to predict the values of several continuous variables from a Steam Generator. The objective was to determine how the different artificial intelligence methods performed in making predictions on the given dataset. The artificial intelligence methods evaluated were Neural Networks, Support Vector Machines, and Adaptive Neuro-Fuzzy Inference Systems. The types of neural networks investigated were Multi-Layer Perceptions, and Radial Basis Function. Bayesian and committee techniques were applied to these neural networks. Each of the AI methods considered was simulated in Matlab. The results of the simulations showed that all the AI methods were capable of predicting the Steam Generator data reasonably accurately. However, the Adaptive Neuro-Fuzzy Inference system out performed the other methods in terms of accuracy and ease of implementation, while still achieving a fast execution time as well as a reasonable training time.

  15. Artificial intelligence approach to accelerator control systems

    International Nuclear Information System (INIS)

    An experiment was recently started at LAMPF to evaluate the power and limitations of using artificial intelligence techniques to solve problems in accelerator control and operation. A knowledge base was developed to describe the characteristics and the relationships of the first 30 devices in the LAMPF H+ beam line. Each device was categorized and pertinent attributes for each category defined. Specific values were assigned in the knowledge base to represent each actual device. Relationships between devices are modeled using the artificial intelligence techniques of rules, active values, and object-oriented methods. This symbolic model, built using the Knowledge Engineering Environment (KEE) system, provides a framework for analyzing faults, tutoring trainee operators, and offering suggestions to assist in beam tuning. Based on information provided by the domain expert responsible for tuning this portion of the beam line, additional rules were written to describe how he tunes, how he analyzes what is actually happening, and how he deals with failures. Initial results have shown that artificial intelligence techniques can be a useful adjunct to traditional methods of numerical simulation. Successful and efficient operation of future accelerators may depend on the proper merging of symbolic reasoning and conventional numerical control algorithms

  16. 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.

  17. 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.

  18. Artificial Intelligence techniques for mission planning for mobile robots

    International Nuclear Information System (INIS)

    This work focuses on Spatial Modelization Techniques and on Control Software Architectures, in order to deal efficiently with the Navigation and Perception problems encountered in Mobile Autonomous Robotics. After a brief survey of the current various approaches for these techniques, we expose ongoing simulation works for a specific mission in robotics. Studies in progress used for Spatial Reasoning are based on new approaches combining Artificial Intelligence and Geometrical techniques. These methods deal with the problem of environment modelization using three types of models: geometrical topological and semantic models at different levels. The decision making processes of control are presented as the result of cooperation between a group of decentralized agents that communicate by sending messages. (author)

  19. [Research progress on techniques for artificial propagation of corals].

    Science.gov (United States)

    Wang, Shu-hong; Hong, Wen-ting; Chen, Ji-xin; Chen, Yun; Wang, Yi-lei; Zhang, Zi-ping; Weng, Zhao-hong; Xie, Yang-jie

    2015-09-01

    The natural coral reef resources degrade rapidly because of climate change, environmental pollution and exploitation of aquarium species. Artificial propagation is an effective way to facilitate the reduction of wild harvesting, reef restoration, preservation of biodiversity. This paper reviewed the technique and research progresses focused on coral artificial propagation. We compared the advantages and disadvantages of sexual reproduction and asexual reproduction as well as in situ and ex situ propagation. Moreover, we summarized the important roles of irradiation, flow rate, nutrients, feed and other factors in coral propagation within recirculating aquaculture system (RAS). Irradiation is the key to successful ex situ coral culture and different species show different needs of radiation intensity and light spectrum. Therefore, artificial lighting in RAS, as well as. power and maintenance costs, are very important for ex situ coral aquaculture. In addition, corals are very sensitive to NH4+, NO3-, NO2- as well as phosphate in RAS, and many physical, chemical and biological methods are acquired to maintain low nutrients condition. Although RAS has progressed a lot in terms of irradiation, flow rate and nutrient control, future studies also should focus on sexual reproduction, genetic modification and disease control. PMID:26785577

  20. On-line fault diagnosis of industrial processes based on artificial intelligence techniques

    OpenAIRE

    Calado, J. M. F.

    1996-01-01

    In this research the application of artificial intelligence techniques for on-line process control and fault detection and diagnosis are investigated. The majority of the research is on using artificial intelligence techniques in on-line fault detection and diagnosis of industrial processes. Several on-line approaches, including a rule based controller and several fault detection and diagnosis systems, have been developed and implemented and are described throughout this thesis. The research ...

  1. 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.

  2. Coordination Techniques for Distributed Artificial Intelligence

    OpenAIRE

    Jennings, N. R.

    1996-01-01

    Coordination, the process by which an agent reasons about its local actions and the (anticipated) actions of others to try and ensure the community acts in a coherent manner, is perhaps the key problem of the discipline of Distributed Artificial Intelligence (DAI). In order to make advances it is important that the theories and principles which guide this central activity are uncovered and analysed in a systematic and rigourous manner. To this end, this paper models agent communities using a ...

  3. 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

  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 (Pimprove color stability.

  5. ARTIFICIAL INTELLIGENCE PLANNING TECHNIQUES FOR ADAPTIVE VIRTUAL COURSE CONSTRUCTION

    OpenAIRE

    NÉSTOR DARÍO DUQUE; DEMETRIO ARTURO OVALLE

    2011-01-01

    This paper aims at presenting a planning model for adapting the behavior of virtual courses based on artificial intelligence techniques, in particular using not only a multi-agent system approach, but also artificial intelligence planning methods. The design and implementation of the system by means of a pedagogical multi-agent approach and the definition of a framework to specify the adaptation strategy allow us to incorporate several pedagogical and technological approaches that are in acco...

  6. 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....

  7. 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.

  8. 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.

  9. Applications of artificial intelligence to reactor and plant control

    International Nuclear Information System (INIS)

    Potential improvements in plant efficiency and reliability are often cited as reasons for developing and applying artificial intelligence (AI) techniques, principally expert systems, to the control and operation of nuclear reactors. Nevertheless, there have been few such applications and then mostly at the prototype level. Therefore, if AI techniques are to contribute to process control, methods must be identified by which rule-based and analytic approaches can be merged. This hypothesis is the basic premise of this article. Presented below are 1. a brief review of the human approach towards process control, 2. a discussion of the suitability of AI methodologies for the performance of control tasks, 3. examples of AI applications to both open- and closed-loop control, 4. an enumeration of unresolved issues associated with the use of AI for control, and 5. a discussion of the possible role of expert system techniques in process control. (orig./GL)

  10. Artificial Intelligence based technique for BTS placement

    International Nuclear Information System (INIS)

    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

  11. Application of Artificial Intelligence Techniques in Uninhabited Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA Southeastearn University and a beginning project at NASA 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 Artificial Intelligence 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.

  12. Application of Artificial Intelligence Techniques in Uninhabitated Aerial Vehicle Flight

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2003-01-01

    This paper describes the development of an application of Artificial Intelligence (AI) for Unmanned Aerial Vehicle (UAV) control. The project was done as part of the requirements for a class in AI at NOVA southeastern University and a beginning project at NASA 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 Artificial Intelligence 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.

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

    International Nuclear Information System (INIS)

    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)

  14. Contamination Control Techniques

    International Nuclear Information System (INIS)

    Welcome to a workshop on contamination Control techniques. This work shop is designed for about two hours. Attendee participation is encouraged during the workshop. We will address different topics within contamination control techniques; present processes, products and equipment used here at Hanford and then open the floor to you, the attendees for your input on the topics

  15. Contamination Control Techniques

    Energy Technology Data Exchange (ETDEWEB)

    EBY, J.L.

    2000-05-16

    Welcome to a workshop on contamination Control techniques. This work shop is designed for about two hours. Attendee participation is encouraged during the workshop. We will address different topics within contamination control techniques; present processes, products and equipment used here at Hanford and then open the floor to you, the attendees for your input on the topics.

  16. Application of artificial intelligence techniques to TRR operation

    International Nuclear Information System (INIS)

    It has been over ten years since TRR had its initial critical. To collect the experiences of shift operators and technique staffs and transfer these experts' knowledge to a computer and build an expert system is a typical application of artificial intelligence techniques to nuclear business. The system can provide the correct information of TRR operation for shift personnel, new staffs and other technical people

  17. Artificial intelligence techniques for industrial applications in job shop scheduling.

    OpenAIRE

    Townsend, Wade Benton

    1983-01-01

    The application of AI (artificial intelligence) techniques to the scheduling of industrial production operations offers a promising new approach to a scheduling problem of great magnitude and complexity. Foremost among these techniques is a powerful knowledge representation language that is capable of modeling the production environment at all levels of detail. The capturing of such complexity in the data base enables the computer to generate feasible schedules from a very large solution spac...

  18. The role of artificial intelligence techniques in scheduling systems

    Science.gov (United States)

    Geoffroy, Amy L.; Britt, Daniel L.; Gohring, John R.

    1990-01-01

    Artificial Intelligence (AI) techniques provide good solutions for many of the problems which are characteristic of scheduling applications. However, scheduling is a large, complex heterogeneous problem. Different applications will require different solutions. Any individual application will require the use of a variety of techniques, including both AI and conventional software methods. The operational context of the scheduling system will also play a large role in design considerations. The key is to identify those places where a specific AI technique is in fact the preferable solution, and to integrate that technique into the overall architecture.

  19. An application of artificial intelligence theory to reconfigurable flight control

    Science.gov (United States)

    Handelman, David A.

    1987-01-01

    Artificial intelligence techniques were used along with statistical hpyothesis testing and modern control theory, to help the pilot cope with the issues of information, knowledge, and capability in the event of a failure. An intelligent flight control system is being developed which utilizes knowledge of cause and effect relationships between all aircraft components. It will screen the information available to the pilots, supplement his knowledge, and most importantly, utilize the remaining flight capability of the aircraft following a failure. The list of failure types the control system will accommodate includes sensor failures, actuator failures, and structural failures.

  20. An artificial intelligence approach to accelerator control systems

    International Nuclear Information System (INIS)

    An experiment was recently started at LAMPF to evaluate the power and limitations of using artificial intelligence techniques to solve problems in accelerator control and operation. A knowledge base was developed to describe the characteristics and the relationships of the first 30 devices in the LAMPF H+ beam line. Each device was categorized and pertinent attributes for each category defined. Specific values were assigned in the knowledge base to represent each actual device. Relationships between devices are modeled using the artificial intelligence techniques of rules, active values, and object-oriented methods. This symbolic model, built using the Knowledge Engineering Environment (KEE) system, provides a framework for analyzing faults, tutoring trainee operators, and offering suggestions to assist in beam tuning. Based on information provided by the domain expert responsible for tuning this portion of the beam line, additional rules were written to describe how he tunes, how he analyzes what is actually happening, and how he deals with failures. Initial results have shown that artificial intelligence techniques can be a useful adjunct to traditional methods of numerical simulation. Successful and efficient operation of future accelerators may depend on the proper merging of symbolic reasoning and conventional numerical control algorithms

  1. Analysis of dynamic conflicts by techniques of artificial intelligence

    OpenAIRE

    Shinar, Josef

    1989-01-01

    Dynamic conflicts exhibit differentiel game characteristics and their analysis by any method which disregards this feature may be, by definition, futile. Unfortunately, realistic conflicts may have an intricate information structure and a complex hierarchy which don't fit in the classical differential game formulation. Moreover, in many cases even well formulated differential games are not solvable. In the recent years great progress has been made in artificial intelligence techniques, put in...

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

    International Nuclear Information System (INIS)

    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

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

    Science.gov (United States)

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

    1999-11-01

    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.

  4. 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.

  5. Comparison of three artificial intelligence techniques for discharge routing

    Science.gov (United States)

    Khatibi, Rahman; Ghorbani, Mohammad Ali; Kashani, Mahsa Hasanpour; Kisi, Ozgur

    2011-06-01

    SummaryThe inter-comparison of three artificial intelligence (AI) techniques are presented using the results of river flow/stage timeseries, that are otherwise handled by traditional discharge routing techniques. These models comprise Artificial Neural Network (ANN), Adaptive Nero-Fuzzy Inference System (ANFIS) and Genetic Programming (GP), which are for discharge routing of Kizilirmak River, Turkey. The daily mean river discharge data with a period between 1999 and 2003 were used for training and testing the models. The comparison includes both visual and parametric approaches using such statistic as Coefficient of Correlation (CC), Mean Absolute Error (MAE) and Mean Square Relative Error (MSRE), as well as a basic scoring system. Overall, the results indicate that ANN and ANFIS have mixed fortunes in discharge routing, and both have different abilities in capturing and reproducing some of the observed information. However, the performance of GP displays a better edge over the other two modelling approaches in most of the respects. Attention is given to the information contents of recorded timeseries in terms of their peak values and timings, where one performance measure may capture some of the information contents but be ineffective in others. Thus, this makes a case for compiling knowledge base for various modelling techniques.

  6. 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.

  7. Artificial Intelligent Controller for a DC Motor

    Science.gov (United States)

    Delavari, Hadi; Ranjbar Noiey, Abolzafl; Minagar, Sara

    The Speed and position control of DC motors is addressed in this paper. An optimal intelligent control scheme is proposed for the system. Preliminary a PID controller is designed using Genetic Algorithms (GA). The proposed controller is implemented by using optimal integral state feedback control with GA and Kalman filter. In the proposed scheme, performance depends on choosing weighting matrices Q and R in the cost function, and accordingly GA is used to find these proper weighting matrices. In order to reduce the control performance degradation due to system parameters variation, a Kalman filter is gained. The performance of the proposed technique (ISF) is compared with PID controller. Computer simulation validates the effectiveness of the proposed scheme even in presence of uncertainties.

  8. Optimal control learning with artificial neural networks

    International Nuclear Information System (INIS)

    This paper shows neural networks capabilities in optimal control applications of non linear dynamic systems. Our method is issued of a classical method concerning the direct research of the optimal control using gradient techniques. We show that neural approach and backpropagation paradigm are able to solve efficiently equations relative to necessary conditions for an optimizing solution. We have taken into account the known capabilities of multi layered networks in approximation functions. And for dynamic systems, we have generalized the indirect learning of inverse model adaptive architecture that is capable to define an optimal control in relation to a temporal criterion. (orig.)

  9. Training Software in Artificial-Intelligence Computing Techniques

    Science.gov (United States)

    Howard, Ayanna; Rogstad, Eric; Chalfant, Eugene

    2005-01-01

    The Artificial Intelligence (AI) Toolkit is a computer program for training scientists, engineers, and university students in three soft-computing techniques (fuzzy logic, neural networks, and genetic algorithms) used in artificial-intelligence applications. The program promotes an easily understandable tutorial interface, including an interactive graphical component through which the user can gain hands-on experience in soft-computing techniques applied to realistic example problems. The tutorial provides step-by-step instructions on the workings of soft-computing technology, whereas the hands-on examples allow interaction and reinforcement of the techniques explained throughout the tutorial. In the fuzzy-logic example, a user can interact with a robot and an obstacle course to verify how fuzzy logic is used to command a rover traverse from an arbitrary start to the goal location. For the genetic algorithm example, the problem is to determine the minimum-length path for visiting a user-chosen set of planets in the solar system. For the neural-network example, the problem is to decide, on the basis of input data on physical characteristics, whether a person is a man, woman, or child. The AI Toolkit is compatible with the Windows 95,98, ME, NT 4.0, 2000, and XP operating systems. A computer having a processor speed of at least 300 MHz, and random-access memory of at least 56MB is recommended for optimal performance. The program can be run on a slower computer having less memory, but some functions may not be executed properly.

  10. Artificial intelligence and information-control systems of robots - 87

    International Nuclear Information System (INIS)

    Independent research areas of artificial intelligence represent the following problems: automatic problem solving and new knowledge discovering, automatic program synthesis, natural language, picture and scene recognition and understanding, intelligent control systems of robots equipped with sensoric subsystems, dialogue of two knowledge systems, as well as studying and modelling higher artificial intelligence attributes, such as emotionality and personality. The 4th Conference draws on the problems treated at the preceding Conferences, and presents the most recent knowledge on the following topics: theoretical problems of artificial intelligence, knowledge-based systems, expert systems, perception and pattern recognition, robotics, intelligent computer-aided design, special-purpose computer systems for artificial intelligence and robotics

  11. Generating Artificial Event Logs with Sufficient Discriminatory Power to Compare Process Discovery Techniques

    OpenAIRE

    Jouck, Toon; Depaire, Benoit

    2014-01-01

    Past research revealed issues with artificial event data used for comparative analysis of process mining algorithms. The aim of this research is to design, implement and validate a framework for producing artificial event logs which should increase discriminatory power of artificial event logs when evaluating process discovery techniques.

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

    OpenAIRE

    Nabil Ali Alrajeh; Lloret, J

    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...

  13. Hybrid Systems Knowledge Representation Using Modelling Environment System Techniques Artificial Intelligence

    OpenAIRE

    Latif, Kamran

    2014-01-01

    Knowledge-based or Artificial Intelligence techniques are used increasingly as alternatives to more classical techniques to model ENVIRONMENTAL SYSTEMS. Use of Artificial Intelligence (AI) in environmental modelling has increased with recognition of its potential. In this paper we examine the DIFFERENT TECHNIQUES of Artificial intelligence with profound examples of human perception, learning and reasoning to solve complex problems. However with the increase of complexity better methods are re...

  14. Technique of pneumatic pest control

    OpenAIRE

    Schäfer, Winfried

    2003-01-01

    Objectives: Pest control in organic production of berries, potatoes and vegetables usually employs spreading technique of registered phytopharmaceutical agents. This technique may be supported or even replaced by pneumatic pest control. Up to now there is no evaluation of pneumatic pest control available from agricultural engineering point of view. This paper concerns the following questions: Which techniques of pneumatic pest control are available and how may these techniques be improved in ...

  15. Detection of Anomalies in Hydrometric Data Using Artificial Intelligence Techniques

    Science.gov (United States)

    Lauzon, N.; Lence, B. J.

    2002-12-01

    This work focuses on the detection of anomalies in hydrometric data sequences, such as 1) outliers, which are individual data having statistical properties that differ from those of the overall population; 2) shifts, which are sudden changes over time in the statistical properties of the historical records of data; and 3) trends, which are systematic changes over time in the statistical properties. For the purpose of the design and management of water resources systems, it is important to be aware of these anomalies in hydrometric data, for they can induce a bias in the estimation of water quantity and quality parameters. These anomalies may be viewed as specific patterns affecting the data, and therefore pattern recognition techniques can be used for identifying them. However, the number of possible patterns is very large for each type of anomaly and consequently large computing capacities are required to account for all possibilities using the standard statistical techniques, such as cluster analysis. Artificial intelligence techniques, such as the Kohonen neural network and fuzzy c-means, are clustering techniques commonly used for pattern recognition in several areas of engineering and have recently begun to be used for the analysis of natural systems. They require much less computing capacity than the standard statistical techniques, and therefore are well suited for the identification of outliers, shifts and trends in hydrometric data. This work constitutes a preliminary study, using synthetic data representing hydrometric data that can be found in Canada. The analysis of the results obtained shows that the Kohonen neural network and fuzzy c-means are reasonably successful in identifying anomalies. This work also addresses the problem of uncertainties inherent to the calibration procedures that fit the clusters to the possible patterns for both the Kohonen neural network and fuzzy c-means. Indeed, for the same database, different sets of clusters can be

  16. Registering plant dysfunction in artificial biosystems through fluorescence imaging technique

    Science.gov (United States)

    Nikolova, Alexandra; Krumov, Alexandar; Vassilev, Vesselin

    Humanity ambitions in space exploration and long-term men-operated space missions evoke an increasing interest to artificial ecosystem researches. Advanced studies of plant biosystems provoke development of new innovative technologies for plant cultivation in man-made environment. Closed ecosystems of different types and structure are now used for space horticulture, cultivation of genetically modified species, bio-products for pharmacies and industry etc. New technologies are required to monitor and control basic parameters of future bioregenerative life support system, especially of plants photosynthetic activity as the most fundamental biological process. Authors propose a conception for a non-invasive control of plant physiological status in closed biosystem through spatial registration of chlorophyll fluorescence. This approach allows an early detection of stress impact on plants, reveal the dynamic and direction of the negative influence and the level of plant stress. Technical requirements for obtaining plant fluorescence images are examined in close relation with plant illumination conditions. Problems related with optimised plant illumination are discussed. Examples of fluorescence images of healthy and stressed plants demonstrate the sensibility and rapidity of signal changes caused by plant dysfunction. Proposed conception could be used for developing new technical solutions in autocontrolled bio-support systems, based on real time analysis of fluorescence images.

  17. 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.

  18. Crack identification based on synthetic artificial intelligent technique

    Energy Technology Data Exchange (ETDEWEB)

    Shim, Mun Bo; Suh, Myung Won [Sungkyunkwan Univ., Suwon (Korea, Republic of)

    2001-07-01

    It has been established that a crack has an important effect on the dynamic behavior of a structure. This effect depends mainly on the location and depth of the crack. To identify the location and depth of a crack in a structure, a method is presented in this paper which uses synthetic artificial intelligent technique, that is, Adaptive-Network-based Fuzzy Inference System(ANFIS) solved via hybrid learning algorithm(the back-propagation gradient descent and the least-squares method) are used to learn the input(the location and depth of a crack)-output(the structural eigenfrequencies) relation of the structural system. With this ANFIS and a Continuous Evolutionary Algorithm(CEA), it is possible to formulate the inverse problem. CEAs based on genetic algorithms work efficiently for continuous search space optimization problems like a parameter identification problem. With this ANFIS, CEAs are used to identify the crack location and depth minimizing the difference from the measured frequencies. We have tried this new idea on a simple beam structure and the results are promising.

  19. APPLICATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES IN PROCESS FAULT DIAGNOSIS

    Directory of Open Access Journals (Sweden)

    M.A. HUSSAIN

    2007-12-01

    Full Text Available Chemical processes are systems that include complicated network of material, energy and process flow. As time passes, the performance of chemical process gradually degrades due to the deterioration of process equipments and components. The early detection and diagnosis of faults in chemical processes is very important both from the viewpoint of plant safety as well as reduced manufacturing costs. The conventional way used in fault detection and diagnosis is through the use of models of the process, which is not easy to be achieved in many cases. In recent years, an artificial intelligence technique such as neural network has been successfully used for pattern recognition and as such it can be suitable for use in fault diagnosis of processes [1]. The application of neural network methods in process fault detection and diagnosis is demonstrated in this work in two case studies using simulated chemical plant systems. Both systems were successfully diagnosed of the faults introduced in them. The neural networks were able to generalise to successfully diagnosed fault combinations it was not explicitly trained upon. Thus, neural network can be fully applied in industries as it has shown several advantages over the conventional way in fault diagnosis.

  20. Alpha efficiency under TL and OSL - A subtraction technique using OSL and TL to detect artificial irradiation

    International Nuclear Information System (INIS)

    With the development of thermoluminescence (TL) and optically stimulated luminescence (OSL) to determine the authenticity of old ceramics, forgers use artificial irradiation by gamma ray to age modern productions. Besides fraudulent action, objects can be exposed to various sources of X-rays (e.g. radiography, security control at airports). For all these reasons, the determination of artificial irradiation is an important topic for dating art objects. The main technique to identify artificial irradiations is the subtraction technique. It is based on the fact that alpha efficiency varies according to the luminescence technique (fine grain, coarse grains, predose, OSL). Having observed a rather significant difference of alpha efficiency for TL and OSL, we propose a new subtraction technique using OSL and TL of fine grains.

  1. Alpha efficiency under TL and OSL - A subtraction technique using OSL and TL to detect artificial irradiation

    Energy Technology Data Exchange (ETDEWEB)

    Zink, A.J.C., E-mail: antoine.zink@culture.gouv.f [Laboratoire du Centre de Recherche et de Restauration des Musees de France, C2RMF, MCC, CNRS, Palais du Louvre, Porte des lions, 14 quai F. Mitterrand, 75001 Paris (France); Dabis, S.; Porto, E.; Castaing, J. [Laboratoire du Centre de Recherche et de Restauration des Musees de France, C2RMF, MCC, CNRS, Palais du Louvre, Porte des lions, 14 quai F. Mitterrand, 75001 Paris (France)

    2010-03-15

    With the development of thermoluminescence (TL) and optically stimulated luminescence (OSL) to determine the authenticity of old ceramics, forgers use artificial irradiation by gamma ray to age modern productions. Besides fraudulent action, objects can be exposed to various sources of X-rays (e.g. radiography, security control at airports). For all these reasons, the determination of artificial irradiation is an important topic for dating art objects. The main technique to identify artificial irradiations is the subtraction technique. It is based on the fact that alpha efficiency varies according to the luminescence technique (fine grain, coarse grains, predose, OSL). Having observed a rather significant difference of alpha efficiency for TL and OSL, we propose a new subtraction technique using OSL and TL of fine grains.

  2. Development and Physical Control Research on Prototype Artificial Leg

    OpenAIRE

    Fei Li; Fuming Zhang; Hualong Xie

    2016-01-01

    To provide an ideal platform for research on intelligent bionic leg (IBL), this paper proposes a model of a biped robot with heterogeneous legs (BRHL). A prototype of an artificial leg is developed based on biological structure and motion principle analysis of human lower extremities. With regard to the driving sources, servomotors are chosen for the hip joint and ankle joint, while pneumatic muscle actuators (PMAs) are chosen for the knee joint. The control system of the bionic artificial le...

  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. Optimization and control of feb-batch fermentation processes by using artificial neural systems

    OpenAIRE

    Valencia Peroni, Catalina

    2002-01-01

    This work focuses on the application of neural networks in the areas of modelling, identification, control and optimization of biothechnology processes, mainly fed-batch bioreactors. The basic ideas and techniques of artificial neural networks are presented with the notation familiar to control engineers. The applications of a variety of neural network architectures in control and control schemes are first surveyed. Some especific fed-batch bioreactor processes are mentioned to illustrate par...

  5. Artificial Intelligence Techniques in Real-Time Strategy Games - Architecture and Combat Behavior

    OpenAIRE

    Stene, Sindre Berg

    2006-01-01

    The general purpose of this research is to investigate the possibilities offered for the use of Artificial Intelligence theory and methods in advanced game environments. The real-time strategy (RTS) game genre is investigated in detail, and an architecture and solutions to some common issues are presented. An RTS AI controlled opponent named KAI is implemented for the TA Spring game engine in order to advance the state of the art in usin AI techniques in games and to gain some insight int...

  6. LARA. Localization of an automatized refueling machine by acoustical sounding in breeder reactors - implementation of artificial intelligence techniques

    International Nuclear Information System (INIS)

    The automatic control of the machine which handles the nuclear subassemblies in fast neutron reactors requires autonomous perception and decision tools. An acoustical device allows the machine to position in the work area. Artificial intelligence techniques are implemented to interpret the data: pattern recognition, scene analysis. The localization process is managed by an expert system. 6 refs.; 8 figs

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

    International Nuclear Information System (INIS)

    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. (paper)

  8. A Survey on Using Artificial Intelligence Techniques in the Software Development Process

    OpenAIRE

    K. Hema Shankari; Dr. R.Thirumalaiselvi

    2014-01-01

    Software engineering and artificial intelligence are the two important fields of the computer science. Artificial Intelligence is about making machines intelligent, while Software engineering is knowledge –intensive activity, requiring extensive knowledge of the application domain and of the target software itself. This study intends to review the techniques developed in artificial intelligence from the standpoint of their application in software engineering. The goal of this rese...

  9. Application of Artificial Intelligence and Data Mining Techniques to Financial Markets

    OpenAIRE

    Katarína Hilovska; Peter Koncz

    2012-01-01

    The aim of artificial intelligence is to discover mechanisms of adaptation in a changing environment with utilisation of intelligence, for instance in the ability to exclude unlikely solutions. Artificial intelligence methods have extensive application in different fields such as medicine, games, transportation, or heavy industry. This paper deals with interdisciplinary issues – interconnection of artificial intelligence and finance. The paper briefly describes techniques of data mining, expe...

  10. Optimal fuel loading pattern design using artificial intelligence techniques

    International Nuclear Information System (INIS)

    The Optimal Fuel Shuffling System (OFSS) is developed for optimal design of PWR fuel loading pattern. OFSS is a hybrid system that a rule based system, a fuzzy logic, and an artificial neural network are connected each other. The rule based system classifies loading patterns into two classes using several heuristic rules and a fuzzy rule. A fuzzy rule is introduced to achieve more effective and fast searching. Its membership function is automatically updated in accordance with the prediction results. The artificial neural network predicts core parameters for the patterns generated from the rule based system. The back-propagation network is used for fast prediction of core parameters. The artificial neural network and the fuzzy logic can be used as the tool for improvement of existing algorithm's capabilities. OFSS was demonstrated and validated for cycle 1 of Kori unit 1 PWR. (Author)

  11. The application of neural networks with artificial intelligence technique in the modeling of industrial processes

    International Nuclear Information System (INIS)

    Neural networks are a relatively new artificial intelligence technique that emulates the behavior of biological neural systems in digital software or hardware. These networks can 'learn', automatically, complex relationships among data. This feature makes the technique very useful in modeling processes for which mathematical modeling is difficult or impossible. The work described here outlines some examples of the application of neural networks with artificial intelligence technique in the modeling of industrial processes.

  12. An application of selected artificial-intelligence techniques to engineering analysis

    Energy Technology Data Exchange (ETDEWEB)

    Forde, B.W.R.

    1989-01-01

    This thesis explores the application of some of the more practical artificial intelligence (AI) techniques developed to date in the field of engineering analysis. The limitations of conventional computer-aided analysis programs provide the motivation for knowledge automation and development of a hybrid approach for constructing and controlling engineering analysis software. Artificial intelligence technology used in this thesis includes: object oriented programming, generic application frameworks, event-driven architectures, and knowledge-based expert systems. Emphasis is placed on the implementation-independent description of objects, classes, methods, and inheritance using a simple graphical representation. The kinds of knowledge used in the analysis process, the programs that control this knowledge, and the resources that perform numerical computation are described as part of a hybrid system for engineering analysis. Modelling, solution, and interpretation activities are examined for a generic problem and a control framework is adopted for event-driven operation. An intelligent finite element analysis program called SNAP is developed to demonstrate the application of AI in the numerical analysis of two-dimensional linear problems in solid and structural mechanics. A step-by-step discussion is given for the design, implementation, and operation of the SNAP software to provide a clear understanding of the principles involved. The general conclusion of this thesis is that a variety of artificial intelligence techniques can be used to significantly improve the engineering analysis process, and that much research is still to be done. A series of projects suitable for completion by graduate students in the field of structural engineering are described at the end of the thesis.

  13. Carrier relaxation dynamics in self-assembled quantum dots studied by artificial control of nonradiative losses

    Energy Technology Data Exchange (ETDEWEB)

    Davydov, V.; Nair, S.V.; Lee, J.-S.; Ren, H.-W. [JST, Tsukuba (Japan). ERATO Single Quantum Dot Project; Ignatiev, I.V.; Kozin, I.E. [JST, Tsukuba (Japan). ERATO Single Quantum Dot Project; Sankt-Peterburgskij Univ. (Russian Federation). Research Inst. of Physics; Sugou, S. [JST, Tsukuba (Japan). ERATO Single Quantum Dot Project; NEC Corp., Tsukuba (Japan). Opto-Electronics Research Lab.; Masumoto, Y. [JST, Tsukuba (Japan). ERATO Single Quantum Dot Project; Tsukuba Univ., Sakura, Ibaraki (Japan). Inst. of Physics

    2001-03-08

    Efficient single-step relaxation processes with emission of acoustic phonons are observed by a technique based on an artificial control of nonradiative losses by an external electric field. This observation is supported by the PL kinetics measurements. The findings give new and important insights into the interaction of the confined electron-hole pairs with the phonon subsystem. (orig.)

  14. Whispering galleries and the control of artificial atoms

    Science.gov (United States)

    Forrester, Derek Michael; Kusmartsev, Feodor V.

    2016-01-01

    Quantum computation using artificial-atoms, such as novel superconducting circuits, can be sensitively controlled by external electromagnetic fields. These fields and the self-fields attributable to the coupled artificial-atoms influence the amount of quantum correlation in the system. However, control elements that can operate without complete destruction of the entanglement of the quantum-bits are difficult to engineer. Here we investigate the possibility of using closely-spaced-linear arrays of metallic-elliptical discs as whispering gallery waveguides to control artificial-atoms. The discs confine and guide radiation through the array with small notches etched into their sides that act as scatterers. We focus on π-ring artificial-atoms, which can generate their own spontaneous fluxes. We find that the micro-discs of the waveguides can be excited by terahertz frequency fields to exhibit whispering-modes and that a quantum-phase-gate composed of π-rings can be operated under their influence. Furthermore, we gauge the level of entanglement through the concurrence measure and show that under certain magnetic conditions a series of entanglement sudden-deaths and revivals occur between the two qubits. This is important for understanding the stability and life-time of qubit operations using, for example, a phase gate in a hybrid of quantum technologies composed of control elements and artificial-atoms. PMID:27122353

  15. Whispering galleries and the control of artificial atoms.

    Science.gov (United States)

    Forrester, Derek Michael; Kusmartsev, Feodor V

    2016-01-01

    Quantum computation using artificial-atoms, such as novel superconducting circuits, can be sensitively controlled by external electromagnetic fields. These fields and the self-fields attributable to the coupled artificial-atoms influence the amount of quantum correlation in the system. However, control elements that can operate without complete destruction of the entanglement of the quantum-bits are difficult to engineer. Here we investigate the possibility of using closely-spaced-linear arrays of metallic-elliptical discs as whispering gallery waveguides to control artificial-atoms. The discs confine and guide radiation through the array with small notches etched into their sides that act as scatterers. We focus on π-ring artificial-atoms, which can generate their own spontaneous fluxes. We find that the micro-discs of the waveguides can be excited by terahertz frequency fields to exhibit whispering-modes and that a quantum-phase-gate composed of π-rings can be operated under their influence. Furthermore, we gauge the level of entanglement through the concurrence measure and show that under certain magnetic conditions a series of entanglement sudden-deaths and revivals occur between the two qubits. This is important for understanding the stability and life-time of qubit operations using, for example, a phase gate in a hybrid of quantum technologies composed of control elements and artificial-atoms. PMID:27122353

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Artificial moment method for swarm robot formation control

    Institute of Scientific and Technical Information of China (English)

    XU WangBao; CHEN XueBo

    2008-01-01

    The purpose of this paper is to develop a general control method for swarm robot formation control.Firstly,an attraction-segment leader-follower formation graph is presented for formation representations.The model of swarm robot systems is described.According to the results and two kinds of artificial momenta defined as leader-attraction moment and follower-attraction moment,a novel artificial moment method is proposed for swarm robot formation control.The principle of the method is introduced and the motion controller of robots is designed.Finally,the stability of the formation control system is proved.The simulations show that both the formation representation graph and the formation control method are valid and feasible.

  3. Control approach development for variable recruitment artificial muscles

    Science.gov (United States)

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

    2016-04-01

    This study characterizes hybrid control approaches for the variable recruitment of fluidic artificial muscles with double acting (antagonistic) actuation. Fluidic artificial muscle actuators have been explored by researchers due to their natural compliance, high force-to-weight ratio, and low cost of fabrication. Previous studies have attempted to improve system efficiency of the actuators through variable recruitment, i.e. using discrete changes in the number of active actuators. While current variable recruitment research utilizes manual valve switching, this paper details the current development of an online variable recruitment control scheme. By continuously controlling applied pressure and discretely controlling the number of active actuators, operation in the lowest possible recruitment state is ensured and working fluid consumption is minimized. Results provide insight into switching control scheme effects on working fluids, fabrication material choices, actuator modeling, and controller development decisions.

  4. Control Strategies and Artificial Intelligence in Rehabilitation Robotics

    OpenAIRE

    Novak, Domen; University of Wyoming; Riener, Robert; Swiss Federal Institute of Technology (ETH) in Zurich

    2015-01-01

    Rehabilitation robots physically support and guide a patient's limb during motor therapy, but require sophisticated control algorithms and artificial intelligence to do so. This article provides an overview of the state of the art in this area. It begins with the dominant paradigm of assistive control, from impedance-based cooperative controller through electromyography and intention estimation. It then covers challenge-based algorithms, which provide more difficult and complex tasks for the ...

  5. Speed estimation of vector controlled squirrel cage asynchronous motor with artificial neural networks

    International Nuclear Information System (INIS)

    In this paper, the artificial neural networks as a sensorless speed estimator in indirect vector controlled squirrel cage asynchronous motor control are defined. High dynamic performance power semi conductors obtainable from direct current motors can also be obtained from asynchronous motor through developments in digital signal processors (DSP) and control techniques. With using of field diverting control in asynchronous motors, the flux and moment can be controlled independently. The process of estimating the speed information required in control of vector controlled asynchronous motor without sensors has been obtained with artificial neural networks (ANN) in this study. By examining the data obtained from the experimental study concluded on the DSP application circuit, the validity and high performance of the ANN speed estimator on real-time speed estimation has been demonstrated.

  6. 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.

  7. 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

  8. Artificial intelligence-based control system for the analysis of metal casting properties

    OpenAIRE

    E. Mares; J.H. Sokolowski

    2010-01-01

    Purpose: The metal casting process requires testing equipment that along with customized computer software properly supports the analysis of casting component characteristic properties. Due to the fact that this evaluation process involves the control of complex and multi-variable melting, casting and solidification factors, it is necessary to develop dedicated software.Design/methodology/approach: The integration of Statistical Process Control methods and Artificial Intelligence techniques (...

  9. Future applications of artificial intelligence to Mission Control Centers

    Science.gov (United States)

    Friedland, Peter

    1991-01-01

    Future applications of artificial intelligence to Mission Control Centers are presented in the form of the viewgraphs. The following subject areas are covered: basic objectives of the NASA-wide AI program; inhouse research program; constraint-based scheduling; learning and performance improvement for scheduling; GEMPLAN multi-agent planner; planning, scheduling, and control; Bayesian learning; efficient learning algorithms; ICARUS (an integrated architecture for learning); design knowledge acquisition and retention; computer-integrated documentation; and some speculation on future applications.

  10. 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.

  11. Development and Physical Control Research on Prototype Artificial Leg

    Directory of Open Access Journals (Sweden)

    Fei Li

    2016-03-01

    Full Text Available To provide an ideal platform for research on intelligent bionic leg (IBL, this paper proposes a model of a biped robot with heterogeneous legs (BRHL. A prototype of an artificial leg is developed based on biological structure and motion principle analysis of human lower extremities. With regard to the driving sources, servomotors are chosen for the hip joint and ankle joint, while pneumatic muscle actuators (PMAs are chosen for the knee joint. The control system of the bionic artificial leg is designed and a physical experimental platform is established. The physical control experiments are done based on proportional-integral-derivative (PID control strategy. The experimental results show that such a system can realize the expected goals.

  12. 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.

  13. The Fixation Technique of Artificial Crowns with Preliminary Preventive Treatment of Tooth Stump

    Directory of Open Access Journals (Sweden)

    Zhulev Е.N.

    2012-09-01

    Full Text Available The article gives the recommendations for artificial crowns cementing using prophylactic drugs aimed at the prevention of complex cavity of hard tissues of a prepared tooth. Preliminary use of prophylactic drug before final fixation of artificial crowns contributes to deep fluorization of hard tooth tissues, and thus, provides long stable positioning of dentures on prepared hard tissues of natural teeth. Clinical trials carried out showed that along with a precisely poured denture and try-in, the technique provides high caries-resistant of hard tooth tissues under an artificial crown.

  14. Vibroacoustic Modeling of Mechanically Coupled Structures: Artificial Spring Technique Applied to Light and Heavy Mediums

    Directory of Open Access Journals (Sweden)

    L. Cheng

    1996-01-01

    Full Text Available This article deals with the modeling of vibrating structures immersed in both light and heavy fluids, and possible applications to noise control problems and industrial vessels containing fluids. A theoretical approach, using artificial spring systems to characterize the mechanical coupling between substructures, is extended to include fluid loading. A structure consisting of a plate-ended cylindrical shell and its enclosed acoustic cavity is analyzed. After a brief description of the proposed technique, a number of numerical results are presented. The analysis addresses the following specific issues: the coupling between the plate and the shell; the coupling between the structure and the enclosure; the possibilities and difficulties regarding internal soundproofing through modifications of the joint connections; and the effects of fluid loading on the vibration of the structure.

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

    OpenAIRE

    Hayriye Altural; Ömer Galip Saracoglu

    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...

  16. Use of nuclear techniques in biological control

    International Nuclear Information System (INIS)

    As pointed out by Benbrook (1996), pest management is at a crossroads, and there is a great need for new, biointensive pest management strategies. Among these approaches, biological control is a keystone. However, because of increasing concerns about the introduction of exotic natural enemies of insect pests and weeds (Howarth 1991, Delfosse 1997), the overall thrust of biological control has moved toward augmentative biological control, involving releases of established natural enemy species (Knipling 1992). This in turn has created a need to develop more cost-effective mass rearing technologies for beneficial insects. Nuclear techniques could play an especially important role in augmentative biological control, not only in facilitating mass rearing, but in several other ways, as indicated below. Recognising the potential value for use of nuclear techniques in biological control, the Insect and Pest Control Section of the Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture, International Atomic Energy Agency, sponsored a Consultants' Group Meeting on this subject in April 1997. The Group produced a document entitled Use of Nuclear Techniques in Biological Control: Managing Pests, Facilitating Trade and Protecting the Environment. The consultants included the authors of this paper as well as Ernest Delfosse (at that time, with the USDA-APHIS National Biological Control Institute), Garry Hill (Intl. Institute for Biological Control), Sinthya Penn (Beneficial Insectary), and Felipe Jeronimo (USDA-APHIS PPQ, Guatemala). The remarks presented in this paper reflect the thoughts presented by these consultants and other participants at the IAEA-sponsored meeting. Several potential uses for nuclear techniques were identified by the Consultants' Group, including: 1) improvements in rearing media (either artificial diets or natural hosts/prey), 2) provision of sterilised natural prey to be used as food during shipment, to ameliorate concerns relating to the

  17. Application of Isotope Techniques for the Estimation of Artificial Recharge

    International Nuclear Information System (INIS)

    Geochemical studies on the alluvial aquifer system near the Nakdong River were carried out for the basic investigation of the estimation of artificial recharge for the river bank filtration. In-situ data do not show any distinct difference between the pumping well and river. Most of waters belong Ca-HCO3 and Ca-SO4 types and show high Mn concentration. In the borehole installed with Multi-packer (MP) system, Na, Ca, Mg, HCO3 contents of the groundwater are increased with depth increasing. Cl and SO4 contents of the groundwater show the lowest values at the bottom level (18m depth) and Mn content is very high at the middle level (13.5m depth) of MP system. There is no distinct difference in the δ18O and D values and tritium content between MP, borehole and surface water samples. The sulfur isotope data indicate that the possible sulfur source is dissolution of sulfate mineral from sedimentary rock. Strontium isotope ratio shows a little differences between the pumping well and observation borehole samples. Nitrogen isotope data indicate that the nitrogen of water samples is originated from fertilizer or organic materials

  18. Evolution of an artificial neural network based autonomous land vehicle controller.

    Science.gov (United States)

    Baluja, S

    1996-01-01

    This paper presents an evolutionary method for creating an artificial neural network based autonomous land vehicle controller. The evolved controllers perform better in unseen situations than those trained with an error backpropagation learning algorithm designed for this task. In this paper, an overview of the previous connectionist based approaches to this task is given, and the evolutionary algorithms used in this study are described in detail. Methods for reducing the high computational costs of training artificial neural networks with evolutionary algorithms are explored. Error metrics specific to the task of autonomous vehicle control are introduced; the evolutionary algorithms guided by these error metrics reveal improved performance over those guided by the standard sum-squared error metric. Finally, techniques for integrating evolutionary search and error backpropagation are presented. The evolved networks are designed to control Carnegie Mellon University's NAVLAB vehicles in road following tasks. PMID:18263046

  19. An on-line gas control system using an artificial intelligence language: PROLOG II

    International Nuclear Information System (INIS)

    An application of Artificial Intelligence to a real physics experiment is presented. This allows comparison with classical programming techniques. The PROLOG language appears as a convenient on-line language, easily interfaced to the low level service routines, for which algorithmic languages can still be used. Steering modules have been written for a gas acquisition and analysis program, and for a control system with graphic human interface. This system includes safety rules and automatic action sequences

  20. 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.

  1. Development of an Accident Diagnostic Scheme Using Artificial Intelligence Techniques (I)

    International Nuclear Information System (INIS)

    As a means to effectively manage the severe nuclear accidents, it is important to identify and diagnose the accident initiating events during an initial short time interval after the accidents by observing the major controlling parameters. Main objective of this study is to develop the diagnostic approach for the accurate prediction of accident initiating events using artificial intelligence techniques. For this, first, a variety of artificial intelligence techniques such as Finn, Gmbh, and Sm were examined through this study. Among them, Sc and Gmbh model were assessed as a useful approach to predict the break location and the break size of Local. In order to verify the proposed algorithm, the 111 accident simulation data (based on Map) were applied to train the Sc and Gmbh models, and the test data was used to independently verify whether or not the SVC and GMDH models work well. The analysis of the maximum errors and RMS errors, and the performance of the GMDH according to the existence of measurement errors and SIS actuation showed that the proposed SVC and GMDH models can accurately classify the break locations and accurately predict the break size. As the time-integrated signals were used for inputs into the GMDH model within a period of 60 second after a reactor scram, the actuation of the safety systems such as safety injection system (SIS), auxiliary feed water system, and containment spray system, were not considered in this study. It is because the initial 60 second time-integrated signals were used and the safety systems usually start to actuate after a more than 60 second time delay after the reactor scram

  2. 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.

  3. DIRECT TORQUE CONTROL FOR INDUCTION MOTOR USING INTELLIGENT TECHNIQUES

    OpenAIRE

    R. Toufouti; S.Meziane; Benalla, H.

    2007-01-01

    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.

  4. Design Optimization Utilizing Dynamic Substructuring and Artificial Intelligence Techniques

    OpenAIRE

    Akcay Perdahcioglu, D.; Ellenbroek, M.H.M.; Hoogt, van der, P.J.M.; Boer

    2008-01-01

    In mechanical and structural systems, resonance may cause large strains and stresses which can lead to the failure of the system. Since it is often not possible to change the frequency content of the external load excitation, the phenomenon can only be avoided by updating the design of the structure. In this paper, a design optimization strategy based on the integration of the Component Mode Synthesis (CMS) method with numerical optimization techniques is presented. For reasons of numerical e...

  5. Artificial intelligence techniques for the European Reliability Data System (ERDS)

    International Nuclear Information System (INIS)

    The design of an intelligent interface aimed at assisting the end-users in accessing a complex system consisting of three data bases loosely coupled (ERDS) and the development of a generalized semi-automatic transcoding system based on expert system techniques are discussed. The overall architecture of the system is presented and its main features are outlined. The formalism for representing specific knowledge is then illustrated. (DG)

  6. ARTIFICIAL INTELLIGENCE TECHNIQUES FOR ESTIMATING THE EFFORT IN SOFTWARE DEVELOPMENT PROJECTS

    OpenAIRE

    Ferreira, G; Quintero, L; Antón, J.

    2015-01-01

    Among the most popular algorithmic cost and efforts estimation models are COCOMO, SLIM, Function Points. However, since the 90s, the models based on Artificial Intelligence techniques, mainly in Machine Learning techniques have been used to improve the accuracy of the estimates. These models are based on two fundamental aspects: the use of data collected in previous projects where estimates were performed and the application of various knowledge extraction techniques, with the ...

  7. Semen controlled-release capsules allow a single artificial insemination in sows.

    Science.gov (United States)

    Vigo, D; Faustini, M; Villani, S; Orsini, F; Bucco, M; Chlapanidas, T; Conte, U; Ellis, K; Torre, M L

    2009-09-01

    Controlled-release capsules containing boar spermatozoa were developed to extend the preservation time of spermatozoa and maximize the efficiency of a single artificial insemination. A large trial (4245 sows) was performed with these capsules using double/triple conventional artificial insemination as a control. The effect of treatment on pregnancy diagnosis, delivery, and born piglets was investigated, with allowance being made for considering season, spermatozoa amount, and the weaning-to-estrus interval as confounding variables. The same pregnancy rate and prolificacy were obtained by two insemination techniques, and a higher parturition frequency was reached with capsules. The reproductive performance in pigs has therefore been optimized by a single instrumental insemination with controlled-release capsules. PMID:19505716

  8. Application of artificial intelligence techniques in the engineering design process

    International Nuclear Information System (INIS)

    The proposed paper gives a proof of concept of the fact that, currently available techniques for handling non-algorithmic problems by computers can be successfully applied to partially automate the decision making processes in the engineering design synthesis. Several small expert systems have been developed for helping a novice engineer to perform finite-element analyses of various structural elements. The expert systems guide the novice through such processes as setting the boundary conditions, choice of materials and suggest changes in initial design to achieve the desired product. (author)

  9. 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.

  10. Artificial intelligence techniques for tuning linear induction accelerators

    International Nuclear Information System (INIS)

    The authors developed an expert system that acts as an intelligent assistant for tuning particle beam accelerators called MAESTRO - Model and Expert System Tuning Resource of Operators. MAESTRO maintains a knowledge base of the accelerator containing not only the interconnections of the beamline components, but also their physical attributes such as measured magnet tilts, offsets, and field profiles. MAESTRO incorporates particle trajectory and beam envelope models which are coupled to the knowledge base permitting large numbers of real-time orbit and envelope calculations in the control-room environment. To data the authors have used this capability in three ways: (1) to implement a tuning algorithm for minimizing transverse beam motion, (2) to produce a beam waist with arbitrary radius at the entrance to a brightness diagnostic, and (3) to measure beam energy along the accelerator by fitting orbits to focusing and steering sweeps

  11. RESEARCH AREA -- ARTIFICIAL INTELLIGENCE CONTROL (AIR POLLUTION TECHNOLOGY BRANCH, AIR POLLUTION PREVENTION AND CONTROL DIVISION, NRMRL)

    Science.gov (United States)

    The Air Pollution Technology Branch (APTB) of NRMRL's Air Pollution Prevention and Control Division in Research Triangle Park, NC, has conducted several research projects for evaluating the use of artificial intelligence (AI) to improve the control of pollution control systems an...

  12. Evaluation, Energy Optimization, and Spectrum Analysis of an Artificial Noise Technique to Improve CWSN Security

    OpenAIRE

    Javier Blesa; Alvaro Araujo; Elena Romero; Octavio Nieto-Taladriz

    2013-01-01

    This paper presents the security evaluation, energy consumption optimization, and spectrum scarcity analysis of artificial noise techniques to increase physical-layer security in Cognitive Wireless Sensor Networks (CWSNs). These techniques introduce noise into the spectrum in order to hide real information. Nevertheless, they directly affect two important parameters in Cognitive Wireless Sensor Networks (CWSNs), energy consumption and spectrum utilization. Both are affected because the number...

  13. 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.

  14. Technique of nuclear reactors controls

    International Nuclear Information System (INIS)

    This report deal about 'Techniques of control of the nuclear reactors' in the goal to achieve the control of natural uranium reactors and especially the one of Saclay. This work is mainly about the measurement into nuclear parameters and go further in the measurement of thermodynamic variables,etc... putting in relief the new features required on behalf of the detectors because of their use in the thermal neutrons flux. In the domain of nuclear measurement, we indicate the realizations and the results obtained with thermal neutron detectors and for the measurement of ionizations currents. We also treat the technical problem of the start-up of a reactor and of the reactivity measurement. We give the necessary details for the comprehension of all essential diagrams and plans put on, in particular, for the reactor of Saclay. (author)

  15. Analysis of Dynamic Road Traffic Congestion Control (DRTCC Techniques

    Directory of Open Access Journals (Sweden)

    Pardeep Mittal

    2015-10-01

    Full Text Available : Dynamic traffic light control at intersection has become one of the most active research areas to develop the Dynamic transportation systems (ITS. Due to the consistent growth in urbanization and traffic congestion, such a system was required which can control the timings of traffic lights dynamically with accurate measurement of traffic on the road. In this paper, analysis of all the techniques that has been developed to automate the traffic lights has been done.. The efficacy of all the techniques has been evaluated, using MATLAB software. After comparison of artificial intelligent techniques , it is found that image mosaicking technique is quite effective (in terms of improving moving time and reducing waiting time for the control of the traffic signals to control congestion on the road.

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

    International Nuclear Information System (INIS)

    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.

  17. 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.

  18. 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.

  19. Artificial intelligence-based computer modeling tools for controlling slag foaming in electric arc furnaces

    Science.gov (United States)

    Wilson, Eric Lee

    Due to increased competition in a world economy, steel companies are currently interested in developing techniques that will allow for the improvement of the steelmaking process, either by increasing output efficiency or by improving the quality of their product, or both. Slag foaming is one practice that has been shown to contribute to both these goals. However, slag foaming is highly dynamic and difficult to model or control. This dissertation describes an effort to use artificial intelligence-based tools (genetic algorithms, fuzzy logic, and neural networks) to both model and control the slag foaming process. Specifically, a neural network is trained and tested on slag foaming data provided by a steel plant. This neural network model is then controlled by a fuzzy logic controller, which in turn is optimized by a genetic algorithm. This tuned controller is then installed at a steel plant and given control be a more efficient slag foaming controller than what was previously used by the steel plant.

  20. 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.

  1. GDO Artificial Intelligence-Based Switching PID Baseline Feedback Linearization Method: Controlled PUMA Workspace

    Directory of Open Access Journals (Sweden)

    Farzin Piltan

    2012-10-01

    Full Text Available Congetive method is used in this research to create portfilo of movement robot manipulator. Gradient descent (GD artificial intelligence based switching feedback linearization controller was used and robot’s postures and trajectory were expected in MATLAB/SIMULINK environment. Feedback linearization controller (CTC is an influential nonlinear controller to certain systems which it is based on feedback linearization and computes the required torques using the nonlinear feedback control law in certain systems. Practically a large amount of systems have uncertainties accordingly this method has a challenge. Switching feedback linearization controller is a significant combination nonlinear stable-robust controller under condition of partly uncertain dynamic parameters of system. This technique is used to control of highly nonlinear systems especially in nonlinear time varient nonlinear dynamic system. To increase the stability and robustness with regards to improve the robustness switching methodology is applied to feedback linearization controller. Lyapunov stability is proved in proposed controller based on switching function. To compensate for the dependence on switching parameters baseline methodology is used.The nonlinear model dynamic formulation problem in uncertain system can be solved by using artificial intelligence theorem. Fuzzy logic theory is used to estimate the system dynamic. Forward kinematics implemented the manipulator's movements. Results validated the robot's range of possible postures and trajectories.

  2. The implementation of artificial intelligence in control systems

    International Nuclear Information System (INIS)

    Some concepts of artificial intelligence are reviewed, particularly as they apply to control systems of accelerators. Logical representation and formal reasoning are discussed briefly, as well as production systems, which describe various systems based on the idea of condition-action pairs (productions). Procedural knowledge, which deals with routine activities that rarely require change, is described. Frames are defined, which provide a convenient structure for representing knowledge. Frames consist of information about objects. For a given frame there are various slots, and for each slot there are various facets, each containing various data. Direct analogical representation is defined as a class of representation which represents knowledge in a natural analog manner, allowing observation of facts in many cases to be achieved quickly and easily compared to deduction. Architecture of systems applied to accelerator control is then described

  3. Challenges in tissue engineering - towards cell control inside artificial scaffolds.

    Science.gov (United States)

    Emmert, M; Witzel, P; Heinrich, D

    2016-05-11

    Control of living cells is vital for the survival of organisms. Each cell inside an organism is exposed to diverse external mechano-chemical cues, all coordinated in a spatio-temporal pattern triggering individual cell functions. This complex interplay between external chemical cues and mechanical 3D environments is translated into intracellular signaling loops. Here, we describe how external mechano-chemical cues control cell functions, especially cell migration, and influence intracellular information transport. In particular, this work focuses on the quantitative analysis of (1) intracellular vesicle transport to understand intracellular state changes in response to external cues, (2) cellular sensing of external chemotactic cues, and (3) the cells' ability to migrate in 3D structured environments, artificially fabricated to mimic the 3D environment of tissue in the human body. PMID:27139622

  4. Artificial Intelligence SVC Based Control of Two Machine Transmission System

    Directory of Open Access Journals (Sweden)

    Reza Bayat

    2013-07-01

    Full Text Available The main target in this paper is to present, design fuzzy logic controller (FLC applied to static var compensator (SVC on two machine transmission system to improve transient stability and rapid damping oscillations of synchronous generators, when power generators sudden changes occur.stability that also played important role in power systems. static var compensator with fuzzy logic controller (SVCFLC is a new control strategy can help improve transient stability.The effect of three phase fault causes instability on power system. By and large, it is very difficult to control machine speeds ,rotor angle and voltage during three-phase fault.SVCFLC is a voltage stablizer using three static var compensator which are controlled by SVC with fuzzy logic controller(FLC.The FLC is an effective device for transient stability of two-mashine transmission system. The nonlinear model dynamic formulation problem in unstable system can be solved by using artificial intelligence theorem. Fuzzy logic theory is used to improve the system stability . simulation results of three-phase fault in power system show that SVCFLC caused to increase the stability and damp out the oscillation of machine, compared with effective of SVC in the presence of power system stabilizer(PSS.

  5. Design techniques for mutlivariable flight control systems

    Science.gov (United States)

    1981-01-01

    Techniques which address the multi-input closely coupled nature of advanced flight control applications and digital implementation issues are described and illustrated through flight control examples. The techniques described seek to exploit the advantages of traditional techniques in treating conventional feedback control design specifications and the simplicity of modern approaches for multivariable control system design.

  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. 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

  8. 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.

  9. Fault diagnosis in nuclear power plants using an artificial neural network technique

    International Nuclear Information System (INIS)

    Application of artificial intelligence (AI) computational techniques, such as expert systems, fuzzy logic, and neural networks in diverse areas has taken place extensively. In the nuclear industry, the intended goal for these AI techniques is to improve power plant operational safety and reliability. As a computerized operator support tool, the artificial neural network (ANN) approach is an emerging technology that currently attracts a large amount of interest. The ability of ANNs to extract the input/output relation of a complicated process and the superior execution speed of a trained ANN motivated this study. The goal was to develop neural networks for sensor and process faults diagnosis with the potential of implementing as a component of a real-time operator support system LYDIA, early sensor and process fault detection and diagnosis

  10. 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...... 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....

  11. 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.

  12. Making smart cities smarter using artificial intelligence techniques for smarter mobility

    OpenAIRE

    Vázquez Salceda, Javier; Álvarez Napagao, Sergio; Tejeda Gómez, José Arturo; Oliva Felipe, Luis Javier; Garcia Gasulla, Dario; Gómez Sebastià, Ignasi; Codina Busquet, Víctor

    2014-01-01

    The term Smart City is tipically applied to urban and metropolitan areas where Information and Communication Technologies provide ways to enable social, cultural and urban development, improving social and political capacities and/or efficiency. In this paper we will show the potential of Artificial Intelligence techniques for augmenting ICT solutions to both increase the cities competiveness but also the active participation of citizens in those processes, making Smart Cities smarter. As exa...

  13. 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.

  14. Investigations into Some Biochemical Processes by the Use of an Artificial Rumen Technique

    International Nuclear Information System (INIS)

    To apply the artificial rumen technique to studies concerning food utilization in ruminants, experiments were conducted with two semi-permeable apparatuses that differed somewhat in their construction. The artificial rumen type I was similar to one already described, and type II was a modification of an apparatus already used. The following analyses were made to determine the digestibility of alfalfa meal: total production of volatile fatty acids, the percentage of organic material and the digestibility of crude fibre. The utilizability of carbohydrates can be evaluated by the production of volatile fatty acids and by the digestibility of cellulose and crude fibre, while microbial protein production can be estimated by the organic binding of sulphate. It was found that apparatus type II showed a better digestibility of alfalfa meal, used less alfalfa meal in a test run, and was easier to handle than the type I apparatus. Three apparatuses of artificial rumen type II were used to examine the digestibility of alfalfa meal in phosphate and sodium-deficient situations produced by exchange dialysis and the use of low phosphate and sodium artificial saliva. It was found that the deficiency of phosphate and sodium led to a reduced production of volatile fatty acids and a lower digestibility of cellulose and crude fibre. There was also a decrease of the organic binding of sulphate. It was interesting to note that the decrease of the digestibility of alfalfa meal was greater with a sodium deficiency than with a phosphate deficiency. (author)

  15. 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.

  16. 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 constr...... transfer method to prepare vesicles, the base for the development of a protocol to induce fission in artificial cell may be available....

  17. Artificial Neural Network Based Control Strategies for Paddy Drying Process

    Directory of Open Access Journals (Sweden)

    Shekhar F. Lilhare

    2014-10-01

    Full Text Available Paddy drying process depends upon ambient conditions, paddy quality, temperature and mass of hot drying air. Existing techniques of paddy drying process are highly nonlinear. In this paper, a neural network based automated controller for paddy drying is designed. The designed controller manages the steam temperature and blower motor speed to achieve constant paddy drying time. A Layer recurrent neural network is adopted for the controller. Atmospheric conditions such as temperature and humidity along with the size of the paddy are used as input to the network. Experimental results show that the developed controller can be used to control the paddy drying process. Implementation of developed controller will help in controlling the drying time at almost constant value which will definitely improve the quality of rice.

  18. A NEW RULE-BASED APPROACH FOR COMPUTER CHESS PROGRAMMING USING GP-ARTIFICIAL TECHNIQUES : PECP

    OpenAIRE

    HANEDAN, Y.Güney; SERTBAŞ, Ahmet

    2012-01-01

    In this paper, we use a brand new chess engine programming technique which we name PECP (Positional Evolutionary Chess Programming), that brings the Artificial Intelligence and Genetic Programming approaches together, to construct a chess endgame analyzing engine. Throughout the paper, the technique and the algorithm are discussed in detail. Also,  using PECP, an  example program (RETI V1.0)  aimed to prove the correctness and performance of the rule-based theory and algorithm is written in P...

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

    International Nuclear Information System (INIS)

    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.

  20. 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…

  1. Artificial neural networks: Principle and application to model based control of drying systems -- A review

    Energy Technology Data Exchange (ETDEWEB)

    Thyagarajan, T.; Ponnavaikko, M. [Crescent Engineering Coll., Madras (India); Shanmugam, J. [Madras Inst. of Tech. (India); Panda, R.C.; Rao, P.G. [Central Leather Research Inst., Madras (India)

    1998-07-01

    This paper reviews the developments in the model based control of drying systems using Artificial Neural Networks (ANNs). Survey of current research works reveals the growing interest in the application of ANN in modeling and control of non-linear, dynamic and time-variant systems. Over 115 articles published in this area are reviewed. All landmark papers are systematically classified in chronological order, in three distinct categories; namely, conventional feedback controllers, model based controllers using conventional methods and model based controllers using ANN for drying process. The principles of ANN are presented in detail. The problems and issues of the drying system and the features of various ANN models are dealt with up-to-date. ANN based controllers lead to smoother controller outputs, which would increase actuator life. The paper concludes with suggestions for improving the existing modeling techniques as applied to predicting the performance characteristics of dryers. The hybridization techniques, namely, neural with fuzzy logic and genetic algorithms, presented, provide, directions for pursuing further research for the implementation of appropriate control strategies. The authors opine that the information presented here would be highly beneficial for pursuing research in modeling and control of drying process using ANN. 118 refs.

  2. Structural investigation and simulation of acoustic properties of some tellurite glasses using artificial intelligence technique

    International Nuclear Information System (INIS)

    Research highlights: → Simulation the acoustic properties of some tellurite glasses using one of the artificial intelligence techniques (artificial neural network). → The glass network is strengthened by enhancing the linkage of Te-O chains. The tellurite network will also come to homogenization, because of uniform distribution of Nb5+ ions among the Te-O chains, though some of the tellurium-oxide polyhedra still link each other in edge sharing. → Excellent agreements between the measured values and the predicted values were obtained for over 50 different tellurite glass compositions. → The model we designed gives a better agreement as compared with Makishima and Machenzie model. - Abstract: The developments in the field of industry raise the need for simulating the acoustic properties of glass materials before melting raw material oxides. In this paper, we are trying to simulate the acoustic properties of some tellurite glasses using one of the artificial intelligence techniques (artificial neural network). The artificial neural network (ANN) technique is introduced in the current study to simulate and predict important parameters such as density, longitudinal and shear ultrasonic velocities and elastic moduli (longitudinal and shear moduli). The ANN results were found to be in successful good agreement with those experimentally measured parameters. Then the presented ANN model is used to predict the acoustic properties of some new tellurite glasses. For this purpose, four glass systems xNb2O5-(1 - x)TeO2, 0.1PbO-xNb2O5-(0.9 - x)TeO2, 0.2PbO-xNb2O5-(0.8 - x)TeO2 and 0.05Bi2O3-xNb2O5-(0.95 - x)TeO2 were prepared using melt quenching technique. The results of ultrasonic velocities and elastic moduli showed that the addition of Nb2O5 as a network modifier provides oxygen ions to change [TeO4] tbps into [TeO3] tps.

  3. Nuclear power plant monitoring and fault diagnosis methods based on the artificial intelligence technique

    International Nuclear Information System (INIS)

    The main objective of this paper is to develop an advanced diagnosis system based on the artificial intelligence technique to monitor the operation and to improve the operational safety of nuclear power plants. Three different methods have been elaborated in this study: an artificial neural network local diagnosis (NNds) scheme that acting at the component level discriminates between normal and abnormal transients, a model-based diagnostic reasoning mechanism that combines a physical causal network model-based knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge. Although the three methods have been developed and verified independently, they are highly correlated and, when connected together, form a effective and robust diagnosis and monitoring tool. (authors)

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

    Science.gov (United States)

    Ramseyer, Craig A.; Mote, Thomas L.

    2016-01-01

    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.

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

    OpenAIRE

    K. Selvi; R.M. Suresh

    2014-01-01

    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 s...

  6. 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.

  7. 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.

  8. The artificial-free technique along the objective direction for the simplex algorithm

    International Nuclear Information System (INIS)

    The simplex algorithm is a popular algorithm for solving linear programming problems. If the origin point satisfies all constraints then the simplex can be started. Otherwise, artificial variables will be introduced to start the simplex algorithm. If we can start the simplex algorithm without using artificial variables then the simplex iterate will require less time. In this paper, we present the artificial-free technique for the simplex algorithm by mapping the problem into the objective plane and splitting constraints into three groups. In the objective plane, one of variables which has a nonzero coefficient of the objective function is fixed in terms of another variable. Then it can split constraints into three groups: the positive coefficient group, the negative coefficient group and the zero coefficient group. Along the objective direction, some constraints from the positive coefficient group will form the optimal solution. If the positive coefficient group is nonempty, the algorithm starts with relaxing constraints from the negative coefficient group and the zero coefficient group. We guarantee the feasible region obtained from the positive coefficient group to be nonempty. The transformed problem is solved using the simplex algorithm. Additional constraints from the negative coefficient group and the zero coefficient group will be added to the solved problem and use the dual simplex method to determine the new optimal solution. An example shows the effectiveness of our algorithm

  9. Simulation and prediction for energy dissipaters and stilling basins design using artificial intelligence technique

    Directory of Open Access Journals (Sweden)

    Mostafa Ahmed Moawad Abdeen

    2015-12-01

    Full Text Available Water with large velocities can cause considerable damage to channels whose beds are composed of natural earth materials. Several stilling basins and energy dissipating devices have been designed in conjunction with spillways and outlet works to avoid damages in canals’ structures. In addition, lots of experimental and traditional mathematical numerical works have been performed to profoundly investigate the accurate design of these stilling basins and energy dissipaters. The current study is aimed toward introducing the artificial intelligence technique as new modeling tool in the prediction of the accurate design of stilling basins. Specifically, artificial neural networks (ANNs are utilized in the current study in conjunction with experimental data to predict the length of the hydraulic jumps occurred in spillways and consequently the stilling basin dimensions can be designed for adequate energy dissipation. The current study showed, in a detailed fashion, the development process of different ANN models to accurately predict the hydraulic jump lengths acquired from different experimental studies. The results obtained from implementing these models showed that ANN technique was very successful in simulating the hydraulic jump characteristics occurred in stilling basins. Therefore, it can be safely utilized in the design of these basins as ANN involves minimum computational and financial efforts and requirements compared with experimental work and traditional numerical techniques such as finite difference or finite elements.

  10. Artificial intelligence-based control system for the analysis of metal casting properties

    Directory of Open Access Journals (Sweden)

    E. Mares

    2010-06-01

    Full Text Available Purpose: The metal casting process requires testing equipment that along with customized computer software properly supports the analysis of casting component characteristic properties. Due to the fact that this evaluation process involves the control of complex and multi-variable melting, casting and solidification factors, it is necessary to develop dedicated software.Design/methodology/approach: The integration of Statistical Process Control methods and Artificial Intelligence techniques (Case-Based Reasoning into Thermal Analysis Data Acquisition Software (NI LabView was developed to analyze casting component properties. The thermal data was tested in terms of accuracy, reliability and timeliness in order to secure metal casting process effectiveness.Findings: Quantitative values were defined as “Low”, “Medium” and “High” to assess the level of improvement in the metal casting analysis by means of the Artificial Intelligence-Based Control System (AIBCS. The traditional process was used as a reference to measure such improvement. As a result, the accuracy, reliability and timeliness were significantly increased to the “High” level.Research limitations/implications: Presently, the AIBCS predicts a limited number of casting properties. Due to its flexible design more properties could be added.Practical implications: The AIBCS has been successfully used at the Ford/Nemak Windsor Aluminum Plant (WAP to analyze Al casting properties of the engine blocks.Originality/value: The metal casting research community has immensely benefited from these developed information technologies that support the metal casting process.

  11. Implementation of Artificial Intelligence Techniques for Steady State Security Assessment in Pool Market

    Directory of Open Access Journals (Sweden)

    I. S. Saeh

    2009-03-01

    Full Text Available Various techniques have been implemented to include steady state securityassessment in the analysis of trading in deregulated power system, howevermost of these techniques lack requirements of fast computational time withacceptable accuracy. The problem is compounded further by the requirements toconsider bus voltages and thermal line limits. This work addresses the problemby presenting the analysis and management of power transaction between powerproducers and customers in the deregulated system using the application ofArtificial Intelligence (AI techniques such as Neural Network (ANN, DecisionTree (DT techniques and Adaptive Network based Fuzzy Inference System(ANFIS. Data obtained from Newton Raphson load flow analysis method areused for the training and testing purposes of the proposed techniques and alsoas comparison in term of accuracy against the proposed techniques. The inputvariables to the AI systems are loadings of the lines and the voltage magnitudesof the load buses. The algorithms are initially tested on the 5 bus system andfurther verified on the IEEE 30 57 and 118 bus test system configured as pooltrading models. By comparing the results, it can be concluded that ANNtechnique is more accurate and better in term of computational time takencompared to the other two techniques. However, ANFIS and DT’s can be moreeasily implemented for practical applications. The newly developed techniquescan further improve security aspects related to the planning and operation ofpool-type deregulated system.

  12. Modern control techniques for accelerators

    Energy Technology Data Exchange (ETDEWEB)

    Goodwin, R.W.; Shea, M.F.

    1984-05-01

    Beginning in the mid to late sixties, most new accelerators were designed to include computer based control systems. Although each installation differed in detail, the technology of the sixties and early to mid seventies dictated an architecture that was essentially the same for the control systems of that era. A mini-computer was connected to the hardware and to a console. Two developments have changed the architecture of modern systems: (a) the microprocessor and (b) local area networks. This paper discusses these two developments and demonstrates their impact on control system design and implementation by way of describing a possible architecture for any size of accelerator. Both hardware and software aspects are included.

  13. 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.

  14. Controlled breeding and artificial insemination of Angora goats in Turkey

    International Nuclear Information System (INIS)

    Experiments were conducted to obtain basic information on the response of the Angora goat to some reproductive management strategies: a comparison of the efficacy of intravaginal progestagen sponge (MAP) and PGF2α (Lutalyse or Prosolvin) to induce a synchronized oestrus during the transition period from anoestrus to oestrus; the application of AI with either fresh or frozen-thawed semen; and the evaluation of the effects of these treatments on fertility. Thirty mature Angora does, aged 3-4 years, were synchronized with MAP, PGF2α (Lutalyse) and the presence of the male (10 animals per treatment): 90%, 80% and 80% respectively of the does were synchronized within 50 +- 4.9 (SD) h, 64.5 +- 14.3 (SD) h and 7.5 +- 3.4 (SD) days respectively and were artificially inseminated with 0.1 mL fresh undiluted semen at least twice per animal. Subsequent conception rates were 66.7%, 100% and 75%, respectively. Washed semen was frozen using skimmed milk as diluent and the viability of this frozen-thawed semen was tested on 15 does at a natural oestrus. Another 11 does were inseminated with frozen-thawed unwashed semen following synchronization of oestrus with PGF2α (Prosolvin); the conception rates were 53.3% and 63.6%, respectively. The use of frozen-thawed semen is thus an effective method when synchronization of oestrus of large numbers of Angora goats is used in a controlled breeding programme. (author). 30 refs, 3 figs, 2 tabs

  15. 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.

  16. 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

    2016-01-01

    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. PMID:27314397

  17. 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.

  18. Artificial neural networks application in duplex/triplex elevator group control system:

    OpenAIRE

    Imrak, C. Erdem

    2008-01-01

    Artificial neural networks can offer the better solution to the passenger call distribution problem when compared to the conventional elevator control systems. Therefore, the application of neural networks in elevator group control system is discussed. The significance of introducing artificial neural networks is presented. Elevator group control systems with neural networks can predict the next stopping floors to stop by considering what has been learnt by processing the changes in passenger...

  19. 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.

  20. Communications and control for electric power systems: Power system stability applications of artificial neural networks

    Science.gov (United States)

    Toomarian, N.; Kirkham, Harold

    1994-01-01

    This report investigates the application of artificial neural networks to the problem of power system stability. The field of artificial intelligence, expert systems, and neural networks is reviewed. Power system operation is discussed with emphasis on stability considerations. Real-time system control has only recently been considered as applicable to stability, using conventional control methods. The report considers the use of artificial neural networks to improve the stability of the power system. The networks are considered as adjuncts and as replacements for existing controllers. The optimal kind of network to use as an adjunct to a generator exciter is discussed.

  1. 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. PMID:24114889

  2. 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. PMID:25685507

  3. 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.

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

    OpenAIRE

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

    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 centr...

  5. 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.

  6. Evaluation of artificial neural network techniques for flow forecasting in the River Yangtze, China

    Directory of Open Access Journals (Sweden)

    C. W. Dawson

    2002-01-01

    Full Text Available While engineers have been quantifying rainfall-runoff processes since the mid-19th century, it is only in the last decade that artificial neural network models have been applied to the same task. This paper evaluates two neural networks in this context: the popular multilayer perceptron (MLP, and the radial basis function network (RBF. Using six-hourly rainfall-runoff data for the River Yangtze at Yichang (upstream of the Three Gorges Dam for the period 1991 to 1993, it is shown that both neural network types can simulate river flows beyond the range of the training set. In addition, an evaluation of alternative RBF transfer functions demonstrates that the popular Gaussian function, often used in RBF networks, is not necessarily the ‘best’ function to use for river flow forecasting. Comparisons are also made between these neural networks and conventional statistical techniques; stepwise multiple linear regression, auto regressive moving average models and a zero order forecasting approach. Keywords: Artificial neural network, multilayer perception, radial basis function, flood forecasting

  7. A COMPARATIVE ANALYSIS OF OPTIMIZATION TECHNIQUES FOR ARTIFICIAL NEURAL NETWORK IN BIO MEDICAL APPLICATIONS

    Directory of Open Access Journals (Sweden)

    V. Saishanmuga Raja

    2014-01-01

    Full Text Available In this study we compare the performance of three evolutionary algorithms such as Genetic Algorithm (GA Particle Swarm Optimization (PSO and Ant-Colony Optimization (ACO which are used to optimize the Artificial Neural Network (ANN. Optimization of Neural Networks improves speed of recall and may also improve the efficiency of training. Here we have used the Ant colony optimization, Particle Swarm Optimization and Genetic Algorithm to optimize the artificial neural networks for applications in medical image processing (extraction and compression. The aim of developing such algorithms is to arrive at near-optimum solutions to large-scale optimization problems, for which traditional mathematical techniques may fail. This study compares the efficiency and results of the three evolutionary algorithms. We have compared these algorithms based on processing time, accuracy and time taken to train Neural Networks. The results show that the Genetic Algorithm outperformed the other two algorithms. This study helps researchers to get an idea of selecting an optimization algorithm for configuring a neural network.

  8. Insect control by using sterile male technique

    International Nuclear Information System (INIS)

    The sterile male technique used in insect control is presented as an alternative for chemical control of pest insect. Description and effects of sterile male technique on morphology and physiology of different classes of pest insects are given. Prerequisite conditions necessary to work out SMT are presented. As an example of the application of this technique: control of Ephestia Cartella is studied. Gamma radiation effects on deformation, sterilization and longevity of the male insect as well as fecondity and fertility with respects of gamma irradiation are presented. 11 refs. 3 tabs

  9. Three-Level Direct Torque Control Based on Artificial Neural Network of Double Star Synchronous Machine

    Directory of Open Access Journals (Sweden)

    Elakhdar BENYOUSSEF

    2014-02-01

    Full Text Available This paper presents a direct torque control strategy for double star synchronous machine fed by two three-level inverters. The analysis of the torque and the stator flux linkage reference frame shows that the concept of direct torque control can be extended easily to double star synchronous machine. The proposed approach consists to replace the switching tables by one artificial neural networks controller. The output switching states vectors of the artificial neural networks controller are used to control the two three-level inverters. Simulations results are given to show the effectiveness and the robustness of the suggested control method.

  10. An Open Loop Feed-Forward Control Scheme for Bioinspired Artificial Hair Cell Sensors

    OpenAIRE

    Crowley, Kevin Michael

    2015-01-01

    This research documents the creation and use of an open-loop feed forward control scheme designed to manipulate the DC potential across lipid bilayer membranes in artificial hair cell sensors. Inspired by the human cochlea's non-linear gain phenomenon, whereby the cochlea can increase or decrease the effective gain of the auditory system, this controller is the first step in developing more sophisticated signal processing schemes for use with future bio-inspired artificial hair cell developme...

  11. The influence of artificial recharge for controlling land subsidence on groundwater quality in Shanghai area

    International Nuclear Information System (INIS)

    Shanghai City is supplied mainly by river water, therefore, quality of tap water is not good enough. In this connection it has been decided to exploit high quality groundwater from deep confined aquifer. This drinking water will be supplied separately form the normal tap water. Groundwater in Quaternary aquifers in Shanghai area up to date was exploited mainly for industrial use. Since 1965, the artificial recharge of aquifers using tap water has been carried out in order to control land subsidence. The influence of artificial recharge on groundwater quality thus should be assessed if groundwater will be used as drinking water. For this purpose, isotope techniques, especially tritium measurement, were used in combination with ICP-MS trace element analyses, and GC/MSD analyses for natural organic tracers. 36 samples from production and injection wells, 2 tap water samples, 3 samples from Huangpu River and Yangtze River were taken in 1998 and 1999. Results obtained show, that tritium content is sensitive to presence of artificially recharged water. Some major chemical constituents, such as sulphate and bicarbonate, some volatile organic compounds, such as chloroform, bromo-dichloro-methane and 1,2-dichloro-ethane, are also good for tracing recharge water. Some trace elements in water samples, such as Li, Cr, which may derived from the base rock, show relatively high content in deep groundwater. While some other trace elements, such as Pb, Mn and Ni, are obviously from the wastewater. They are characteristic for surface water. Based on results obtained for these available indicators, it was concluded, that a few production wells of the IV layer, which is the major layer for drinking water exploitation, are in the sphere of influence of injection wells. (author)

  12. Use of artificial intelligence techniques for visual inspection systems prototyping. Application to magnetoscopy

    International Nuclear Information System (INIS)

    The automation of visual inspection is a complex task that requires collaboration between experts, for example inspection specialist, vision specialist. on-line operators. Solving such problems through prototyping promotes this collaboration: the use of a non specific programming environment allows rapid, concrete checking of method validity, thus leading incrementally to the final system. In this context, artificial intelligence techniques permit easy, extensible, and modular design of the prototype, together with heuristic solution building. We define and achieve the SPOR prototyping environment, based on object-oriented programming and rules-basis managing. The feasibility and the validity of an heuristic method for automated visual inspection in fluoroscopy have been proved through prototyping in SPOR. (author)

  13. Integration of artificial intelligence and numerical optimization techniques for the design of complex aerospace systems

    International Nuclear Information System (INIS)

    A new software system called Engineous combines artificial intelligence and numerical methods for the design and optimization of complex aerospace systems. Engineous combines the advanced computational techniques of genetic algorithms, expert systems, and object-oriented programming with the conventional methods of numerical optimization and simulated annealing to create a design optimization environment that can be applied to computational models in various disciplines. Engineous has produced designs with higher predicted performance gains that current manual design processes - on average a 10-to-1 reduction of turnaround time - and has yielded new insights into product design. It has been applied to the aerodynamic preliminary design of an aircraft engine turbine, concurrent aerodynamic and mechanical preliminary design of an aircraft engine turbine blade and disk, a space superconductor generator, a satellite power converter, and a nuclear-powered satellite reactor and shield. 23 refs

  14. Artificial intelligence search techniques for optimization of the cold source geometry

    International Nuclear Information System (INIS)

    Most optimization studies of cold neutron sources have concentrated on the numerical prediction or experimental measurement of the cold moderator optimum thickness which produces the largest cold neutron leakage for a given thermal neutron source. Optimizing the geometrical shape of the cold source, however, is a more difficult problem because the optimized quantity, the cold neutron leakage, is an implicit function of the shape which is the unknown in such a study. We draw an analogy between this problem and a state space search, then we use a simple Artificial Intelligence (AI) search technique to determine the optimum cold source shape based on a two-group, r-z diffusion model. We implemented this AI design concept in the computer program AID which consists of two modules, a physical model module and a search module, which can be independently modified, improved, or made more sophisticated. 7 refs., 1 fig

  15. An alarm processing system for a nuclear power plant using artificial intelligence techniques

    International Nuclear Information System (INIS)

    This paper reports on an alarm processing system (APS) developed that uses artificial intelligence techniques to help operators to make decisions. Alarms in nuclear power plants are classified into generalized and special alarms. Generalized alarms are further classified into global and local alarms. For each type of alarm, the specific processing rules are applied to filter and suppress unnecessary and potentially misleading alarms. The processing for the generalized alarms is based on model-based reasoning. The special alarms are processed by the cause-consequence check rules. The priorities of alarms are determined according to both the plant state and the consistencies among the alarms. This APS is built on a workstation using the Prolog language

  16. Designed strength identification of concrete by ultrasonic signal processing based on artificial intelligence techniques.

    Science.gov (United States)

    Kim, Se-Dong; Shin, Dong-Hwan; Lim, Lea-Mook; Lee, Jin; Kim, Sung-Hwan

    2005-07-01

    This paper presents a pattern recognition method to identify the designed strength of concrete by evidence accumulation based on artificial intelligence techniques with multiple feature parameters. Concrete specimens in this experiment, which were designed to have the strengths of 180, 210, 240, 300, and 400 kg/cm2, respectively, have been considered. Variance, zero-crossing, mean frequency, autoregressive (AR) model coefficients, and linear cepstrum coefficients are extracted as feature parameters from ultrasonic signals of concretes. Pattern recognition is carried out through the evidence accumulation procedure using the distances measured with reference parameters. A fuzzy mapping function is introduced to transform the distance for the application of the evidence accumulation method. Results are presented to support the feasibility of the suggested approach for concrete pattern identification. PMID:16212253

  17. 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

  18. Evolving Spiking Neural Networks for Control of Artificial Creatures

    OpenAIRE

    Arash Ahmadi

    2013-01-01

    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 survi...

  19. 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.

  20. Detection of apnea using a short-window FFT technique and an artificial neural network

    Science.gov (United States)

    Waldemark, Karina E.; Agehed, Kenneth I.; Lindblad, Thomas; Waldemark, Joakim T. A.

    1998-03-01

    Sleep apnea is characterized by frequent prolonged interruptions of breathing during sleep. This syndrome causes severe sleep disorders and is often responsible for development of other diseases such as heart problems, high blood pressure and daytime fatigue, etc. After diagnosis, sleep apnea is often successfully treated by applying positive air pressure (CPAP) to the mouth and nose. Although effective, the (CPAP) equipment takes up a lot of space and the connected mask causes a lot of inconvenience for the patients. This raised interest in developing new techniques for treatment of sleep apnea syndrome. Several studies have indicated that electrical stimulation of the hypoglossal nerve and muscle in the tongue may be a useful method for treating patients with severe sleep apnea. In order to be able to successfully prevent the occurrence of apnea it is necessary to have some technique for early and fast on-line detection or prediction of the apnea events. This paper suggests using measurements of respiratory airflow (mouth temperature). The signal processing for this task includes the use of a short window FFT technique and uses an artificial back propagation neural net to model or predict the occurrence of apneas. The results show that early detection of respiratory interruption is possible and that the delay time for this is small.

  1. 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

  2. Multirobot Lunar Excavation and ISRU Using Artificial-Neural-Tissue Controllers

    International Nuclear Information System (INIS)

    Automation of site preparation and resource utilization on the Moon with teams of autonomous robots holds considerable promise for establishing a lunar base. Such multirobot autonomous systems would require limited human support infrastructure, complement necessary manned operations and reduce overall mission risk. We present an Artificial Neural Tissue (ANT) architecture as a control system for autonomous multirobot excavation tasks. An ANT approach requires much less human supervision and pre-programmed human expertise than previous techniques. Only a single global fitness function and a set of allowable basis behaviors need be specified. An evolutionary (Darwinian) selection process is used to 'breed' controllers for the task at hand in simulation and the fittest controllers are transferred onto hardware for further validation and testing. ANT facilitates 'machine creativity', with the emergence of novel functionality through a process of self-organized task decomposition of mission goals. ANT based controllers are shown to exhibit self-organization, employ stigmergy (communication mediated through the environment) and make use of templates (unlabeled environmental cues). With lunar in-situ resource utilization (ISRU) efforts in mind, ANT controllers have been tested on a multirobot excavation task in which teams of robots with no explicit supervision can successfully avoid obstacles, interpret excavation blueprints, perform layered digging, avoid burying or trapping other robots and clear/maintain digging routes

  3. Multirobot Lunar Excavation and ISRU Using Artificial-Neural-Tissue Controllers

    Science.gov (United States)

    Thangavelautham, Jekanthan; Smith, Alexander; Abu El Samid, Nader; Ho, Alexander; Boucher, Dale; Richard, Jim; D'Eleuterio, Gabriele M. T.

    2008-01-01

    Automation of site preparation and resource utilization on the Moon with teams of autonomous robots holds considerable promise for establishing a lunar base. Such multirobot autonomous systems would require limited human support infrastructure, complement necessary manned operations and reduce overall mission risk. We present an Artificial Neural Tissue (ANT) architecture as a control system for autonomous multirobot excavation tasks. An ANT approach requires much less human supervision and pre-programmed human expertise than previous techniques. Only a single global fitness function and a set of allowable basis behaviors need be specified. An evolutionary (Darwinian) selection process is used to `breed' controllers for the task at hand in simulation and the fittest controllers are transferred onto hardware for further validation and testing. ANT facilitates `machine creativity', with the emergence of novel functionality through a process of self-organized task decomposition of mission goals. ANT based controllers are shown to exhibit self-organization, employ stigmergy (communication mediated through the environment) and make use of templates (unlabeled environmental cues). With lunar in-situ resource utilization (ISRU) efforts in mind, ANT controllers have been tested on a multirobot excavation task in which teams of robots with no explicit supervision can successfully avoid obstacles, interpret excavation blueprints, perform layered digging, avoid burying or trapping other robots and clear/maintain digging routes.

  4. Application and evaluation of the artificial tritium tagging of moisture soil technique in hydrogeological research in Brazil

    International Nuclear Information System (INIS)

    In this work, we apply and make an evaluation the artificial tritium tagging technique of moisture in many kinds of soils for the determination of rainfall infiltration in unsaturated zone. The purpose of this work is the determination of ground water recharge in order to assist evaluating sites for radioactive waste disposal and water resources. From the experimental results obtained, we can conclude that the use of artificial tritium tagging method is an accurate, useful and probably the best available technique to determine ground water recharge. (author)

  5. 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.

  6. Teaching artificial neural systems to drive: Manual training techniques for autonomous systems

    Science.gov (United States)

    Shepanski, J. F.; Macy, S. A.

    1987-01-01

    A methodology was developed for manually training autonomous control systems based on artificial neural systems (ANS). In applications where the rule set governing an expert's decisions is difficult to formulate, ANS can be used to extract rules by associating the information an expert receives with the actions taken. Properly constructed networks imitate rules of behavior that permits them to function autonomously when they are trained on the spanning set of possible situations. This training can be provided manually, either under the direct supervision of a system trainer, or indirectly using a background mode where the networks assimilates training data as the expert performs its day-to-day tasks. To demonstrate these methods, an ANS network was trained to drive a vehicle through simulated freeway traffic.

  7. 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.

  8. 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.

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

    International Nuclear Information System (INIS)

    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 (137Cs) 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)

  11. Measure of pore size in micro filtration polymeric membrane using ultrasonic technique and artificial neural networks

    International Nuclear Information System (INIS)

    This work presents a study of the pore size in micro filtration polymeric membranes, used in the nuclear area for the filtration of radioactive liquid effluent, in the residual water treatment of the petrochemical industry, in the electronic industry for the ultrapure water production for the manufacture of conductors and laundering of microcircuits and in many other processes of separation. Diverse processes for measures of pores sizes in membranes exist, amongst these, electronic microscopy, of bubble point and mercury intrusion porosimetry, however the majority of these uses destructive techniques, of high cost or great time of analysis. The proposal of this work is to measure so great of pore being used ultrasonic technique in the time domain of the frequency and artificial neural networks. A receiving/generator of ultrasonic pulses, a immersion transducer of 25 MHz was used, a tank of immersion and microporous membranes of pores sizes of 0,2 μm, 0,4 μm, 0,6 μm, 8 μm, 10 μm and 12 μm. The ultrasonic signals after to cover the membrane, come back to the transducer (emitting/receiving) bringing information of the interaction of the signal with the membranes. These signals had been used for the training of neural networks, and these had supplied the necessary precision the distinction of the same ones. Soon after, technique with the one of electronic microscopy of sweepings was made the comparison of this. The experiment showed very resulted next to the results gotten with the MEV, what it indicated that the studied technique is ideal for measure of pore size in membranes for being not destructive and of this form to be able to be used also on-line of production. (author)

  12. Process sensors characterization based on noise analysis technique and artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Mesquita, Roberto N. de; Perillo, Sergio R.P.; Santos, Roberto C. dos [Instituto de Pesquisas Energeticas e Nucleares (IPEN), Sao Paulo, SP (Brazil)]. E-mail: rnavarro@ipen.br; sperillo@ipen.br; rcsantos@ipen.br

    2005-07-01

    The time response of pressure and temperature sensors from the Reactor Protection System (RPS) is a requirement that must be satisfied in nuclear power plants, furthermore is an indicative of its degradation and its remaining life. The nuclear power industry and others have been eager to implement smart sensor technologies and digital instrumentation concepts to reduce manpower and effort currently spent on testing and calibration. Process parameters fluctuations during normal operation of a reactor are caused by random variations in neutron flux, heat transfer and other sources. The output sensor noise can be considered as the response of the system to an input representing the statistical nature of the underlying process which can be modeled using a time series model. Since the noise signal measurements are influenced by many factors, such as location of sensors, extraneous noise interference, and randomness in temperature and pressure fluctuation - the quantitative estimate of the time response using autoregressive noise modeling is subject to error. This technique has been used as means of sensor monitoring. In this work a set of pressure sensors installed in one experimental loop adapted from a flow calibration setup is used to test and analyze signals in a new approach using artificial intelligence techniques. A set of measurements of dynamic signals in different experimental conditions is used to distinguish and identify underlying process sources. A methodology that uses Blind Separation of Sources with a neural networks scheme is being developed to improve time response estimate reliability in noise analysis. (author)

  13. Process sensors characterization based on noise analysis technique and artificial intelligence

    International Nuclear Information System (INIS)

    The time response of pressure and temperature sensors from the Reactor Protection System (RPS) is a requirement that must be satisfied in nuclear power plants, furthermore is an indicative of its degradation and its remaining life. The nuclear power industry and others have been eager to implement smart sensor technologies and digital instrumentation concepts to reduce manpower and effort currently spent on testing and calibration. Process parameters fluctuations during normal operation of a reactor are caused by random variations in neutron flux, heat transfer and other sources. The output sensor noise can be considered as the response of the system to an input representing the statistical nature of the underlying process which can be modeled using a time series model. Since the noise signal measurements are influenced by many factors, such as location of sensors, extraneous noise interference, and randomness in temperature and pressure fluctuation - the quantitative estimate of the time response using autoregressive noise modeling is subject to error. This technique has been used as means of sensor monitoring. In this work a set of pressure sensors installed in one experimental loop adapted from a flow calibration setup is used to test and analyze signals in a new approach using artificial intelligence techniques. A set of measurements of dynamic signals in different experimental conditions is used to distinguish and identify underlying process sources. A methodology that uses Blind Separation of Sources with a neural networks scheme is being developed to improve time response estimate reliability in noise analysis. (author)

  14. 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.

  15. Application and evaluation of the artificial tritium tagging of moisture soil technique in hydrogeological research in Brazil

    International Nuclear Information System (INIS)

    In this work, we apply and make an evaluation of the technique of artificial tritium tagging of moisture in many kinds of soils for the determination of rainfall infiltration in unsaturated zone. The purpose of this work is the determination of ground water recharge in order to assist in evaluation of sites for the disposal of radioactive wastes and also to assist in the evaluation of water resources. With this thesis, we intend to present a new choice for the measuring of local ground water recharge rate, due to availability of artificial tritium. From the experimental results obtained, we can conclude that the use of artificial tritium tagging method is an accurate, useful and probably the best available technique to determine ground water recharge. (author)

  16. Control Power Optimization using Artificial Intelligence for Hybrid Wing Body Aircraft

    OpenAIRE

    Chhabra, Rupanshi

    2015-01-01

    Traditional methods of control allocation optimization have shown difficulties in exploiting the full potential of controlling a large array of control surfaces. This research investigates the potential of employing artificial intelligence methods like neurocomputing to the control allocation optimization problem of Hybrid Wing Body (HWB) aircraft concepts for minimizing control power, hinge moments, and actuator forces, while keeping the system weights within acceptable limits. The main obje...

  17. On the cost of null-control of an artificial advection-diffusion problem

    OpenAIRE

    Cornilleau, Pierre; Guerrero, Sergio

    2012-01-01

    In this paper we study the null-controllability of an artificial advection-diffusion system in dimension $n$. Using a spectral method, we prove that the control cost goes to zero exponentially when the viscosity vanishes and the control time is large enough. On the other hand, we prove that the control cost tends to infinity exponentially when the viscosity vanishes and the control time is small enough.

  18. 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.

  19. 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.

  20. 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.

  1. Simulation and Control of Turbulence at Tokamaks with Artificial Intelligence Methods

    Directory of Open Access Journals (Sweden)

    Danilo Rastovic

    2012-12-01

    Full Text Available The control of turbulence at tokamaks is very complex problem.The idea is to apply the fuzzy Markovian processes and fuzzy Brownian motions as good approximation of general robust drift kinetic equation. It is obtained by using the artificial neural networks for solving of appropriate advanced control problem. The proof of the appropriate theorem is shown.

  2. 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.

  3. 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..

  4. 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

  5. Artificial intelligence research in particle accelerator control systems for beam line tuning

    Energy Technology Data Exchange (ETDEWEB)

    Pieck, Martin [Los Alamos National Laboratory

    2008-01-01

    Tuning particle accelerators is time consuming and expensive, with a number of inherently non-linear interactions between system components. Conventional control methods have not been successful in this domain and the result is constant and expensive monitoring of the systems by human operators. This is particularly true for the start-up and conditioning phase after a maintenance period or an unexpected fault. In turn, this often requires a step-by-step restart of the accelerator. Surprisingly few attempts have been made to apply intelligent accelerator control techniques to help with beam tuning, fault detection, and fault recovery problems. The reason for that might be that accelerator facilities are rare and difficult to understand systems that require detailed expert knowledge about the underlying physics as well as months if not years of experience to understand the relationship between individual components, particularly if they are geographically disjoint. This paper will give an overview about the research effort in the accelerator community that has been dedicated to the use of artificial intelligence methods for accelerator beam line tuning.

  6. Artificial Intelligence SVC Based Control of Two Machine Transmission System

    OpenAIRE

    Reza Bayat; Hamed ahmadi

    2013-01-01

    The main target in this paper is to present, design fuzzy logic controller (FLC) applied to static var compensator (SVC) on two machine transmission system to improve transient stability and rapid damping oscillations of synchronous generators, when power generators sudden changes occur.stability that also played important role in power systems. static var compensator with fuzzy logic controller (SVCFLC) is a new control strategy can help improve transient stability.The effect of three phase...

  7. 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…

  8. 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.

  9. 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.

  10. Modern insect control: Nuclear techniques and biotechnology

    International Nuclear Information System (INIS)

    The Symposium dealt primarily with genetic methods of insect control, including sterile insect technique (SIT), F1 sterility, compound chromosomes, translocations and conditional lethals. Research and development activities on various aspects of these control technologies were reported by participants during the Symposium. Of particular interest was development of F1 sterility as a practical method of controlling pest Lepidoptera. Genetic methods of insect control are applicable only on an area wide basis. They are species specific and thus do not reduce populations of beneficial insects or cause other environmental problems. Other papers presented reported on the potential use of radiation as a quarantine treatment for commodities in international trade and the use of radioisotopes as ''tags'' in studying insects

  11. Admission Control Techniques for UMTS System

    Directory of Open Access Journals (Sweden)

    P. Kejik

    2010-09-01

    Full Text Available Universal mobile telecommunications system (UMTS is one of the 3rd generation (3G cell phone technologies. The capacity of UMTS is interference limited. Radio resources management (RRM functions are therefore used. They are responsible for supplying optimum coverage, ensuring efficient use of physical resources, and providing the maximum planned capacity. This paper deals with admission control techniques for UMTS. An own UMTS simulation program and several versions of proposed admission control algorithms are presented in this paper. These algorithms are based on fuzzy logic and genetic algorithms. The performance of algorithms is verified via simulations.

  12. Control techniques for invasive alien plants

    OpenAIRE

    Michele de Sá Dechoum; Sílvia Renate Ziller

    2013-01-01

    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. T...

  13. Hierarchical hybrid control of manipulators - Artificial intelligence in LSI.

    Science.gov (United States)

    Greene, P. H.

    1973-01-01

    The need for remotely controlled manipulators and explorers, coupled with emerging large-scale integrated (LSI) circuit technology, foreshadow the dominant role of a style of hybrid control. Systems having many degrees of freedom should be guided and regulated by controllers to which commands are given in purpose-oriented form, to be converted into appropriate machine-oriented signals to effectors for achieving the purpose. In particular, numerical tabulations of functions should be replaced by low-level analog microcircuit realizations of the functions, particularly when feedback can keep errors from piling up. The study is concerned with new problems and organizations that arise in attempting to exploit obvious principles to the fullest degree.

  14. Modeling of artificial stiction in steam turbine control valve

    International Nuclear Information System (INIS)

    The steam turbine control valves play a pivotal role in regulating the output power of the turbine in a commercial nuclear power plant. In this paper the turbine system refers to Ulchin units 3 and 4. The modeling of friction in steam turbine control valve is presented. Instead of a detailed physical model of the control valve friction, the data-driven models are adopted for modeling the friction to obtain an easier friction identification and faster calculation time. Some computational results by using the MARS thermal hydraulic analysis code are presented to show the effect of friction on the total mass flow at the inlet of the high pressure turbine. The computational results demonstrate that the friction will initiate fluctuations on the total mass flow at the turbine inlet

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

    DEFF Research Database (Denmark)

    Bönzli, Eva; Hadorn, Maik; De Lucrezia, Davide; Girke Jørgensen, Mikkel; Hotz, Peter Eggenberger; Hanczyc, Martin; Yomo, Tetsuya

    special class of viral proteins, termed fusogenic peptides, were added to the external medium. In the present work, we intend to develop genetically controlled fusion, fission and exocytosis of vesicles by the synthesis of peptides within vesicles. First, we enclosed synthesized peptides in vesicles to...... induce in a next step fusion of adjacent vesicles, fission and exocytosis of nested vesicles. Second, we will replace the peptides by an enclosed cell-free expression system to internally synthesize fusion peptides. To control the gene expression, different mechanisms are available, e.g. addition of...... fusion, fission and exocytosis....

  16. Stochastic techniques applied to the smoothing treatment of bias and compression of artificial satellite tracking and telemetry data

    Science.gov (United States)

    Orlando, V.

    1983-10-01

    Three procedures related with preprocessing of artificial satellite tracking and telemetry data, developed with the aid of stochastic techniques are presented. The first of them consists of a data smoothing procedure by curve fitting developed by the application of the Kalman filter combined with an adaptive technique of state noise evaluation. The second procedure, developed in order to allow an automatic treatment of bias errors in dynamics systems observation data, makes Kalman filter state estimation possible by direct processing of the bias errors corrupted observations. For this, a dynamic compensation scheme is used. Finally, the third procedure, classified as a data compression procedure, has the objective of obtaining, in certain conditions, a processing speed gain in Kalman filter applications to nonlinear dynamic systems state estimation. Validation tests of the procedures were made by digital computer simulation using simulated data related with a low altitude artificial satellite orbit.

  17. Closed-Loop Control and Advisory Mode Evaluation of an Artificial Pancreatic β Cell: Use of Proportional–Integral–Derivative Equivalent Model-Based Controllers

    Science.gov (United States)

    Percival, Matthew W.; Zisser, Howard; Jovanovič, Lois; Doyle, Francis J.

    2008-01-01

    Background Using currently available technology, it is possible to apply modern control theory to produce a closed-loop artificial β cell. Novel use of established control techniques would improve glycemic control, thereby reducing the complications of diabetes. Two popular controller structures, proportional–integral–derivative (PID) and model predictive control (MPC), are compared first in a theoretical sense and then in two applications. Methods The Bergman model is transformed for use in a PID equivalent model-based controller. The internal model control (IMC) structure, which makes explicit use of the model, is compared with the PID controller structure in the transfer function domain. An MPC controller is then developed as an optimization problem with restrictions on its tuning parameters and is shown to be equivalent to an IMC controller. The controllers are tuned for equivalent performance and evaluated in a simulation study as a closed-loop controller and in an advisory mode scenario on retrospective clinical data. Results Theoretical development shows conditions under which PID and MPC controllers produce equivalent output via IMC. The simulation study showed that the single tuning parameter for the equivalent controllers relates directly to the closed-loop speed of response and robustness, an important result considering system uncertainty. The risk metric allowed easy identification of instances of inadequate control. Results of the advisory mode simulation showed that suitable tuning produces consistently appropriate delivery recommendations. Conclusion The conditions under which PID and MPC are equivalent have been derived. The MPC framework is more suitable given the extensions necessary for a fully closed-loop artificial β cell, such as consideration of controller constraints. Formulation of the control problem in risk space is attractive, as it explicitly addresses the asymmetry of the problem; this is done easily with MPC. PMID:19885240

  18. Biologically Inspired Robotic Arm Control Using an Artificial Neural Oscillator

    Directory of Open Access Journals (Sweden)

    Woosung Yang

    2010-01-01

    Full Text Available We address a neural-oscillator-based control scheme to achieve biologically inspired motion generation. In general, it is known that humans or animals exhibit novel adaptive behaviors regardless of their kinematic configurations against unexpected disturbances or environment changes. This is caused by the entrainment property of the neural oscillator which plays a key role to adapt their nervous system to the natural frequency of the interacted environments. Thus we focus on a self-adapting robot arm control to attain natural adaptive motions as a controller employing neural oscillators. To demonstrate the excellence of entrainment, we implement the proposed control scheme to a single pendulum coupled with the neural oscillator in simulation and experiment. Then this work shows the performance of the robot arm coupled to neural oscillators through various tasks that the arm traces a trajectory. With these, the real-time closed-loop system allowing sensory feedback of the neural oscillator for the entrainment property is proposed. In particular, we verify an impressive capability of biologically inspired self-adaptation behaviors that enables the robot arm to make adaptive motions corresponding to an unexpected environmental variety.

  19. Intelligent process control operator aid -- An artificial intelligence approach

    International Nuclear Information System (INIS)

    This paper describes an approach for designing intelligent process and power plant control operator aids. It is argued that one of the key aspects of an intelligent operator aid is the capability for dynamic procedure synthesis with incomplete definition of initial state, unknown goal states, and the dynamic world situation. The dynamic world state is used to determine the goal, select appropriate plan steps from prespecified procedures to achieve the goal, control the execution of the synthesized plan, and provide for dynamic recovery from failure often using a goal hierarchy. The dynamic synthesis of a plan requires integration of various problems solving capabilities such as plan generation, plan synthesis, plan modification, and failure recovery from a plan. The programming language for implementing the DPS framework provides a convenient tool for developing applications. An application of the DPS approach to a Nuclear Power Plant emergency procedure synthesis is also described. Initial test results indicate that the approach is successful in dynamically synthesizing the procedures. The authors realize that the DPS framework is not a solution for all control tasks. However, many existing process and plant control problems satisfy the requirements discussed in the paper and should be able to benefit from the framework described

  20. Application of Meta-Heuristic Hybrid Artificial Intelligence Techniques for Modeling of Bonding Strength of Plywood Panels

    OpenAIRE

    Demirkır, Cenk; Kahraman, Hamdi Tolga; ÇOLAKOĞLU*, Gürsel

    2014-01-01

    Plywood, which is one of the most important wood based panels, has many usage areas changing from traffic signs to building constructions in many countries. It is known that the high quality plywood panel manufacturing has been achieved with a good bonding under the optimum pressure conditions depending on adhesive type. This is a study of determining the using possibilities of modern meta-heuristic hybrid artificial intelligence techniques such as IKE and AANN methods for prediction of bondi...

  1. Development of a Rain Down Technique to Artificially Infest Hemlocks with the Hemlock Woolly Adelgid, Adelges tsugae

    OpenAIRE

    Jetton, Robert M.; Mayfield, Albert E.; Zaidee L. Powers

    2014-01-01

    The hemlock woolly adelgid Adelges tsugae Annand (Hemiptera: Adelgidae), is a non-native invasive pest that has caused widespread decline and mortality of eastern hemlock (Tsuga canadensis (L.) Carr. (Pinales: Pinaceae)) and Carolina hemlock (T. caroliniana Engelm.) in the eastern United States. Our preliminary experiments evaluated the utility of a rain-down technique to induce artificial infestations of A. tsugae on hemlock seedlings en masse. Experiments were conducted in PVC (1 m3) cages ...

  2. Fault Diagnosis in Process Control Valve Using Artificial Neural Network

    OpenAIRE

    K. Prabakaran; T. Uma Mageshwari; Prakash, D.; A. Suguna

    2013-01-01

    As modern process industries become more complex, the importance to detect and identify the faulty operation of pneumatic process control valves is increasing rapidly. The prior detection of faults leads to avoiding the system shutdown, breakdown, raw material damage and etc. The proposed approach for fault diagnosis comprises of two processes such as fault detection and fault isolation. In fault diagnosis, the difference between the system outputs and model outputs called as residuals are us...

  3. Fault Diagnosis in Process Control Valve Using Artificial Neural Network

    Directory of Open Access Journals (Sweden)

    K. Prabakaran

    2013-05-01

    Full Text Available As modern process industries become more complex, the importance to detect and identify the faulty operation of pneumatic process control valves is increasing rapidly. The prior detection of faults leads to avoiding the system shutdown, breakdown, raw material damage and etc. The proposed approach for fault diagnosis comprises of two processes such as fault detection and fault isolation. In fault diagnosis, the difference between the system outputs and model outputs called as residuals are used to detect and isolate the faults. But in the control valve it is not an easy process due to inherent nonlinearity. The particular values of five measurable quantities from the valve are depend on the commonly occurring faults such as Incorrect supply pressure, Diaphragm leakage and Actuator vent blockage. The correlations between these parameters from the fault values for each operating condition are learned by a multilayer BP Neural Network. The parameter consideration is done through the committee of Development and Application of Methods for Actuator Diagnosis in Industrial Control Systems (DAMADICS. The simulation results using MATLab prove that BP neural network has the ability to detect and identify various magnitudes of the faults and can isolate multiple faults. In addition, it is observed that the network has the ability to estimate fault levels not seen by the network during training.

  4. 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. PMID:24409897

  5. 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.

  6. 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.

  7. OOP techniques for control systems software design

    International Nuclear Information System (INIS)

    The process of software design for nuclear power plants has several stages that must be fulfilled for a successful application. The first deals with the suitability of the concepts being applied to control the process itself, i.e. the control theory approach used, rationale for imposed limits, etc., that could be termed the formal specification generation. The second encompasses the processes of insuring the correctness of the software according to its formal specification. There are several approaches to dealing with these issues being developed worldwide, from the purely analytical to exhaustive testing methods. The purpose of our research effort is to explore and develop new tools for designing and testing control algorithms based in object-oriented programming (OOP) techniques and iconic interfaces. These two technologies will empower the designer by providing powerful yet simple means to introduce faults, investigate their effects and introduce configuration changes. Software development approaches that both encourage and force modularity with explicit interfacing definition could be of great help towards automatic software verification techniques. It is in this context that OOP techniques could play an important role, since they could be thought of as independent units interacting through allowed communication channels. Object classes implementing most common algorithms have been developed and used in our research laboratory computing environment with good results. It is feasible, in principle at least, to design a topology advisor/verifier that parses the control algorithm to detect anomalous configurations. Future research topics include the development of a prototype topology parser to explore its potential applicability in software design. (Author) 6 refs., 2 figs

  8. Research review: Indoor air quality control techniques

    International Nuclear Information System (INIS)

    Techniques for controlling the concentration of radon, formaldehyde, and combustion products in the indoor air are reviewed. The most effective techniques, which are generally based on limiting or reducing indoor pollutant source strengths, can decrease indoor pollutant concentrations by a factor of 3 to 10. Unless the initial ventilation rate is unusually low, it is difficult to reduce indoor pollutant concentrations more than approximately 50% by increasing the ventilation rate of an entire building. However, the efficiency of indoor pollutant control by ventilation can be enhanced through the use of local exhaust ventilation near concentrated sources of pollutants, by minimizing short circuiting of air from supply to exhaust when pollutant sources are dispersed and, in some situations, by promoting a displacement flow of air and pollutants toward the exhaust. Active air cleaning is also examined briefly. Filtration and electrostatic air cleaning for removal of particles from the indoor air are the most practical and effective currently available techniques of air cleaning. 49 refs., 7 figs

  9. Online speed control of a brushless AC servomotor based on artificial neural networks

    OpenAIRE

    PARTAL, Sibel; Şenol, İbrahim; BAKAN, Ahmet Faruk

    2011-01-01

    In this paper, an alternative approach to speed estimation of brushless AC servomotors is presented. Speed control is realized in the following steps. First, the servomotor was mathematically modelled; the driver system was designed and speed control of the servomotor was accomplished with feedback. Next, a network structure representing the electrical and mechanical properties of the servomotor was built via Artificial Neural Network (ANN) and trained with the results of the first ...

  10. 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

  11. Sterile insect technique for tsetse control and eradication

    International Nuclear Information System (INIS)

    The current publication contains the contributions made by scientists who participated in the fourth Co-ordinated Research Programme. A range of topics, covering both field and laboratory activities, was addressed: Eradication of Glossina palpalis palpalis (Robineau-Desvoidy) (Diptera: Glossinidae) from agropastoral land in Central Nigeria by means of the sterile insect technique; Research and development in the IAEA Laboratory at Seibersdorf in support of BICOT for the eradication of Glossina palpalis palpalis; Tsetse fly eradication in Burkina Faso and evaluation of traps and targets; Ecology of Glossina species inhabiting peridomestic agroecosystems in relation to options for tsetse fly control; Population dynamics of Glossina fuscipes fuscipes on Buvuma Island, Lake Victoria, Uganda; Population estimation from mark-recapture data: Equations for a pooled mark system and for pooled data, with applications to a study on island populations of tsetse flies in Zimbabwe; Surveillance of tsetse fly and cattle populations for trypanosomes in the BICOT area during the sterile insect technique control programme; Freeze dried blood and development of an artificial diet for blood feeding anthropods; Effects of the nutritional quality of locally obtained blood diets on the performance of Glossina palpalis palpalis fed in vitro; Mycetomes and symbionts of tsetse flies maintained on a membrane feeding system and the agents interfering with natural reproduction; Virus particles infection in laboratory reared Glossina pallidipes Austen (Diptera: Glossinidae); Influence of different nutritional sources on haemolymph composition and vitellogenesis in haematophagous arthropods; Effect of rearing diet on the injection rate in flies released for the control of tsetse populations by sterile males; Use of juvenile hormone mimics in the sterilization of tsetse flies; Studies of Glossina pallidipes and G. morsitans subspecies related to the genetic control of tsetse flies

  12. Resfriamento artificial para o controle de Coleoptera em arroz armazenado em silo metálico

    Directory of Open Access Journals (Sweden)

    Sonia Maria Noemberg Lazzari

    2006-06-01

    Full Text Available Resfriamento artificial para o controle de Coleoptera em arroz armazenado em silo metálico. O objetivo desta pesquisa foi avaliar o efeito do resfriamento artificial de grãos de arroz para o controle de coleópteros-praga. O ar frio foi insuflado pelo sistema de aeração em um silo metálico com arroz-em-casca. A avaliação do tratamento foi feita quinzenalmente usando armadilhas caladores. As espécies de Coleoptera capturadas foram: Oryzaephilus surinamensis (60%; Cryptolestes ferrugineus (9%; Rhyzopertha dominica (16,5% e Sitophilus spp. (0,5%. Aos 28 dias, a temperatura média da massa de grãos era de 15ºC, e o número médio de insetos havia diminuído 76,8%. A aplicação de ar frio manteve as populações sob controle por aproximadamente 60 dias. Os resultados do monitoramento dos insetos e da temperatura indicaram que um novo ciclo de ar frio deveria ser aplicado nesse período para manter as populações sob controle. Também o manejo adequado da massa de grãos faz-se necessário para garantir resultados satisfatórios do resfriamento artificial.Artificial chilling to control Coleoptera in paddy rice stored in metallic silo. The objective of this research was to evaluate the effect of artificial chilling for the control of coleopterans in stored paddy rice. The cold air was insufflated through the aeration system of a metallic silo with paddy rice. Evaluation of insect number was made every 15 days using probe traps. The species of Coleoptera captured were: Oryzaephilus surinamensis (60%; Cryptolestes ferrugineus (9%; Rhyzopertha dominica (16.5% and Sitophilus spp. (0.5%. By the 28th day the average temperature of the grain mass was 15ºC, and the mean number of insects decreased 76.8%. The cold air application kept the insect populations under control for approximately 60 days. The results of temperature and insect monitoring indicated that a new cycle of cold air should be applied by that time to keep the populations under

  13. 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...

  14. 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...

  15. 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.

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

    Science.gov (United States)

    Hashim, H A; Abido, M A

    2015-01-01

    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. PMID:25960738

  17. Scientific approaches and techniques for negotiation : a game theoretic and artificial intelligence perspective

    NARCIS (Netherlands)

    Gerding, E.H.; Bragt, D.D.B. van; La Poutré, J.A.

    2000-01-01

    Due to the rapid growth of electronic environments (such as the Internet) much research is currently being performed on autonomous trading mechanisms. This report contains an overview of the current literature on negotiations in the fields of game theory and artificial intelligence (AI). Game theori

  18. The First Workshop on Artificial Intelligence Techniques for Ambient Intelligence (AITAmI '06)

    OpenAIRE

    Augusto, Juan Carlos; Shapiro, Daniel

    2007-01-01

    The first annual workshop on the role of AI in ambient intelligence was held in Riva de Garda, Italy, on August 29, 2006. The workshop was colocated with the European Conference on Artificial Intelligence (ECAI 2006). It provided an opportunity for researchers in a variety of AI subfields together with representatives of commercial interests to explore ambient intelligence technology and applications.

  19. IDENTIFICATION OF MARKS ON TIRES USING ARTIFICIAL VISION FOR QUALITY CONTROL

    Directory of Open Access Journals (Sweden)

    André P. Dias

    2015-03-01

    Full Text Available Tire inspection is presently done by workers who have as their main problems, besides identifying the defects, the time available for defect identification and the inherent costs. Companies can become more sustainable by adopting automated methods to perform such type of processes, such as artificial vision, with advantages both in the processing time and in the incurred costs. This paper addresses the development of an artificial vision system that aims to be an asset in the field of tyre inspection, having as main characteristics its execution speed and its reliability. The conjugation of these criteria is a prerequisite for this system to be able to be integrated in inspection machines. The paper focusses on the study of three image processing methods to be used in the identification of marks (red dots on tires. In this work was used the free Open Computer Vision artificial vision library to process the images acquired by a Basler matrix camera. Two different techniques, namely Background Subtraction and Hough Transform, were tested to implement the solution. After developing the artificial vision inspection application, tests were made to measure the performance of both methods and the results were promising: processing time was low and, simultaneous, the achieved accuracy is high.

  20. CONCURRENCY CONTROL TECHNIQUE IN RFID IMPLEMENTATION

    Directory of Open Access Journals (Sweden)

    Ajaegbu C

    2015-11-01

    Full Text Available Database techniques have been used to proffer solution to some challenging situations that has to do with management of data in industries. This idea can also be valuable and implemented in managing the operation mode of some devices during the design level stage. The proposition of Radio Frequency Identification Detection technology as a convenient and automatic instrument of identification and detection has shown value in usage in the society. However, it has been identified with some challenges such as collision despite its prospects. The need to mitigate collision between a reader and multiple tags is of importance for effective deployment of the technology. The paper aimed at integrating one of the concepts of database management technique of concurrency control known as Time-Stamp (TS in order to offer solution to the problem of collision in RFID implementation. This paper adopted a small scale business scenario which was used to illustrate the benefit this stands to offer in the real-life implementation. The paper concluded by arguing that this technique can be adopted and implemented and by such doing, will enhance further the performance of RFID technology.

  1. Concurrency Control Technique in RFID Implementation

    Directory of Open Access Journals (Sweden)

    Ajaegbu C

    2014-03-01

    Full Text Available Database techniques have been used to proffer solution to some challenging situations that has to do with management of data in industries. This idea can also be valuable and implemented in managing the operation mode of some devices during t he design level stage. The proposition of Radio Frequency Identification Detection technology as a convenient and automatic instrument of identification and detection has shown value in usage in the society. However, it has been identified with some challenges such as collision despite its prospects. The need to mitigate collision between a reader and multiple tags is of importance for effective deployment of the technology. The paper aimed at integrating one of the concepts of database management technique of concurrency control known as Time-Stamp (TS in order to offer solution to the problem of collision in RFID implementation. This paper adopted a small scale business scenario which was used to illustrate the benefit this stands to offer in the real-life implementation. The paper concluded by arguing that this technique can be adopted and implemented and by such doing, will enhance further the performance of RFID technology.

  2. 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. PMID:22942683

  3. Magnetic force control technique in industrial application

    International Nuclear Information System (INIS)

    Techniques of the magnetic force control have been examined for industrial application. The problems and the technique are different in dispersion medium of gas and that of liquid. In addition, the method is different depending on the magnetic characteristic of the target objects. In case of the liquid, the dispersion medium having different viscosity was examined. The separation speed is decided with the magnitude of the magnetic force because a drag force increases with the viscosity. When the water is the dispersion medium, magnetic seeding is possible and hence the nonmagnetic materials can be separated and even the dissolved material could be separated. The separation technique has been used for purifying the waste water form paper mill or wash water of drum. On the other hand when the water is not dispersion medium, mainly the ferromagnetism particle becomes the target object because the magnetic seeding becomes difficult. The iron fragments have been separated from the slurry of slicing machine of solar battery. It has been clarified high gradient magnetic separation (HGMS) can be applied for the viscous fluid of which viscosity was as high as 10 Pa s. When the dispersion medium is gaseous material, the air is important. The drag force from air depends greatly on Reynolds number. When speed of the air is small, the Reynolds number is small, and the drag force is calculated by the Stokes' law of resistance. The study with gaseous dispersion medium is not carried out much. The magnetic separation will discuss the possibility of the industrial application of this technique.

  4. 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.

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

    OpenAIRE

    Dr. Ashutosh Kumar Bhatt; Kunwar Singh Vaisla

    2010-01-01

    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 N...

  6. Daily water level forecasting using wavelet decomposition and artificial intelligence techniques

    Science.gov (United States)

    Seo, Youngmin; Kim, Sungwon; Kisi, Ozgur; Singh, Vijay P.

    2015-01-01

    Reliable water level forecasting for reservoir inflow is essential for reservoir operation. The objective of this paper is to develop and apply two hybrid models for daily water level forecasting and investigate their accuracy. These two hybrid models are wavelet-based artificial neural network (WANN) and wavelet-based adaptive neuro-fuzzy inference system (WANFIS). Wavelet decomposition is employed to decompose an input time series into approximation and detail components. The decomposed time series are used as inputs to artificial neural networks (ANN) and adaptive neuro-fuzzy inference system (ANFIS) for WANN and WANFIS models, respectively. Based on statistical performance indexes, the WANN and WANFIS models are found to produce better efficiency than the ANN and ANFIS models. WANFIS7-sym10 yields the best performance among all other models. It is found that wavelet decomposition improves the accuracy of ANN and ANFIS. This study evaluates the accuracy of the WANN and WANFIS models for different mother wavelets, including Daubechies, Symmlet and Coiflet wavelets. It is found that the model performance is dependent on input sets and mother wavelets, and the wavelet decomposition using mother wavelet, db10, can further improve the efficiency of ANN and ANFIS models. Results obtained from this study indicate that the conjunction of wavelet decomposition and artificial intelligence models can be a useful tool for accurate forecasting daily water level and can yield better efficiency than the conventional forecasting models.

  7. Economic power dispatch of power systems with pollution control using artificial bee colony optimization

    OpenAIRE

    Linda SLIMANI; BOUKTIR, Tarek

    2013-01-01

    This paper presents a solution for the emission-controlled economic dispatch (ECED) problem of medium-sized power systems via an artificial bee colony algorithm. The ECED problem, which accounts for the minimization of both the fuel cost and the emission, is a multiple objective function problem. The objective is to minimize the total fuel cost of the generation and environmental pollution caused by fossil-based thermal generating units and to also maintain an acceptable system performa...

  8. 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.

  9. 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.

  10. Artificial feel system using magneto-rheological fluid on aircraft control stick

    Science.gov (United States)

    Manoharan, Vignesh; Kim, Daewon

    2016-04-01

    The conventional feel system in aircraft occupies large space in the cockpit and has complicated designs. The primary objective of this research is to develop an artificial feel force system that can overcome some drawbacks of the current system. A novel feel system using magneto-rheological (MR) fluid is constructed to precisely control the shear stress under the magnetic field. To validate the functionality of the MR artificial feel system, the final system is fabricated and multiple tests are performed to acquire force-velocity characteristics that are compared to the mathematical model derived. In addition, the PID closed loop control algorithm is developed to simulate the dynamic system model. Both experimental and simulation results are compared to validate the derived system model. The system response time and sampling rates are evaluated and compared to the conventional system at the end. It is concluded that the developed artificial feel system can precisely control and acts as a fail proof system when incorporated with a modern fly-by-wire aircraft system.

  11. Comparison of Artificial Immune System and Particle Swarm Optimization Techniques for Error Optimization of Machine Vision Based Tool Movements

    Science.gov (United States)

    Mahapatra, Prasant Kumar; Sethi, Spardha; Kumar, Amod

    2015-10-01

    In conventional tool positioning technique, sensors embedded in the motion stages provide the accurate tool position information. In this paper, a machine vision based system and image processing technique for motion measurement of lathe tool from two-dimensional sequential images captured using charge coupled device camera having a resolution of 250 microns has been described. An algorithm was developed to calculate the observed distance travelled by the tool from the captured images. As expected, error was observed in the value of the distance traversed by the tool calculated from these images. Optimization of errors due to machine vision system, calibration, environmental factors, etc. in lathe tool movement was carried out using two soft computing techniques, namely, artificial immune system (AIS) and particle swarm optimization (PSO). The results show better capability of AIS over PSO.

  12. 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.

  13. Artificial biomembrane based on DPPC--Investigation into phase transition and thermal behavior through ellipsometric techniques.

    Science.gov (United States)

    González, Carmen M; Pizarro-Guerra, Guadalupe; Droguett, Felipe; Sarabia, Mauricio

    2015-10-01

    Organic thin film deposition presents a multiplicity of challenges. Most notably, layer thickness control, homogeneity and subsequent characterization have been not cleared yet. Phospholipid bilayers are frequently used to model cell membranes. Bilayers can be disrupted by changes in mechanical stress, pH and temperature. The strategy presented in this article is based on thermal study of 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) through analysis of slight changes in material thickness. The sample was prepared by depositing X- or Y-type DPPC bilayers using Langmuir-Blodgett technique over silicon wafer. Thus, molecular inclination degree, mobility and stability of phases and their respective phase transitions were observed and analyzed through ellipsometric techniques during heating cycles and corroborated by Grazing Incidence X-ray Diffraction and Atomic Force Microcopy measurements. DPPC functional group vibrations were detected by Raman spectra analysis. Scanning Electron Microscope with Field Emission gun (FE-SEM) and conventional SEM micrographs were also used to characterize sample morphology, demonstrating that homogenous bilayer formations coexist with some vesicles or micelles at surface level. Contact angle measurements corroborate DPPC surface wettability, which is mainly related to surface treatment methods of silicon wafer used to create either hydrophilic or hydrophobic nature regarding the substrate surface. Also, shifting and intensity changes of certain functional groups into Raman spectra confirm water presence between DPPC layers. Signal analysis detects certain interdigitation between aliphatic chains. These studies correspond to the base of future biosensors based on proteins or antimicrobial peptides stabilized into phospholipid bilayers over thin hydrogel films as moist scaffold. PMID:26150275

  14. Modeling of biodistribution of 90 Y-DOTA-hR3 by using artificial intelligence techniques

    International Nuclear Information System (INIS)

    In this work the biodistribution of radioimmunoconjugate 90Y-DOTA-hR3 was modeled by using an artificial neural network. In vivo stability of 90Y-DOTA-hR3 was determined in healthy male Wistar rats at 4, 24 and 48 hours, in different organs. A model describing the relationship between, by one hand, the incorporated dose and, by the other hand, organ and time was developed by using a multilayer perceptron neural network. Adjusted model was analyzed by several statistical tests. Outcomes shown that proposed neural model describes the relationship between the studied variables in a proper way. (Author)

  15. 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.

  16. 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. PMID:22956056

  17. Use of conditional rule structure to automate clinical decision support: a comparison of artificial intelligence and deterministic programming techniques.

    Science.gov (United States)

    Friedman, R H; Frank, A D

    1983-08-01

    A rule-based computer system was developed to perform clinical decision-making support within a medical information system, oncology practice, and clinical research. This rule-based system, which has been programmed using deterministic rules, possesses features of generalizability, modularity of structure, convenience in rule acquisition, explanability, and utility for patient care and teaching, features which have been identified as advantages of artificial intelligence (AI) rule-based systems. Formal rules are primarily represented as conditional statements; common conditions and actions are stored in system dictionaries so that they can be recalled at any time to form new decision rules. Important similarities and differences exist in the structure of this system and clinical computer systems utilizing artificial intelligence (AI) production rule techniques. The non-AI rule-based system possesses advantages in cost and ease of implementation. The degree to which significant medical decision problems can be solved by this technique remains uncertain as does whether the more complex AI methodologies will be required. PMID:6352165

  18. 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.

  19. 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. PMID:27055066

  20. Optimal artificial neural network architecture selection for performance prediction of compact heat exchanger with the EBaLM-OTR technique

    International Nuclear Information System (INIS)

    Highlights: → Performance prediction of PCHE using artificial neural networks. → Evaluating artificial neural network performance for PCHE modeling. → Selection of over-training resilient artificial neural networks. → Artificial neural network architecture selection for modeling problems with small data sets. - Abstract: Artificial Neural Networks (ANN) have been used in the past to predict the performance of printed circuit heat exchangers (PCHE) with satisfactory accuracy. Typically published literature has focused on optimizing ANN using a training dataset to train the network and a testing dataset to evaluate it. Although this may produce outputs that agree with experimental results, there is a risk of over-training or over-learning the network rather than generalizing it, which should be the ultimate goal. An over-trained network is able to produce good results with the training dataset but fails when new datasets with subtle changes are introduced. In this paper we present EBaLM-OTR (error back propagation and Levenberg-Marquardt algorithms for over training resilience) technique, which is based on a previously discussed method of selecting neural network architecture that uses a separate validation set to evaluate different network architectures based on mean square error (MSE), and standard deviation of MSE. The method uses k-fold cross validation. Therefore in order to select the optimal architecture for the problem, the dataset is divided into three parts which are used to train, validate and test each network architecture. Then each architecture is evaluated according to their generalization capability and capability to conform to original data. The method proved to be a comprehensive tool in identifying the weaknesses and advantages of different network architectures. The method also highlighted the fact that the architecture with the lowest training error is not always the most generalized and therefore not the optimal. Using the method the

  1. Cascading effects of artificial light at night: resource-mediated control of herbivores in a grassland ecosystem

    OpenAIRE

    Bennie, Jonathan; Davies, Thomas W; Cruse, David; Inger, Richard; Gaston, Kevin J

    2015-01-01

    Artificial light at night has a wide range of biological effects on both plants and animals. Here, we review mechanisms by which artificial light at night may restructure ecological communities by modifying the interactions between species. Such mechanisms may be top-down (predator, parasite or grazer controlled), bottom-up (resource-controlled) or involve non-trophic processes, such as pollination, seed dispersal or competition. We present results from an experiment investigating both top-do...

  2. Simulation of radionuclide chemistry and sorption characteristics in the geosphere by artificial intelligence technique

    International Nuclear Information System (INIS)

    An expert system operated in a personal computer is employed to simulate chemistry and sorption phenomena of radionuclides in the geosphere. The system handles both qualitative and quantitative analyses primarily for the actinides and fission products. The system also incorporates data bases of several groundwater and rock types with mineral and chemical compositions, the distribution coefficients of nuclides for minerals, etc. The decision rule base facilitates this system to carry out the reasoning procedures to predict the solubility-limiting phase, solute species, oxidation states and possible complex formations of radionuclides, as well as to calculate the distribution coefficients and retardation factors in a geological formation, provided that the essential groundwater and host rock information are available. It is concluded that this device of artificial intelligence provides a vehicle to accumulate developed human knowledge and serves as a tool not only for simulating the complicated radionuclide behaviour in the geosphere, but also for instructional or educational purpose in this field. (orig.)

  3. Artificial Intelligence Techniques for the Berth Allocation and Container Stacking Problems in Container Terminals

    Science.gov (United States)

    Salido, Miguel A.; Rodriguez-Molins, Mario; Barber, Federico

    The Container Stacking Problem and the Berth Allocation Problem are two important problems in maritime container terminal's management which are clearly related. Terminal operators normally demand all containers to be loaded into an incoming vessel should be ready and easily accessible in the terminal before vessel's arrival. Similarly, customers (i.e., vessel owners) expect prompt berthing of their vessels upon arrival. In this paper, we present an artificial intelligence based-integrated system to relate these problems. Firstly, we develop a metaheuristic algorithm for berth allocation which generates an optimized order of vessel to be served according to existing berth constraints. Secondly, we develop a domain-oriented heuristic planner for calculating the number of reshuffles needed to allocate containers in the appropriate place for a given berth ordering of vessels. By combining these optimized solutions, terminal operators can be assisted to decide the most appropriated solution in each particular case.

  4. Intelligent postoperative morbidity prediction of heart disease using artificial intelligence techniques.

    Science.gov (United States)

    Hsieh, Nan-Chen; Hung, Lun-Ping; Shih, Chun-Che; Keh, Huan-Chao; Chan, Chien-Hui

    2012-06-01

    Endovascular aneurysm repair (EVAR) is an advanced minimally invasive surgical technology that is helpful for reducing patients' recovery time, postoperative morbidity and mortality. This study proposes an ensemble model to predict postoperative morbidity after EVAR. The ensemble model was developed using a training set of consecutive patients who underwent EVAR between 2000 and 2009. All data required for prediction modeling, including patient demographics, preoperative, co-morbidities, and complication as outcome variables, was collected prospectively and entered into a clinical database. A discretization approach was used to categorize numerical values into informative feature space. Then, the Bayesian network (BN), artificial neural network (ANN), and support vector machine (SVM) were adopted as base models, and stacking combined multiple models. The research outcomes consisted of an ensemble model to predict postoperative morbidity after EVAR, the occurrence of postoperative complications prospectively recorded, and the causal effect knowledge by BNs with Markov blanket concept. PMID:21184153

  5. State and data techniques for control of discontinuous systems

    International Nuclear Information System (INIS)

    This paper describes a technique for structured analysis and design of automated control systems. The technique integrates control of continuous and discontinuous nuclear power plant subsystems and components. A hierarchical control system with distributed intelligence follows from applying the technique. Further, it can be applied to all phases of control system design. For simplicity, the example used in the paper is limited to phase 1 design (basic automatic control action), in which no maintenance, testing, or contingency capability is attempted. 11 figs

  6. 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...

  7. Development of a technique for level measurement in pressure vessels using thermal probes and artificial neural networks

    International Nuclear Information System (INIS)

    A technique for level measurement in pressure vessels was developed using thermal probes with internal cooling and artificial neural networks (ANN's). This new concept of thermal probes was experimentally tested in an experimental facility (BETSNI) with two test sections, ST1 and ST2. Two different thermal probes were designed and constructed: concentric tubes probe and U tube probe. A data acquisition system (DAS) was assembled to record the experimental data during the tests. Steady state and transient level tests were carried out and the experimental data obtained were used as learning and recall data sets in the ANN's program RETRO-05 that simulate a multilayer perceptron with backpropagation. The results of the analysis show that the technique can be applied for level measurements in pressure vessel. The technique is applied for a less input temperature data than the initially designed to the probes. The technique is robust and can be used in case of lack of some temperature data. Experimental data available in literature from electrically heated thermal probe were also used in the ANN's analysis producing good results. The results of the ANN's analysis show that the technique can be improved and applied to level measurements in pressure vessels. (author)

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

    Science.gov (United States)

    Kong, Young Bae; Hur, Min Goo; Lee, Eun Je; Park, Jeong Hoon; Park, Yong Dae; Yang, Seung Dae

    2016-01-01

    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.

  9. Sterile insect technique in codling moth control

    International Nuclear Information System (INIS)

    Exposure of mature pupae or adult codling moths, Cydia pomonella (L.), to 30-40 krad of gamma radiation induces a high level of sterility in the male and complete sterility in the female without seriously affecting behaviour except for sperm competitiveness which is drastically reduced. Substerilizing doses (below about 25 krad) have very little adverse effect and induces higher level of sterility in the F1 male than in the irradiated male parent. The most satisfactory method of measuring the population density of native moths is by examining fruit for larval exit holes. Population increase per generation depends largely on evening temperatures during the moth's reproductive period. The codling moth is a sedentary species, and its distribution is very uneven in commercial orchards. Neglected host trees must be sprayed or destroyed to avoid reinfestation of sterile insect release orchards with immigrant moths. Laboratory-reared moths may be marked externally with fluorescent powders or internally with calco oil red without adverse effects. Mass rearing is still unreliable and expensive, and prolonged colonization affects the insects' behaviour. Successful codling moth suppression was achieved in North America and/or Europe by release of sterile males, sterile females or sterile mixed sexes; by substerile males; and by F1 male progeny (released as diapausing larvae) of substerile males X untreated females. Arthropod predators and parasites held aphids and spider mites at noninjurious levels in most insect release orchards, but leafrollers eventually built up to damaging numbers. The sterile insect technique for commercial control of the codling moth is not feasible at this time because of high costs. (author)

  10. Contribution of artificial intelligence to operation

    International Nuclear Information System (INIS)

    Artificial Intelligence techniques are already used in nuclear plants for assistance to operation: synthesis from numerous information sources may be then derived, based on expert knowledge. Artificial intelligence may be used also for quality and reliability assessment of software-based control-command systems. Various expert systems developed by CEA, EDF and Framatome are presented

  11. Integrated control of the cooling system and surface openings using the artificial neural networks

    International Nuclear Information System (INIS)

    This study aimed at suggesting an indoor temperature control method that can provide a comfortable thermal environment through the integrated control of the cooling system and the surface openings. Four control logic were developed, employing different application levels of rules and artificial neural network models. Rule-based control methods represented the conventional approach while ANN-based methods were applied for the predictive and adaptive controls. Comparative performance tests for the conventional- and ANN-based methods were numerically conducted for the double-skin-facade building, using the MATLAB (Matrix Laboratory) and TRNSYS (Transient Systems Simulation) software, after proving the validity by comparing the simulation and field measurement results. Analysis revealed that the ANN-based controls of the cooling system and surface openings improved the indoor temperature conditions with increased comfortable temperature periods and decreased standard deviation of the indoor temperature from the center of the comfortable range. In addition, the proposed ANN-based logic effectively reduced the number of operating condition changes of the cooling system and surface openings, which can prevent system failure. The ANN-based logic, however, did not show superiority in energy efficiency over the conventional logic. Instead, they have increased the amount of heat removal by the cooling system. From the analysis, it can be concluded that the ANN-based temperature control logic was able to keep the indoor temperature more comfortably and stably within the comfortable range due to its predictive and adaptive features. - Highlights: • Integrated rule-based and artificial neural network based logics were developed. • A cooling device and surface openings were controlled in an integrated manner. • Computer simulation method was employed for comparative performance tests. • ANN-based logics showed the advanced features of thermal environment. • Rule

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

    OpenAIRE

    O P Verma; Kumar, R.; Kumar, A.(State University of New York at Buffalo, Buffalo, USA); Chand, S

    2012-01-01

    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...

  13. 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.

  14. 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.

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

    OpenAIRE

    Hiram Ponce; Luis Ibarra; Pedro Ponce; Arturo Molina

    2014-01-01

    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 eas...

  16. 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.

  17. Development of sediment load estimation models by using artificial neural networking techniques.

    Science.gov (United States)

    Hassan, Muhammad; Ali Shamim, M; Sikandar, Ali; Mehmood, Imran; Ahmed, Imtiaz; Ashiq, Syed Zishan; Khitab, Anwar

    2015-11-01

    This study aims at the development of an artificial neural network-based model for the estimation of weekly sediment load at a catchment located in northern part of Pakistan. The adopted methodology has been based upon antecedent sediment conditions, discharge, and temperature information. Model input and data length selection was carried out using a novel mathematical tool, Gamma test. Model training was carried out by using three popular algorithms namely Broyden-Fletcher-Goldfarb-Shanno (BFGS), back propagation (BP), and local linear regression (LLR) using forward selection of input variables. Evaluation of the best model was carried out on the basis of basic statistical parameters namely R-square, root mean squared error (RMSE), and mean biased error (MBE). Results indicated that BFGS-based ANN model outperformed all other models with significantly low values of RMSE and MBE. A strong correlation was also found between the observed and estimated sediment load values for the same model as the value of Nash-Sutcliffe model efficiency coefficient (R-square) was found to be quite high as well. PMID:26463089

  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. 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.

  20. 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.

  1. Comparison of Conventional and Modern Load Forecasting Techniques Based on Artificial Intelligence and Expert Systems

    Directory of Open Access Journals (Sweden)

    Badar ul Islam

    2011-09-01

    Full Text Available This paper picturesquely depicts the comparison of different methodologies adopted for predicting the load demand and highlights the changing trend and values under new circumstances using latest non analytical soft computing techniques employed in the field of electrical load forecasting. A very clear advocacy about the changing trends from conventional and obsolete to the modern techniques is explained in very simple way. Load forecast has been a central and an integral process in the planning and operation of electric utilities. Many techniques and approaches have been investigated to tackle this problem in the last two decades. These are often different in nature and apply different engineering considerations and economic analysis. Further a clear comparison is also presented between the past standard practices with the current methodology of electrical load demand forecasting. Besides all this, different important points are highlighted which need special attention while doing load forecasting when the environment is competitive and deregulated one.

  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. The Development of Ball Control Techniques for Robot Soccer based on Predefined Scenarios

    Directory of Open Access Journals (Sweden)

    K. Omar

    2011-01-01

    Full Text Available Robotic soccer is an attractive topic in artificial intelligence and robotics research. However, to develop techniques and algorithms in this domain is a complex task. This study presents the development of ball control techniques and algorithms for robot soccer based on several predefined scenarios. In this study, we study the robot can do ball passing, obstacle avoiding and ball shooting according to certain situations. A vision system is used in this case where it calculates the robot position in x, y coordinates to make sure the robots move to the right direction. The velocity of each robot wheel is manipulated to control the speed of the robots and allow them to make turning and shooting. Algorithm testing was carried out by using a robot soccer simulator. Several techniques in obstacle avoiding and positioning were successfully implemented. The results prove these algorithms can be applied to execute the given tasks.

  4. The design and optimization for light-algae bioreactor controller based on Artificial Neural Network-Model Predictive Control

    Science.gov (United States)

    Hu, Dawei; Liu, Hong; Yang, Chenliang; Hu, Enzhu

    As a subsystem of the bioregenerative life support system (BLSS), light-algae bioreactor (LABR) has properties of high reaction rate, efficiently synthesizing microalgal biomass, absorbing CO2 and releasing O2, so it is significant for BLSS to provide food and maintain gas balance. In order to manipulate the LABR properly, it has been designed as a closed-loop control system, and technology of Artificial Neural Network-Model Predictive Control (ANN-MPC) is applied to design the controller for LABR in which green microalgae, Spirulina platensis is cultivated continuously. The conclusion is drawn by computer simulation that ANN-MPC controller can intelligently learn the complicated dynamic performances of LABR, and automatically, robustly and self-adaptively regulate the light intensity illuminating on the LABR, hence make the growth of microalgae in the LABR be changed in line with the references, meanwhile provide appropriate damping to improve markedly the transient response performance of LABR.

  5. Use of nuclear techniques for evaluation of first service conception rate in dairy herds with artificial insemination in Chile

    International Nuclear Information System (INIS)

    The objective of this study was to identify causes of inefficiency in Artificial Insemination (AI) services in 12 dairy farms located in southern Chile. Milk progesterone concentration was determined on the day of breeding and then 10-12 and 21-22 days after AI. Data for semen and cow inseminated, including physical signs of oestrus, were recorded in a computer database (AIDA). Information from 713 cows with first services was analysed. The mean interval from calving to first service was 88.7 days and the mean interval from calving to conception was 107.9 days. The conception rate at first service was 61.9%. Incidence of incorrect AI, most likely due to erroneous heat detection, was 8.9%. Herd related problems affected efficiency of AI in 15.2%. The results show that important factors affecting reproductive performance include nutritional management, oestrus detection and AI technique. (author)

  6. Identification of unique repeated patterns, location of mutation in DNA finger printing using artificial intelligence technique.

    Science.gov (United States)

    Mukunthan, B; Nagaveni, N

    2014-01-01

    In genetic engineering, conventional techniques and algorithms employed by forensic scientists to assist in identification of individuals on the basis of their respective DNA profiles involves more complex computational steps and mathematical formulae, also the identification of location of mutation in a genomic sequence in laboratories is still an exigent task. This novel approach provides ability to solve the problems that do not have an algorithmic solution and the available solutions are also too complex to be found. The perfect blend made of bioinformatics and neural networks technique results in efficient DNA pattern analysis algorithm with utmost prediction accuracy. PMID:24589835

  7. Techniques of Artificial Intelligence Network (Ann) and Applıed to Radiology

    OpenAIRE

    SERHATLIOĞLU, Selami; HARDALAÇ, Fırat

    2009-01-01

    Artifical Neural Network (ANN) have been begin by using in various field and worked to build by developing of computer process to smilar thing of human. In this cases, Introducing of Neural network techniques were aimed to composed of estimation on relationship ideas by using radiology.

  8. Application of artificial neural network technique to uranium logging data interpretation

    International Nuclear Information System (INIS)

    The author describes the application of B-P technique to pertinent questions in uranium logging data interpretation. Adopting the improved B-P algorithm to establish network structure and thoroughly investigating the process, and the method constructing learning sample has been improved. Good results have been achieved through applying the B-P model to recognize lithologies and forecast porosity

  9. Application of artificial intelligence techniques to the acceleration of Monte Carlo transport calculations

    International Nuclear Information System (INIS)

    The techniques of learning theory and pattern recognition are used to learn splitting surface locations for the Monte Carlo neutron transport code MCN. A study is performed to determine default values for several pattern recognition and learning parameters. The modified MCN code is used to reduce computer cost for several nontrivial example problems

  10. Magnetic Levitation Technique for Active Vibration Control

    OpenAIRE

    Hoque, Emdadul; Mizuno, Takeshi

    2010-01-01

    A zero-power controlled magnetic levitation system has been presented in this chapter. The unique characteristic of the zero-power control system is that it can generate negative stiffness with zero control current in the steady-state which is realized in this chapter. The detail characteristics of the levitation system are investigated. Moreover, two major contributions, the stiffness adjustment and nonlinear compensation of the suspension system have been introduced elaborately. Often, ther...

  11. Autonomous self-configuration of artificial neural networks for data classification or system control

    Science.gov (United States)

    Fink, Wolfgang

    2009-05-01

    Artificial neural networks (ANNs) are powerful methods for the classification of multi-dimensional data as well as for the control of dynamic systems. In general terms, ANNs consist of neurons that are, e.g., arranged in layers and interconnected by real-valued or binary neural couplings or weights. ANNs try mimicking the processing taking place in biological brains. The classification and generalization capabilities of ANNs are given by the interconnection architecture and the coupling strengths. To perform a certain classification or control task with a particular ANN architecture (i.e., number of neurons, number of layers, etc.), the inter-neuron couplings and their accordant coupling strengths must be determined (1) either by a priori design (i.e., manually) or (2) using training algorithms such as error back-propagation. The more complex the classification or control task, the less obvious it is how to determine an a priori design of an ANN, and, as a consequence, the architecture choice becomes somewhat arbitrary. Furthermore, rather than being able to determine for a given architecture directly the corresponding coupling strengths necessary to perform the classification or control task, these have to be obtained/learned through training of the ANN on test data. We report on the use of a Stochastic Optimization Framework (SOF; Fink, SPIE 2008) for the autonomous self-configuration of Artificial Neural Networks (i.e., the determination of number of hidden layers, number of neurons per hidden layer, interconnections between neurons, and respective coupling strengths) for performing classification or control tasks. This may provide an approach towards cognizant and self-adapting computing architectures and systems.

  12. 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.

  13. 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.

  14. Indoor air quality control techniques. Radon, formaldehyde, combustion products

    International Nuclear Information System (INIS)

    This book reviews and evaluates existing indoor air quality control techniques. The indoor air pollutants of most concern are radon, formaldehyde, and certain combustion products-nitrogen dioxide, carbon monoxide, carbon dioxide, and various respirable particles. Many techniques exist to control the concentration of these pollutants and other indoor pollutants that are only now being recognized as significant. The purpose of the book is to provide a current review and evaluation of these control techniques

  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. PMID:26409226

  16. 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 w...

  17. Cost averaging techniques for robust control of flexible structural systems

    Science.gov (United States)

    Hagood, Nesbitt W.; Crawley, Edward F.

    1991-01-01

    Viewgraphs on cost averaging techniques for robust control of flexible structural systems are presented. Topics covered include: modeling of parameterized systems; average cost analysis; reduction of parameterized systems; and static and dynamic controller synthesis.

  18. Optimizing an Industrial Scale Naphtha Catalytic Reforming Plant Using a Hybrid Artificial Neural Network and Genetic Algorithm Technique

    Directory of Open Access Journals (Sweden)

    Sepehr Sadighi

    2015-07-01

    Full Text Available In this paper, a hybrid model for estimating the activity of a commercial Pt-Re/Al2O3 catalyst in an industrial scale heavy naphtha catalytic-reforming unit (CRU is presented. This model is also capable of predicting research octane number (RON and yield of gasoline. In the proposed model, called DANN, the decay function of heterogeneous catalysts is combined with a recurrent-layer artificial neural network. During a life cycle (919 days, fifty-eight points are selected for building and training the DANN (60%, nineteen data points for testing (20%, and the remained ones for validating steps. Results show that DANN can acceptably estimate the activity of catalyst during its life in consideration of all process variables. Moreover, it is confirmed that the proposed model is capable of predicting RON and yield of gasoline for unseen (validating data with AAD% (average absolute deviation of 0.272% and 0.755%, respectively. After validating the model, the octane barrel level (OCB of the plant is maximized by manipulating the inlet temperature of reactors, and hydrogen to hydrocarbon molar ratio whilst all process limitations are taken into account. During a complete life cycle results show that the decision variables, generated by the optimization program, can increase the RON, process yield and OCB of CRU to about 1.15%, 3.21%, and 4.56%, respectively. © 2015 BCREC UNDIP. All rights reserved.Received: 27th July 2014; Revised: 31st May 2015; Accepted: 31th May 2015 How to Cite: Sadighi, S., Mohaddecy, R.S., Norouzian, A. (2015. Optimizing an Industrial Scale Naphtha Catalytic Reforming Plant Using a Hybrid Artificial Neural Network and Genetic Algorithm Technique. Bulletin of Chemical Reaction Engineering & Catalysis, 10(2: 210-220. (doi:10.9767/bcrec.10.2.7171.210-220 Permalink/DOI: http://dx.doi.org/10.9767/bcrec.10.2.7171.210-220  

  19. The artificial control of enhanced optical processes in fluorescent molecules on high-emittance metasurfaces.

    Science.gov (United States)

    Iwanaga, Masanobu; Choi, Bongseok; Miyazaki, Hideki T; Sugimoto, Yoshimasa

    2016-06-01

    Plasmon-enhanced optical processes in molecules have been extensively but individually explored for Raman scattering, fluorescence, and infrared light absorption. In contrast to recent progress in the interfacial control of hot electrons in plasmon-semiconductor hybrid systems, plasmon-molecule hybrid systems have remained to be a conventional scheme, mainly assuming electric-field enhancement. This was because it was difficult to control the plasmon-molecule interface in a well-controlled manner. We here experimentally substantiate an obvious change in artificially enhanced optical processes of fluorescence/Raman scattering in fluorescent molecules on high-emittance plasmo-photonic metasurfaces with/without a self-assembled monolayer of sub-nm thickness. These results indicate that the enhanced optical processes were successfully selected under artificial configurations without any additional chemical treatment that modifies the molecules themselves. Although Raman-scattering efficiency is generally weak in high-fluorescence-yield molecules, it was found that Raman scattering becomes prominent around the molecular fingerprint range on the metasurfaces, being enhanced by more than 2000 fold at the maximum for reference signals. In addition, the highly and uniformly enhancing metasurfaces are able to serve as two-way functional, reproducible, and wavelength-tunable platforms to detect molecules at very low densities, being distinct from other platforms reported so far. The change in the enhanced signals suggests that energy diagrams in fluorescent molecules are changed in the configuration that includes the metal-molecule interface, meaning that plasmon-molecule hybrid systems are rich in the phenomena beyond the conventional scheme. PMID:27227964

  20. Optimisation techniques for advanced process supervision and control

    OpenAIRE

    Abu-el-zeet, Z.H.

    2000-01-01

    This thesis is concerned with the use and development of optimisation techniques for process supervision and control. Two major areas related to optimisation are combined namely model predictive control and dynamic data reconciliation. A model predictive control scheme is implemented and used to simulate the control of a coal gasification plant. Static as well as dynamic data reconciliation techniques are developed and used in conjunction with steady-state optimisation and model predictive co...

  1. Models of signal validation using artificial intelligence techniques applied to a nuclear reactor

    International Nuclear Information System (INIS)

    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)

  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. Microgrid Control Techniques at Power Converter Level

    Czech Academy of Sciences Publication Activity Database

    Valouch, Viktor; Šimek, Petr; Škramlík, Jiří; Tlustý, J.

    Ostrava: VŠB - TU Ostrava, 2013, s. 611-616. ISBN 978-80-248-2988-3. [Electric Power Engineering - EPE 2013. Kouty nad Desnou (CZ), 28.05.2013-30.05.2013] Institutional support: RVO:61388998 Keywords : microgrid * power converter * droop control Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering

  4. Advanced Control Techniques for WEC Wave Dragon

    DEFF Research Database (Denmark)

    Tedd, James; Kofoed, Jens Peter; Jasinski, M.; Morris, A.; Friis-Madsen, E.; Wisniewski, Rafal; Bendtsen, Jan Dimon

    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...

  5. Giant Controllable Magnetization Changes Induced by Structural Phase Transitions in a Metamagnetic Artificial Multiferroic.

    Science.gov (United States)

    Bennett, S P; Wong, A T; Glavic, A; Herklotz, A; Urban, C; Valmianski, I; Biegalski, M D; Christen, H M; Ward, T Z; Lauter, V

    2016-01-01

    The realization of a controllable metamagnetic transition from AFM to FM ordering would open the door to a plethora of new spintronics based devices that, rather than reorienting spins in a ferromagnet, harness direct control of a materials intrinsic magnetic ordering. In this study FeRh films with drastically reduced transition temperatures and a large magneto-thermal hysteresis were produced for magnetocaloric and spintronics applications. Remarkably, giant controllable magnetization changes (measured to be as high has ~25%) are realized by manipulating the strain transfer from the external lattice when subjected to two structural phase transitions of BaTiO3 (001) single crystal substrate. These magnetization changes are the largest seen to date to be controllably induced in the FeRh system. Using polarized neutron reflectometry we reveal how just a slight in plane surface strain change at ~290C results in a massive magnetic transformation in the bottom half of the film clearly demonstrating a strong lattice-spin coupling in FeRh. By means of these substrate induced strain changes we show a way to reproducibly explore the effects of temperature and strain on the relative stabilities of the FM and AFM phases in multi-domain metamagnetic systems. This study also demonstrates for the first time the depth dependent nature of a controllable magnetic order using strain in an artificial multiferroic heterostructure. PMID:26940159

  6. Giant Controllable Magnetization Changes Induced by Structural Phase Transitions in a Metamagnetic Artificial Multiferroic

    Science.gov (United States)

    Bennett, S. P.; Wong, A. T.; Glavic, A.; Herklotz, A.; Urban, C.; Valmianski, I.; Biegalski, M. D.; Christen, H. M.; Ward, T. Z.; Lauter, V.

    2016-03-01

    The realization of a controllable metamagnetic transition from AFM to FM ordering would open the door to a plethora of new spintronics based devices that, rather than reorienting spins in a ferromagnet, harness direct control of a materials intrinsic magnetic ordering. In this study FeRh films with drastically reduced transition temperatures and a large magneto-thermal hysteresis were produced for magnetocaloric and spintronics applications. Remarkably, giant controllable magnetization changes (measured to be as high has ~25%) are realized by manipulating the strain transfer from the external lattice when subjected to two structural phase transitions of BaTiO3 (001) single crystal substrate. These magnetization changes are the largest seen to date to be controllably induced in the FeRh system. Using polarized neutron reflectometry we reveal how just a slight in plane surface strain change at ~290C results in a massive magnetic transformation in the bottom half of the film clearly demonstrating a strong lattice-spin coupling in FeRh. By means of these substrate induced strain changes we show a way to reproducibly explore the effects of temperature and strain on the relative stabilities of the FM and AFM phases in multi-domain metamagnetic systems. This study also demonstrates for the first time the depth dependent nature of a controllable magnetic order using strain in an artificial multiferroic heterostructure.

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

    International Nuclear Information System (INIS)

    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. (orig.)

  8. 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.

  9. 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.

  10. 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

  11. Comparison of two solution ways of district heating control: Using analysis methods, using artificial intelligence methods

    Energy Technology Data Exchange (ETDEWEB)

    Balate, J.; Sysala, T. [Technical Univ., Zlin (Czech Republic). Dept. of Automation and Control Technology

    1997-12-31

    The District Heating Systems - DHS (Centralized Heat Supply Systems - CHSS) are being developed in large cities in accordance with their growth. The systems are formed by enlarging networks of heat distribution to consumers and at the same time they interconnect the heat sources gradually built. The heat is distributed to the consumers through the circular networks, that are supplied by several cooperating heat sources, that means by power and heating plants and heating plants. The complicated process of heat production technology and supply requires the system approach when solving the concept of automatized control. The paper deals with comparison of the solution way using the analysis methods and using the artificial intelligence methods. (orig.)

  12. Research Considering Embryonic Development of Pikeperch (Stizostedion lucioperca under Artificial-Controlled Spawning Conditions

    Directory of Open Access Journals (Sweden)

    Daniel Tiberiu Oprea

    2014-05-01

    Full Text Available The experiments made in order to study the embryonic development of pikeperch were take place at the Fish Culture Research and Development Station Nucet, within 02.04 – 17.04.2012. For artificial-controlled spawning of pikeperch were used 4 years old breeders reared in ponds, at Nucet Station in policulture with older cyprinids. The experiment was accomplished in two experimental variants, wherein the fertilized eggs have been hatched at two different intervals of temperatures. The technological parameters of incubation were as follow, variant V1: fertilized rate 92 %, embryo rate 76 % and hatching rate 65 %; variant V2: fertilized rate 93 %, embryo rate 82 % and hatching rate 71 %. The Nucet type incubators seem to offer good conditions for embryonic development of pikeperch.

  13. 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.

  14. Hybrid optical fiber sensor and artificial neural network system for bioethanol quality control and productivity enhancement

    Science.gov (United States)

    Gusken, Edmilton; Salgado, Ricardo M.; Rossell, Carlos E. V.; Ohishi, Takaaki; Suzuki, Carlos K.

    2008-04-01

    Bioethanol is produced by bio-chemical process that converts sugar or biomass feedstock into ethanol. After bio-chemical process, the solution is distilled under controlled conditions of pressure and temperature, in order to obtain an ethanol-water solution. However, the ethanol concentration analysis is generally performed off-line and, sometimes, a re-distillation process becomes necessary. In this research, an optical apparatus based on Fresnel reflection has been used in combination with artificial neural networks for determination of bioethanol concentration in hydro-alcoholic solution at any temperature. The volumetric concentration and temperature effect was investigated. This intelligent system can effectively detect and update in real-time the correction of distillation parameters to reduce losses of bioethanol and also to improve the quality in a production plant.

  15. 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...

  16. Benchmark of experimental techniques for measuring and controlling suction

    OpenAIRE

    Muñoz, Juan Jorge; Tarantino, A.; Gallipoli, Domenico; Augarde, C.E.; V. Gennaro; Gómez, R.; Laloui, L.; Mancuso, C.; El Mountassir, G.; Wheeler, S. J.; Tombolato, S.; Toll, D.G.; Rojas Arias, Juan Carlos; Raveendiraraj, A.; Romero Morales, Enrique Edgar

    2011-01-01

    The paper presents a benchmarking study carried out within the ‘Mechanics of Unsaturated Soils for Engineering’ (MUSE) network aimed at comparing different techniques for measurement and control of suction. Techniques tested by the eight ‘Mechanics of Unsaturated Soils for Engineering’ research teams include axis-translation (pressure plate and suction-controlled oedometer), highcapacity tensiometer and osmotic technique. The soil used in the exercise was a mixture of uniform sand, sodium ...

  17. Design and Control of a Transcutaneous Power Regulator for Artificial Heart

    Directory of Open Access Journals (Sweden)

    Ms. R. Kasthuri

    2014-02-01

    Full Text Available In medical implant systems high efficiency and improving the patient’s mobility. Artificial organs and monitoring devices to be implanted into human body for the extension and the improvement of human lives. The implants must operate inside the body for the considerable period of time and communicate with outside world wirelessly for exchange of medical data and commands. Rechargeable batteries are recharged remotely through the human skin via inductive links. In my project transformer model a remote power supply for use in the artificial hearts for easy controllability and high efficiency, which can monitor the charging level of the battery has been designed and implemented. In order to recharge the battery the electro-magnetic coupling between primary coil and secondary coil has been used. Primary and secondary windings of the transformer are positioned outside and inside the human body respectively. In such a transformer, the alignment and gap may change with external positioning. The coupling coefficient of the transformer is also varying, and so are the tool to large leakage inductances and the mutual inductance. Resonance-tank circuits with varying resonance frequency are formed from the transformer inductors and external capacitors. A control method is proposed to lock the switching frequency at just above the load insensitive frequency for optimized efficiency at heavy loads. Specifically operation at above resonant of the resonance circuits is maintained under varying coupling coefficient. A transcutaneous power regulator is built and found to perform excellently with high efficiency and tight regulation under variations of the alignment or gap of the transcutaneous transformer load and input voltage.

  18. 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.

  19. 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.

  20. 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. PMID:25571075

  1. Adhesion control by inflation: implications from biology to artificial attachment device

    Science.gov (United States)

    Dening, Kirstin; Heepe, Lars; Afferrante, Luciano; Carbone, Giuseppe; Gorb, Stanislav N.

    2014-08-01

    There is an increasing demand for materials that incorporate advanced adhesion properties, such as an ability to adhere in a reversible and controllable manner. In biological systems, these features are known from adhesive pads of the tree frog, Litoria caerulea, and the bush-cricket, Tettigonia viridissima. These species have convergently developed soft, hemispherically shaped pads that might be able to control their adhesion through active changing the curvature of the pad. Inspired by these biological systems, an artificial model system is developed here. It consists of an inflatable membrane clamped to the metallic cylinder and filled with air. Pull-off force measurements of the membrane surface were conducted in contact with the membrane at five different radii of curvature r c with (1) a smooth polyvinylsiloxane membrane and (2) mushroom-shaped adhesive microstructured membrane made of the same polymer. The hypothesis that an increased internal pressure, acting on the membrane, reduces the radius of the membrane curvature, resulting in turn in a lower pull-off force, is verified. Such an active control of adhesion, inspired by biological models, will lead to the development of industrial pick-and-drop devices with controllable adhesive properties.

  2. Controlled positioning of nanobeads by strayfields of artificial topographically flat magnetic patterns generated by keV-He-ion bombardment

    International Nuclear Information System (INIS)

    Ion bombardment induced lateral magnetic patterning (IBMP) has been used to generate different magnetic patterns (artificial domains) in an IrMn/NiFe bilayer system without changes in the surface topography. This technique enables to create areas with effective antiparallel magnetizations in adjacent patterns stable in remanence. In the resulting stray fields (essentially emitted by the artificial domain walls) it is possible to position nanobeads along these walls. The dependence of this positioning on the domain wall width, domain wall type and size of the nanobeads is discussed, and first results are presented.

  3. Materials and techniques for controllable microwave surfaces

    Science.gov (United States)

    Barnes, Alan; Ford, Kenneth L.; Wright, Peter V.; Chambers, Barry; Smith, Christopher D.; Thompson, Denise A.; Pavri, Francis

    2000-08-01

    Discs and waveguide samples of polymeric mixed conductor nanocomposite materials comprising a conducting polymer and redox active switching agent in a polymer electrolyte have been prepared and studied. These novel materials have been shown to exhibit large, rapid and reversible changes in their microwave impedance when small d.c. electric fields are applied across them from the edges. The results of simultaneous cyclic voltammetry or potential square waves and microwave transmission measurements have shown that the changes are apparantly instantaneous with the application or removal of the applied field. Analysis of the microwave results has shown that the impedance of the materials changes by a factor of up to almost 50 with the imposition or removal of the fields. Nanocomposite materials having either poly(pyrrole) or poly(aniline) as the conducting polymer component and either silver/silver tetrafluoroborate or copper/copper(II) tetrafluoroborate as the redox active components have been investigated. The results of the nanocomposite materials are compared with those of microparticulate composities of similar composition. A new configuration of single layer tunable microwave absorber using only resistive control has been investigated and shown to exhibit wideband, low reflectivity performance combined with reduced thickness. A major advantage of the new topology is the requirement for only a 3:1 change in controllable resistance.

  4. 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...

  5. Control of Robot Interaction Forces Using Evolutionary Techniques

    OpenAIRE

    de Gea, Jose; Kassahun, Yohannes; Kirchner, Frank

    2010-01-01

    The work presented describes the design of an ANN-based impedance controller by using evolutionary techniques. The impedance controller is first discretized and represented as a neural network. The use of evolutionary techniques provides a simple methodology to evolve the controller requiring only the definition of a proper performance criteria to be optimised. Currently, unclear or cumbersome methodologies are found to select impedance parameters. The proposed approach obtains optimal parame...

  6. 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.

  7. Landfill pollution control with isotope techniques

    International Nuclear Information System (INIS)

    Groundwater and surface water contamination by sanitary landfills is being monitored since 1989 in Italy by using isotope techniques combined with chemical analyses. The results obtained are considered mostly satisfactory for identifying sources of contaminants and predicting their behaviour. We present in this work the results of chemical and isotopic measurements performed on rainwater, surface water and groundwater samples, with the aim of investigating the fate of contaminants released from some landfills located near Ancona, Central Italy. The isotope determinations included δ18O, δ2H and tritium (3H). The first objective of these investigations is establishing the background values of the main environmental parameters related to contamination, and obtaining indication about source and residence time (age) of groundwater in the landfill proximity. In particular, the methods used for detecting groundwater and/or surface waters contamination derived from the landfill, are based on the occurrence of tritium activity anomalies and chemical concentration changes. In order to estimate the regional background of environmental tritium in shallow groundwater, we measured the tritium content of monthly rainwater samples collected in stations on the Apennines in proximity of Ancona. The tritium concentration ranged from 3 to 6 TU in winter months (October to April), and reached the maximum values (up to 14 TU) in summer months. The investigations of groundwater and surface water contamination were undertaken on landfills dismissed from 1986 to 1998. The isotopic and chemical monitoring was started one year ago and was carried out on leachates, surface waters and groundwater (the last sampled in several downstream wells). The tritium concentration in leachates can be very high, due to a still active tritium release from the landfill. Tritium values in wells outside of the landfill area, lower than in leachate but higher than the regional background of environmental

  8. SIMULATION OF BLDC MOTOR CONTROL USING SLIDING MODE CONTROL TECHNIQUE

    OpenAIRE

    Namita P. Galphade; Subhash S. Sankeshwari

    2015-01-01

    Mostly, Brushless DC motors have been used in various industrial and domestic applications because of its advantages like simple structure, large torque, long use time, good speed regulation. Generally the BLDCM systems have uncertain and nonlinear characteristics which degrade performance of controllers. Based on these reasons, Sliding Mode Control (SMC) is one of the popular control strategies to deal with the nonlinear uncertain system. In This work implemented a SMC scheme for effective s...

  9. Fault detection and diagnosis using statistical control charts and artificial neural networks

    International Nuclear Information System (INIS)

    In order to operate a successful plant or process, continuous improvement must be made in the areas of safety, quality and reliability. Central to this continuous improvement is the early or proactive detection and correct diagnosis of process faults. This research examines the feasibility of using Cumulative Summation (CUSUM) Control Charts and artificial neural networks together for fault detection and diagnosis (FDD). The proposed FDD strategy was tested on a model of the heat transport system of a CANDU nuclear reactor. The results of the investigation indicate that a FDD system using CUSUM Control Charts and a Radial Basis Function (RBF) neural network is not only feasible but also of promising potential. The control charts and neural network are linked together by using a characteristic fault signature pattern for each fault which is to be detected and diagnosed. When tested, the system was able to eliminate all false alarms at steady state, promptly detect 6 fault conditions and correctly diagnose 5 out of the 6 faults. The diagnosis for the sixth fault was inconclusive. (author). 9 refs., 6 tabs., 7 figs

  10. 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.

  11. Controlling the Twin Wire Arc Spray Process Using Artificial Neural Networks (ANN)

    Science.gov (United States)

    Hartz-Behrend, K.; Schaup, J.; Zierhut, J.; Schein, J.

    2016-01-01

    One approach for controlling the twin wire arc spray process is to use optical properties of the particle beam as input parameters for a process control. The idea is that changes in the process like eroded contact nozzles or variations of current, voltage, and/or atomizing gas pressure may be detected through observation of the particle beam. It can be assumed that if these properties deviate significantly from those obtained from a beam recorded for an optimal coating process, the spray particle and thus the coating properties change significantly. The goal is to detect these deviations and compensate the occurring errors by adjusting appropriate process parameters for the wire arc spray unit. One method for monitoring optical properties is to apply the diagnostic system particle flux imaging (PFI): PFI fits an ellipse to an image of a particle beam thereby defining easy to analyze characteristical parameters by relating optical beam properties to ellipse parameters. Using artificial neural networks (ANN), mathematical relations between ellipse and process parameters can be defined. It will be shown that in the case of a process disturbance through the use of an ANN-based control new process parameters can be computed to compensate particle beam deviations.

  12. Advancements in artificial heart valve disks using nano-sized thin films deposited by CVD and sol-gel techniques

    International Nuclear Information System (INIS)

    Pyrolytic carbon (PyC) is widely used in manufacturing commercial artificial heart valve disks (HVD). Although, PyC is commonly used in HVD, it is not the best material for this application since its blood compatibility is not ideal for prolonged clinical use. As a result thrombosis often occurs and the patients are required to take anti- coagulation drugs on a regular basis in order to minimise the formation of thrombosis. However, the anti-coagulation therapy gives rise to some detrimental side effects in patients. Therefore, it is extremely urgent that newer and more technically advanced materials with better surface and bulk properties are developed. In this paper, we report the mechanical properties of PyC-HVD, namely, strength, wear resistance and coefficient of friction. The strength of the material was assessed using Brinell indentation tests. Furthermore, wear resistance and the coefficient of friction values were obtained from the pin-on-disk testing. The micro-structural properties of PyC were characterized using XRD, Raman spectroscopy and SEM analysis. Also, in this paper we report the preparation of free standing nanocrystalline diamond films (FSND) using the time-modulated chemical vapor deposition (TMCVD) process. Furthermore, the sol-gel technique was used to uniformly coat PyC-HVD with dense, nanocrystalline-titanium oxide (nc-TiO/sub 2/) coatings. The as-grown nc-TiO/sub 2/ coatings were characterized for microstructure using SEM and XRD analysis. (author)

  13. 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.

  14. Hybrid control using evolutionary tuned fuzzy controller techniques - a study

    OpenAIRE

    Stirrup, R.; Chipperfield, A.; Tang, K.S.; Man, K.F.

    2002-01-01

    Many real world systems exist that have operating regions or regimes that exhibit varying degrees of non-lineararity. An example of this are the significant variations in the dynamic characteristics of a distributed collector field within a solar power plant. Her a gain schedule controller using pole placement with feedforward was chosen to control the more linear operating regimes of the plant. Then a study was carried out to find the best suited and most efficient evolutionary-tuned fuzz...

  15. Using Artificial Intelligence Models in System Identification

    OpenAIRE

    Elshamy, Wesam

    2013-01-01

    Artificial Intelligence (AI) techniques are known for its ability in tackling problems found to be unyielding to traditional mathematical methods. A recent addition to these techniques are the Computational Intelligence (CI) techniques which, in most cases, are nature or biologically inspired techniques. Different CI techniques found their way to many control engineering applications, including system identification, and the results obtained by many researchers were encouraging. However, most...

  16. Optimal and suboptimal control technique for aircraft spin recovery

    Science.gov (United States)

    Young, J. W.

    1974-01-01

    An analytic investigation has been made of procedures for effecting recovery from equilibrium spin conditions for three assumed aircraft configurations. Three approaches which utilize conventional aerodynamic controls are investigated. Included are a constant control recovery mode, optimal recoveries, and a suboptimal control logic patterned after optimal recovery results. The optimal and suboptimal techniques are shown to yield a significant improvement in recovery performance over that attained by using a constant control recovery procedure.

  17. Using statistical quality control techniques to monitor blood glucose levels.

    OpenAIRE

    Oniki, T. A.; Clemmer, T. P.; Arthur, L. K.; Linford, L. H.

    1995-01-01

    Continuous Quality Improvement techniques developed in industry are increasingly being applied to the medical field. Statistical process control charts are a CQI technique aimed at monitoring a process and its variability. At our hospital, statistical quality control charts are being constructed from laboratory blood glucose measurements of patients receiving enteral or parenteral nutrition. The charts will be used to monitor glucose levels, reveal variations, and illustrate the effects of ne...

  18. 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.

  19. Establishment of an artificial β-cell line expressing insulin under the control of doxycycline

    Institute of Scientific and Technical Information of China (English)

    Xin-Yu Qin; Kun-Tang Shen; Xin Zhang; Zhi-Hong Cheng; Xiang-Ru Xu; Ze-Guang Han

    2002-01-01

    AIM: Artificial β-cell lines may offer an abundant source of calls for the treatment of type Ⅰ diabetes, but insulin secretion in β-cells is tightly regulwted in physiological conditions The Tet-On system is a "gene switch" system,which can induce gene expression by administration of tetracycline (Tet) derivatives such as doxcycline (D ox).Using this system, we established 293 cells to an artificial cell line secreting insulin in response to stimulation by Dox.METHODS: The mutated proinsulin cDNA was obtained fromplasmid pcDNA3.1/C-mlNS by the polymerase chain reaction(PCR), and was inserted downstream from the promoter onthe expression vector pTRE2, to construct a recombinedexpression vector pTRE2mlNS. The promoter on pTRE2consists of the tetracycline-response element and the CMVminimal promoter and is thus activated by the reversetetracycline-controlled transactivator (rtTA) when Dox isadministrated. pTRE2mlNS and plasmid pTK-Hyg encodinghygromycin were co-transfected in the tet293 cells, whichexpress rtTA stably. Following hygromycin screening, thesurvived cells expressing insulin were selected andenriched. Dox was used to control the expression of insulinin these cells. At the levels of mRNA and protein, theregulating effect of Dox in culture medium on the expressionof proinsulin gene was estimated respectively with Northernblot, RT-PCR, and radioimmunoassay.RESULTS: From the 28 hygromycin-resistant cell strains, weselected one cell strain (tet293/Ins6) secreting insulin notonly automatically, but in response to stimulation by Dox.The amount on insulin secretion was dependent on the Doxdose (0,10,100,200,400,800 and 1000 μg@ L-1 ), the level ofinsulin secreted by the cells treated with Dox ( 1000μg. L-1 )wes 241.0 pU@d1 @cell-1 , which was 25-fold that of 9.7 pU@d1@ cell-1 without Dox treatment. Northern blot analyses andRT-PCR further confinned that the transcription of insulingene had already been up-regulated after exposing tet293/Ins6 cells to Dox for

  20. Pig Artificial Insemination Techniques and Factors Discussed%猪人工授精技术和影响因素讨论

    Institute of Scientific and Technical Information of China (English)

    黄汉良

    2014-01-01

    As technology becomes more sophisticated modern pig insemination, to work in this field technicians put forward higher requirements, requiring mastery of the relevant technology to control the factors that affect the success rate of fertilization. In this regard, elaborated pig semen quality detection technology, breeding sows, semen preservation and insemination techniques, so that the number of swine artificial insemination conception rate and production to reach the expected level in order to provide a reference for future work.%随着现代猪人工授精技术越来越精湛,对从事这方面工作的技术人员提出了更高的要求,要求其熟悉掌握相关技术,能够控制影响授精成功率的因素。对此,阐述了猪精液的质量检测技术、母猪的饲养、精液保存和输精技术等,使猪人工授精的受胎率和生产数达到预期水平,以期为今后工作提供借鉴。

  1. Artificial noses.

    Science.gov (United States)

    Stitzel, Shannon E; Aernecke, Matthew J; Walt, David R

    2011-08-15

    The mammalian olfactory system is able to detect many more odorants than the number of receptors it has by utilizing cross-reactive odorant receptors that generate unique response patterns for each odorant. Mimicking the mammalian system, artificial noses combine cross-reactive sensor arrays with pattern recognition algorithms to create robust odor-discrimination systems. The first artificial nose reported in 1982 utilized a tin-oxide sensor array. Since then, however, a wide range of sensor technologies have been developed and commercialized. This review highlights the most commonly employed sensor types in artificial noses: electrical, gravimetric, and optical sensors. The applications of nose systems are also reviewed, covering areas such as food and beverage quality control, chemical warfare agent detection, and medical diagnostics. A brief discussion of future trends for the technology is also provided. PMID:21417721

  2. 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.

  3. 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.

  4. Active vibration control techniques for flexible space structures

    Science.gov (United States)

    Parlos, Alexander G.; Jayasuriya, Suhada

    1990-01-01

    Two proposed control system design techniques for active vibration control in flexible space structures are detailed. Control issues relevant only to flexible-body dynamics are addressed, whereas no attempt was made to integrate the flexible and rigid-body spacecraft dynamics. Both of the proposed approaches revealed encouraging results; however, further investigation of the interaction of the flexible and rigid-body dynamics is warranted.

  5. Comparison of Suspended Branch and Direct Infestation Techniques for Artificially Infesting Hemlock Seedlings with the Hemlock Woolly Adelgid for Resistance Screening

    OpenAIRE

    Zaidee L. Powers; Mayfield, Albert E.; John Frampton; Jetton, Robert M.

    2015-01-01

    The hemlock woolly adelgid (Adelges tsugae Annand) is an invasive forest pest in eastern North America that has caused significant decline and mortality in populations of eastern hemlock (Tsuga canadensis (L.) Carr.) and Carolina hemlock (T. caroliniana Engelm.). The breeding of adelgid-resistant genotypes for reforestation activities is still in the early development phases, and most resistance screening programs have depended on labor-intensive direct artificial infestation techniques for...

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

    OpenAIRE

    Aline Luiza Tomazi; Carlos Eduardo Zimmermann; Rudi Ricardo Laps

    2010-01-01

    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, Br...

  7. vitisFlower®: Development and Testing of a Novel Android-Smartphone Application for Assessing the Number of Grapevine Flowers per Inflorescence Using Artificial Vision Techniques

    OpenAIRE

    Arturo Aquino; Borja Millan; Daniel Gaston; María-Paz Diago; Javier Tardaguila

    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...

  8. Left and right pump output control in one-piece electromechanical total artificial heart.

    Science.gov (United States)

    Takatani, S; Shiono, M; Sasaki, T; Orime, Y; Sakuma, I; Noon, G; Nosé, Y; DeBakey, M

    1993-03-01

    Left master alternate (LMA) ejection control based on the left pump fill method was implemented for a one-piece electromechanical total artificial heart (TAH). The TAH consists of left and right pusher-plate-type blood pumps sandwiching a compact electromechanical actuator comprising a direct current (DC) brushless motor and a planetary roller screw. The motor rotation is controlled on the basis of the roller-screw position as detected by a Hall effect sensor and a commutation pulse counting method. Since the pusher-plate shaft and roller screw are decoupled during filling, both pumps fill passively with the right and left atrial pressure. To obtain response to the right atrial pressure change in the LMA mode, the left fill trigger level as detected by a Hall effect position sensor is adjusted to operate the pump at a higher rate and to drive the right pump at 85-90% of the full stroke level. The in vitro evaluation demonstrated that this method can respond to right atrial pressure changes provided that the right pump is operated at less than the full stroke level. When the preload is high and the right pump goes into full stroke operation, the left eject level can be decreased to run the pump at a higher rate and to transfer more blood from the right to the left. In the in vivo evaluation, which lasted 1 week in a 95 kg calf, the left and right atrial pressures were kept within physiological ranges.(ABSTRACT TRUNCATED AT 250 WORDS) PMID:8215943

  9. Engine control techniques to account for fuel effects

    Energy Technology Data Exchange (ETDEWEB)

    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.

  10. 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

  11. 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.

  12. Rewritable artificial magnetic charge ice

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Yong-Lei; Xiao, Zhili; Snezhko, Alexey; Xu, Jing; Ocola, Leonidas E.; Divan, Ralu; Pearson, John E.; Crabtree, George W.; Kwok, Wai-Kwong

    2016-05-20

    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.

  13. Rewritable artificial magnetic charge ice

    Science.gov (United States)

    Wang, Yong-Lei; Xiao, Zhi-Li; Snezhko, Alexey; Xu, Jing; Ocola, Leonidas E.; Divan, Ralu; Pearson, John E.; Crabtree, George W.; Kwok, Wai-Kwong

    2016-05-01

    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. Evolutionary biology and genetic techniques for insect control

    OpenAIRE

    Leftwich, Philip; Bolton, Michael; Chapman, Tracey

    2016-01-01

    Abstract The requirement to develop new techniques for insect control that minimize negative environmental impacts has never been more pressing. Here we discuss population suppression and population replacement technologies. These include sterile insect technique, genetic elimination methods such as the release of insects carrying a dominant lethal (RIDL), and gene driving mechanisms offered by intracellular bacteria and homing endonucleases. We also review the potential of newer or underutil...

  15. 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)

  16. Application of the 222Rn technique for estimating the residence times of artificially recharged groundwater: Hengsen water catchment area, Dortmunder Stadtwerke AG

    International Nuclear Information System (INIS)

    Recently, a new technique was established to estimate groundwater residence times of up to about 15 days. The technique assumes that the ingrowth of 222Rn upon infiltration and movement in the ground can be described by the growth law of radioactivity. Radon-222 emanates from mineral grains by alpha recoil or by diffusion. It dissolves in the groundwater and migrates in the aquifer without interactions. This was confirmed at two sites of naturally infiltrating rivers and at a canal where the saturated aquifer is recharged. In this poster, we give results from the application of the method to a water catchment area with artificial groundwater recharge. 2 refs, 1 fig

  17. Object oriented programming techniques applied to device access and control

    International Nuclear Information System (INIS)

    In this paper a model, called the device server model, has been presented for solving the problem of device access and control faced by all control systems. Object Oriented Programming techniques were used to achieve a powerful yet flexible solution. The model provides a solution to the problem which hides device dependancies. It defines a software framework which has to be respected by implementors of device classes - this is very useful for developing groupware. The decision to implement remote access in the root class means that device servers can be easily integrated in a distributed control system. A lot of the advantages and features of the device server model are due to the adoption of OOP techniques. The main conclusion that can be drawn from this paper is that 1. the device access and control problem is adapted to being solved with OOP techniques, 2. OOP techniques offer a distinct advantage over traditional programming techniques for solving the device access problem. (J.P.N.)

  18. A time-delay suppression technique for DPWM control circuit

    OpenAIRE

    Ishizuka, Yoichi; Hirose, Fumitoshi; Yamada, Yusuke; Matsuo, Hirofumi

    2009-01-01

    A proposed design of a low-cost digital pulse width modulation (DPWM) control circuit for non-isolated DC-DC converter without A/D converter is described. Also, propsed real-time PID control technique for DPWM is described. Some experimental results and simulation results are revealed the proposed circuit and scheme. The purpose of this research is striking a balance between minimizing cost increase by digitalizing of the control circuit of DC-DC converter and speeding up the control circuit.

  19. Hydrologic control of dissolved organic matter concentration and quality in a semiarid artificially drained agricultural catchment

    Science.gov (United States)

    Bellmore, Rebecca A.; Harrison, John A.; Needoba, Joseph A.; Brooks, Erin S.; Kent Keller, C.

    2015-10-01

    Agricultural practices have altered watershed-scale dissolved organic matter (DOM) dynamics, including in-stream concentration, biodegradability, and total catchment export. However, mechanisms responsible for these changes are not clear, and field-scale processes are rarely directly linked to the magnitude and quality of DOM that is transported to surface water. In a small (12 ha) agricultural catchment in eastern Washington State, we tested the hypothesis that hydrologic connectivity in a catchment is the dominant control over the concentration and quality of DOM exported to surface water via artificial subsurface drainage. Concentrations of dissolved organic carbon (DOC) and humic-like components of DOM decreased while the Fluorescence Index and Freshness Index increased with depth through the soil profile. In drain discharge, these characteristics were significantly correlated with drain flow across seasons and years, with drain DOM resembling deep sources during low-flow and shallow sources during high flow, suggesting that DOM from shallow sources bypasses removal processes when hydrologic connectivity in the catchment is greatest. Assuming changes in streamflow projected for the Palouse River (which contains the study catchment) under the A1B climate scenario (rapid growth, dependence on fossil fuel, and renewable energy sources) apply to the study catchment, we project greater interannual variability in annual DOC export in the future, with significant increases in the driest years. This study highlights the variability in DOM inputs from agricultural soil to surface water on daily to interannual time scales, pointing to the need for a more nuanced understanding of agricultural impacts on DOM dynamics in surface water.

  20. Metamodeling Techniques Applied to the Design of Reconfigurable Control Applications

    Directory of Open Access Journals (Sweden)

    Luca Ferrarini

    2008-02-01

    Full Text Available In order to realize autonomous manufacturing systems in environments characterized by high dynamics and high complexity of task, it is necessary to improve the control system modelling and performance. This requires the use of better and reusable abstractions. In this paper, we explore the metamodel techniques as a foundation to the solution of this problem. The increasing popularity of model-driven approaches and a new generation of tools to support metamodel techniques are changing software engineering landscape, boosting the adoption of new methodologies for control application development.

  1. 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.

  2. 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

  3. 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.

  4. Analysis of Dynamic Road Traffic Congestion Control (DRTCC) Techniques

    OpenAIRE

    Pardeep Mittal; Yashpal Singh,; Yogesh Sharma

    2015-01-01

    : Dynamic traffic light control at intersection has become one of the most active research areas to develop the Dynamic transportation systems (ITS). Due to the consistent growth in urbanization and traffic congestion, such a system was required which can control the timings of traffic lights dynamically with accurate measurement of traffic on the road. In this paper, analysis of all the techniques that has been developed to automate the traffic lights has been done.. The efficacy...

  5. SINGLE - PHASE INVERTER CONTROL TECHNIQUES FOR INTERFACING RENEWABLE ENERGY SOURCES

    OpenAIRE

    C.Nallasivam

    2015-01-01

    A novel current control technique is proposed to control power flow from a renewable energy source feeding a microgrid system through a three - phase parallel - connected inverter. The parallel - connected inverter ensures that the power flow from the grid with low - current total harmonic distortion even in the presence of nonlinear load. The renewable energy sources ar e paralleled, and the average of this constant sup...

  6. Development of irradiation technique on controlling food contamination residue

    International Nuclear Information System (INIS)

    The current state of the researches of irradiation technology on controlling food mycotoxin, pesticide, veterinary drugs and fishery drugs residue was summarized. And the degradation rate, mechanism, products and toxicities of food contamination were expatiated. The free radical from irradiation attack the site of weaker bond, and the less or more toxic substances were produced, which lead to the degradation of the food contamination. The limitations and future application of irradiation technique on controlling food contamination were also analyzed. (authors)

  7. Sterile insect technique and radiation in insect control

    International Nuclear Information System (INIS)

    Out of 39 papers and 6 summaries of the poster presentations published in this proceeding series, 23 respectively fall within the INIS subject scope. Four main topics were covered: a review of the sterile insect technique against various insect pests; its application to tsetse flies in eradication programmes; quality control of mass-reared insects for release; and the development of genetic approaches to insect mass rearing and control. Other topics emphasized integrated pest management, computer models and radioisotope labelling

  8. Tsetse control, diagnosis and chemotherapy using nuclear techniques

    International Nuclear Information System (INIS)

    The focus of the seminar was on recent advances in the use of nuclear techniques in the diagnosis and control of tsetse-transmitted trypanosomiasis. The proceedings contain the full text of sixteen selected papers addressing the disease and its diagnosis, chemotherapy, vector biology, ecology and control. Synopses of the other papers presented are also included. The individual contributions are indexed separately. Refs, figs and tabs

  9. Reinforcement Learning Technique in Multiple Motorway Access Control Strategy Design

    OpenAIRE

    Veljanovska, Kostandina; M. Bombol, Kristi; Maher, Tomaž

    2010-01-01

    An appropriately designed motorway access control can decrease the total travel time spent in the system up to 30% and consequently increase the merging operations safety. To date, implemented traffic responsive motorway access control systems have been of local or regulatory type and not truly adaptive in the real sense of the meaning. Hence, traffic flow can be influenced positively by numerous intelligent transportation system (ITS) techniques. In this paper a contemporary approach is pres...

  10. 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.

  11. The sterile insect technique for control of tsetse flies in Africa

    International Nuclear Information System (INIS)

    The tsetse fly is the major vector of trypanosomiasis in Africa. At various places in Africa, tsetse control and eradication studies are under way, mostly relying on insecticides. However, two sterile insect programmes are in an executionary phase as field research projects. A third project, in Nigeria, will be carried out by the Joint FAO/IAEA Division, in close collaboration with the Nigerian Government. The Seibersdorf Entomology Laboratory (Austria) is studying several basic aspects of the fly's biology. Research is now being conducted on mass-rearing techniques. An artificial membrane has been developed to replace living hosts and has proved effective, stretched over a pool of blood. Sterilization of flies by 12-17 rad of gamma radiation from a cobalt-60 source without enfeebling their mating behaviour in the field is also investigated at Seibersdorf. Training facilities are available for scientists from developing countries

  12. 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.

  13. Genetic techniques in insect pest control: an overview

    Czech Academy of Sciences Publication Activity Database

    Marec, František

    1998-01-01

    Roč. 71, - (1998), s. 40. [ FAO /IAEA International Conference on area-wide control of insect pests integrating the sterile insect and related nuclear and other techniques. 28.05.1998-02.06.1998, Penang] Keywords : Cochliomyia hominivorax * Ceratitis capitata Subject RIV: EB - Genetics ; Molecular Biology

  14. Materials and techniques for spacecraft static charge control 2

    Science.gov (United States)

    Schmidt, R. E.; Eagles, A. E.

    1979-01-01

    Results of exploratory development on the design, fabrication and testing of transparent conductive coatings, conductive bulk materials and grounding techniques for application to high resistivity spacecraft dielectric materials to obtain control of static charge buildup are presented. Deposition techniques for application of indium oxide, indium/tin oxide and other metal oxide films on Kapton, FEP Teflon, OSR and solar cell coverglasses discussed include RF and Magnetron sputtering and vapor deposition. Development, fabrication and testing of conductive glass tiles for OSR and solar cell coverglass applications is discussed. Several grounding techniques for rapid charge dissipation from the conductively coated polymer and glass dielectrics which were developed and tested in thermal cycled and electron plasma environments are described. The optical and electrical characterization and aging effects of these coatings, bulk materials and grounding techniques are reviewed as they apply to the performance of their design functions in a geosynchronous orbit environment.

  15. 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)

  16. Quantum coherence controls the charge separation in a prototypical artificial light harvesting system

    Directory of Open Access Journals (Sweden)

    Schramm H.

    2013-03-01

    Full Text Available Ultrafast spectroscopy and quantum-dynamics simulations of an artificial supramolecular light-harvesting system — a supramolecular triad - provide strong evidence that the quantum-correlated wavelike motion of electrons and nuclei on a timescale of few tens of femtoseconds governs the ultrafast electronic charge transfer.

  17. 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

  18. 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

    2015-06-01

    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

  19. Reinforcement learning output feedback NN control using deterministic learning technique.

    Science.gov (United States)

    Xu, Bin; Yang, Chenguang; Shi, Zhongke

    2014-03-01

    In this brief, a novel adaptive-critic-based neural network (NN) controller is investigated for nonlinear pure-feedback systems. The controller design is based on the transformed predictor form, and the actor-critic NN control architecture includes two NNs, whereas the critic NN is used to approximate the strategic utility function, and the action NN is employed to minimize both the strategic utility function and the tracking error. A deterministic learning technique has been employed to guarantee that the partial persistent excitation condition of internal states is satisfied during tracking control to a periodic reference orbit. The uniformly ultimate boundedness of closed-loop signals is shown via Lyapunov stability analysis. Simulation results are presented to demonstrate the effectiveness of the proposed control. PMID:24807456

  20. Advanced analytical techniques for boiling water reactor chemistry control

    International Nuclear Information System (INIS)

    The analytical techniques applied can be divided into 5 classes: OFF-LINE (discontinuous, central lab), AT-LINE (discontinuous, analysis near loop), ON-LINE (continuous, analysis in bypass). In all cases pressure and temperature of the water sample are reduced. In a strict sense only IN-LINE (continuous, flow disturbance) and NON-INVASIVE (continuous, no flow disturbance) techniques are suitable for direct process control; - the ultimate goal. An overview of the analytical techniques tested in the pilot loop is given. Apart from process and overall water quality control, standard for BWR operation, the main emphasis is on water impurity characterization (crud particles, hot filtration, organic carbon); on stress corrosion crackling control for materials (corrosion potential, oxygen concentration) and on the characterization of the oxide layer on austenites (impedance spectroscopy, IR-reflection). The above mentioned examples of advanced analytical techniques have the potential of in-line or non-invasive application. They are different stages of development and are described in more detail. 28 refs, 1 fig., 5 tabs

  1. Insect population control by the sterile-male technique

    International Nuclear Information System (INIS)

    The successful use of the sterile male technique to eradicate the screw worm fly from the Southeastern part of the United States showed that a new biological method using radiation-sterilized insects could not only control but also eradicate harmful insect pests. A panel of experts met at the IAEA in Vienna in October 1962 to discuss the various aspects and applications of this new technique and to assess its usefulness and limitations. This report summarizes the panel proceedings. 42 refs, 18 figs, 1 tab

  2. Management techniques and methods used to computerize work control processes

    International Nuclear Information System (INIS)

    With the thrust of this meeting being ...to articulate the nuclear power industry's vigorous move toward excellence in operations and that such excellence is both cost-effective and safety enhancing, the subject of this paper is how the Point Beach Nuclear Power Plant instituted a computerized work control and data processing system. The paper deals with the goals established and the approaches used. Also included is a description of the mechanisms and techniques utilized and an assessment of successes. It is hoped that by articulating the management techniques and methods used to institute a major functional and organizational change at Point Beach Nuclear Plant, the presentation will be beneficial

  3. 家蚕人工授精关键技术的研究%Study on Key Technique of Artificial Insemination for Silkworm, Bombyx mori

    Institute of Scientific and Technical Information of China (English)

    张业顺; 张国政; 韦亚东; 夏定国

    2009-01-01

    [Objective] The aim of this study was to investigate the efficient technique of artificial insemination for silkworm. [Method] Sperms were extracted from bursa copulatrix of female moths mated for 30 min through extruding and centrifugal method, and then the semen was injected into other virgin moths with trypsinase. [Result] A high-effective collection technology of spermatids from silkworm was established successfully, 50 μl semen could be collected by only one person in each hour. The survival rate of spermatids was over 80% in vito after collected from bursa copulatrix, while the obtained semen was quite pure and the average fertilization rate of silkworm was 76.5%. [Conclusion] The establishment of high-effective semen extraction technique of silkworm provides the technical basis for studies on other related techniques for silkworm sperm.

  4. 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

  5. Improvement in separation of isolated muons and pions at low pT in ATLAS hadron calorimeter using artificial neural networks technique

    International Nuclear Information System (INIS)

    Advantages of artificial neural networks techniques in handling data from highly granulated ATLAS hadron calorimeter (HC) are shown in application to isolated π/μ separation task in the range 3 TT muons have a significant probability to be absorbed in the calorimeter and therefore they cannot be reliably registered by the muon detector. The comparative analysis of main characteristics is presented for several neural net discriminators and a linear threshold discriminator operating on energy deposition in the last depth of HC. The analysis is based on MC data obtained with ATLAS simulation programs. 9 refs., 12 figs

  6. Distributed flow estimation and closed-loop control of an underwater vehicle with a multi-modal artificial lateral line.

    Science.gov (United States)

    DeVries, Levi; Lagor, Francis D; Lei, Hong; Tan, Xiaobo; Paley, Derek A

    2015-04-01

    Bio-inspired sensing modalities enhance the ability of autonomous vehicles to characterize and respond to their environment. This paper concerns the lateral line of cartilaginous and bony fish, which is sensitive to fluid motion and allows fish to sense oncoming flow and the presence of walls or obstacles. The lateral line consists of two types of sensing modalities: canal neuromasts measure approximate pressure gradients, whereas superficial neuromasts measure local flow velocities. By employing an artificial lateral line, the performance of underwater sensing and navigation strategies is improved in dark, cluttered, or murky environments where traditional sensing modalities may be hindered. This paper presents estimation and control strategies enabling an airfoil-shaped unmanned underwater vehicle to assimilate measurements from a bio-inspired, multi-modal artificial lateral line and estimate flow properties for feedback control. We utilize potential flow theory to model the fluid flow past a foil in a uniform flow and in the presence of an upstream obstacle. We derive theoretically justified nonlinear estimation strategies to estimate the free stream flowspeed, angle of attack, and the relative position of an upstream obstacle. The feedback control strategy uses the estimated flow properties to execute bio-inspired behaviors including rheotaxis (the tendency of fish to orient upstream) and station-holding (the tendency of fish to position behind an upstream obstacle). A robotic prototype outfitted with a multi-modal artificial lateral line composed of ionic polymer metal composite and embedded pressure sensors experimentally demonstrates the distributed flow sensing and closed-loop control strategies. PMID:25807584

  7. 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.

  8. Most frequent nematode parasites of artificially raised pheasants (Phasianus colchicus L) and measures for their control

    OpenAIRE

    Pavlović Ivan 1; Jakić-Dimić Dobrila; Kulišić Zoran; Florestean Iulia

    2003-01-01

    Helminthoses have an important role in the pathology of artificially raised game pheasants. During the period 1997-2002. we examined a total of 1893 pheasant poults aged from 4 to 14 weeks and 1432 adult birds at several pheasanteries in Serbia. The following nematode species were found: Syngamus trachea, Ascaridia galli, A. columbae, Heterakis gallinarum, H. isolonche Capillaria gallinae (sin. C. caudinflata), C. columbae (sin. C. obsignata) and C. phasianis. The intensity of infection in to...

  9. Three machine learning techniques for automatic determination of rules to control locomotion.

    Science.gov (United States)

    Jonić, S; Janković, T; Gajić, V; Popović, D

    1999-03-01

    Automatic prediction of gait events (e.g., heel contact, flat foot, initiation of the swing, etc.) and corresponding profiles of the activations of muscles is important for real-time control of locomotion. This paper presents three supervised machine learning (ML) techniques for prediction of the activation patterns of muscles and sensory data, based on the history of sensory data, for walking assisted by a functional electrical stimulation (FES). Those ML's are: 1) a multilayer perceptron with Levenberg-Marquardt modification of backpropagation learning algorithm; 2) an adaptive-network-based fuzzy inference system (ANFIS); and 3) a combination of an entropy minimization type of inductive learning (IL) technique and a radial basis function (RBF) type of artificial neural network with orthogonal least squares learning algorithm. Here we show the prediction of the activation of the knee flexor muscles and the knee joint angle for seven consecutive strides based on the history of the knee joint angle and the ground reaction forces. The data used for training and testing of ML's was obtained from a simulation of walking assisted with an FES system [39]. The ability of generating rules for an FES controller was selected as the most important criterion when comparing the ML's. Other criteria such as generalization of results, computational complexity, and learning rate were also considered. The minimal number of rules and the most explicit and comprehensible rules were obtained by ANFIS. The best generalization was obtained by the IL and RBF network. PMID:10097465

  10. Statistic techniques of process control for MTR type

    International Nuclear Information System (INIS)

    This work aims at introducing some improvements on the fabrication of MTR type fuel plates, applying statistic techniques of process control. The work was divided into four single steps and their data were analyzed for: fabrication of U3O8 fuel plates; fabrication of U3 Si2 fuel plates; rolling of small lots of fuel plates; applying statistic tools and standard specifications to perform a comparative study of these processes. (author)

  11. An artificial-vision responsive to patient motions during computer controlled radiation therapy

    International Nuclear Information System (INIS)

    Purpose/Objectives: Automated precision radiotherapy using multiple conformal and modulated beams, requires monitoring of patient movements during irradiation. Immobilizers relying on patient cooperating in cradles have somewhat reduced positional uncertainties, but others including breathing are largely unknown. We built an artificial vision (AV) device for real-time vision of patient movements, their tracking and quantification. Method and Materials: The Artificial Vision System's 'acuity' and 'reflex' were evaluated in terms of imaged skin spatial resolutions and temporal dispersions measured using a mannequin and a fiduciated harmonic oscillator placed at 100cm isocenter. The device traced skin motion even in poorly lighted rooms without use of explicit skin fiduciation, or using standard radiotherapy skin tattoos. Results: The AV system tracked human skin at vision rates approaching 30Hz and sensitivity of 2mm. It successfully identified and tracked independent skin marks, either natural tattoos or artificial fiducials. Three alert levels triggered when patient movement exceeded preset displacements (2mm/30Hz), motion velocities (5m/sec) or acceleration (2m/sec2). Conclusion: The AV system trigger should suit for patient ventilatory gating and safety interlocking of treatment accelerators, in order to modulate, interrupt, or abort radiation during dynamic therapy

  12. Direct in vivo study of flowing blood-artificial surface interactions - an original application of dynamic isotopic techniques

    International Nuclear Information System (INIS)

    A Ge(Li) detector, associated with a data acquisition and storage unit, and a data analysis facility, was used to record sequentially the activity, related to several radioisotopes, inside an extracorporeal shunt, settled between the femoral artery and the colateral vein of an anaesthetized dog. The shunt was made of a material, the haemocompatibility of which needed to be evaluated. Before the blood was allowed to flow through the shunt, the circulation of the dog was fed with technetium- or indium-labelled biological species thought to be concerned with blood-artificial surface interactions. The method described here offers the possibility of computing kinetic parameters for these interactions. (author)

  13. Demographic and quality control parameters of Anastrepha Fraterculus (Diptera: Tephritidae) maintained under artificial rearing

    International Nuclear Information System (INIS)

    The integration of the sterile insect technique (SIT) in the management of the South American fruit fly Anastrepha fraterculus (Wiedemann) (Diptera: Tephritidae) is a promising alternative to chemically-based control in those areas where it is sympatric with Ceratitis capitata (Wiedemann) (Diptera: Tephritidae) or other tephritid species for which the SIT is being used. Implementation of the SIT requires the development of a cost effective mass-rearing protocol. In this work, we present demographic and quality control parameters for the A. fraterculus strain reared at the Estacion Experimental Agroindustrial Obispo Colombres, Tucuman, Argentina. Considering the rearing cage as the reproduction unit, we observed that fecundity is optimal during the first 3 weeks after the onset of oviposition. Fertility was constant during this period. During 2003 and 2004, some improvements were made to the existing rearing protocol, which resulted in increased larval viability, pupal weight, and adult emergence. Current weekly egg production is 1 million per week. These eggs are used to maintain the colony and to assess quality parameters. Finally, research needs leading to improved yields and fly quality are discussed. (author)

  14. Non-Destructive Testing Techniques for Research and Process Control

    International Nuclear Information System (INIS)

    Non-destructive test methods have been used primarily for the detection of defects and the rejection of faulty materials. The Oak Ridge National Laboratory has found it valuable to employ special non-destructive testing techniques as aids in materials research, component development, and process control. This paper gives three recent examples of the evolution of non-destructive testing techniques from research to process control. A current fuel-element design contains fuel pins filled with vibratorily compacted uranium and thorium oxide powder. A gamma-attenuation technique was developed to allow the homogeneity of fuel loading to be measured and was used to aid the development of fabrication techniques and equipment. Later an inspection device was built to operate remotely in a hermetically sealed and shielded facility and used for production process control. Another fuel element required fuel plates containing a uranium oxide-aluminium dispersion core with a programmed variation in the fuel loading across the width. A continuous scanning, X-ray attenuation technique was developed and used to measure fuel inhomogeneities and conformity to design contour. The technique assisted the development for both core pressing and plate-rolling practices. A system was constructed for rapid automatic evaluation of production fuel plates. These fuel plates were pressed into involute shape and assembled with alternate cooling channels. Stringent heat-transfer requirements imposed a tight tolerance on the channel dimensions. A unique eddy-current device using the ''lift-off'' characteristic was invented to insert in the very narrow channel and allow recording of dimensions both during fabrication development and actual manufacture. Another approach to fuel elements is the use of minute fuel-bearing particles coated with pyrolytic carbon to retain the fission products. Of concern are the core diameter, coating thickness and integrity, and presence of fuel in the coating

  15. 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 on the...

  16. Novel Robot Manipulator Adaptive Artificial Control: Design a Novel SISO Adaptive Fuzzy Sliding Algorithm Inverse Dynamic Like Method

    Directory of Open Access Journals (Sweden)

    Farzin Piltan

    2011-12-01

    Full Text Available Refer to the research, design a novel SISO adaptive fuzzy sliding algorithm inverse dynamic like method (NAIDLC and application to robot manipulator has proposed in order to design high performance nonlinear controller in the presence of uncertainties. Regarding to the positive points in inverse dynamic controller, fuzzy logic controller and self tuning fuzzy sliding method, the output has improved. The main objective in this research is analyses and design of the adaptive robust controller based on artificial intelligence and nonlinear control. Robot manipulator is nonlinear, time variant and a number of parameters are uncertain, so design the best controller for this plant is the main target. Although inverse dynamic controller have acceptable performance with known dynamic parameters but regarding to uncertainty, this controller\\'s output has fairly fluctuations. In order to solve this problem this research is focoused on two methodology the first one is design a fuzzy inference system as a estimate nonlinear part of main controller but this method caused to high computation load in fuzzy rule base and the second method is focused on design novel adaptive method to reduce the computation in fuzzy algorithm.

  17. Run control techniques for the Fermilab DART data acquisition system

    International Nuclear Information System (INIS)

    DART is the high speed, Unix based data acquisition system being developed by the Fermilab Computing Division in collaboration with eight High Energy Physics Experiments. This paper describes DART run-control which implements flexible, distributed, extensible and portable paradigms for the control and monitoring of data acquisition systems. We discuss the unique and interesting aspects of the run-control - why we chose the concepts we did, the benefits we have seen from the choices we made, as well as our experiences in deploying and supporting it for experiments during their commissioning and sub-system testing phases. We emphasize the software and techniques we believe are extensible to future use, and potential future modifications and extensions for those we feel are not

  18. Development of automatic control techniques for HANARO NTD driving unit

    International Nuclear Information System (INIS)

    The results of the research on the NTD automatic control techniques started from the beginning of 2001. The motor control system is designed to operate with independent and simultaneous up-down and rotation of the silicon ingot motion and the setpoint of each motor speed could be easily adjusted by the control PC. Taking a few steps of field test, its performance has been successfully verified. Then, through the actual irradiation with the real silicon ingot under 24MW of reactor power, it has been confirmed that the motor control system developed could be applied to the commercial production. Two set of Rh-type SPNDs, known as a in-core neutron detector are used for real-time monitoring of the accumulated neutron irradiation. They are installed around the center position of the irradiation sleeve and the cables are carefully routed up to the top of the pool for connection to the DC amplifier. It has been verified, by the sample irradiation test for validation of the design that the neutron measurement system gives an accurate and stable signal, which shows a good consistency with the estimation. To precisely control the target fluence, the NTD control program has been designed so that the silicon ingot be automatically removed from its irradiation hole by the pre-defined irradiation time or accumulated neutron flux. Data acquisition program has been also developed for real-time monitoring and analysis of the analog signals, like SPND flux, control rod position and reactor power. The actual position of the silicon ingot is fedback from the motor control system via the digital communication port then used as a reference signal for the data analysis. It's been proved that a few times of sample irradiation tests under real condition that the NTD control software and the data acquisition program works satisfactorily and can be used for the commercial service next year

  19. 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.

  20. 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...

  1. Optimal Design of PID Controller for the Speed Control of DC Motor by Using Metaheuristic Techniques

    Directory of Open Access Journals (Sweden)

    Mirza Muhammad Sabir

    2014-01-01

    Full Text Available DC motors are used in numerous industrial applications like servo systems and speed control applications. For such systems, the Proportional+Integral+Derivative (PID controller is usually the controller of choice due to its ease of implementation, ruggedness, and easy tuning. All the classical methods for PID controller design and tuning provide initial workable values for Kp, Ki, and Kd which are further manually fine-tuned for achieving desired performance. The manual fine tuning of the PID controller parameters is an arduous job which demands expertise and comprehensive knowledge of the domain. In this research work, some metaheuristic algorithms are explored for designing PID controller and a comprehensive comparison is made between these algorithms and classical techniques as well for the purpose of selecting the best technique for PID controller design and parameters tuning.

  2. 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

  3. 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...

  4. 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.

  5. Operant Conditioning: A Minimal Components Requirement in Artificial Spiking Neurons Designed for Bio-Inspired Robot’s Controller

    Directory of Open Access Journals (Sweden)

    André Cyr

    2014-07-01

    Full Text Available We demonstrate the operant conditioning (OC learning process within a basic bio-inspired robot controller paradigm, using an artificial spiking neural network (ASNN with minimal component count as artificial brain. In biological agents, OC results in behavioral changes that are learned from the consequences of previous actions, using progressive prediction adjustment triggered by reinforcers. In a robotics context, virtual and physical robots may benefit from a similar learning skill when facing unknown environments with no supervision. In this work, we demonstrate that a simple ASNN can efficiently realise many OC scenarios. The elementary learning kernel that we describe relies on a few critical neurons, synaptic links and the integration of habituation and spike-timing dependent plasticity (STDP as learning rules. Using four tasks of incremental complexity, our experimental results show that such minimal neural component set may be sufficient to implement many OC procedures. Hence, with the described bio-inspired module, OC can be implemented in a wide range of robot controllers, including those with limited computational resources.

  6. Nuclear and related techniques in the control of communicable diseases

    International Nuclear Information System (INIS)

    The IAEA has a programme component entitled ''Nuclear Techniques in Communicable Diseases'', the aims of which are to encourage research in the development of new methods of controlling communicable diseases and to transfer the technology to institutes in endemic regions. Implementation of the programme component includes information exchange through publications, symposiums and seminars. The two most recent seminars were held in Bombay in November 1988 and Belo Horizonte in November 1989, and a selection of the papers presented have been published in this Technical Document. Refs, figs and tabs

  7. 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.

  8. Quality control technique for high-volume atmospheric particulate sampler

    International Nuclear Information System (INIS)

    Quality control technique was developed for high-volume atmospheric particulate sampler. The flow meter of PMS-800 sampler was calibrated by an ISA1932 nozzle flow meter, and the global collection efficiency of PMS-800 sampler was tested by a type 2031 mobile sampler. The results show that the flowrate relative deviation between ISA1932 nozzle flow meter and PMS-800 sampler flow meter is less than 5%., and the global collection efficiency relative deviation between type 2031 sampler and PMS-800 sampler is less than 10%. The performance of PMS-800 sampler meets the specifications with the request of the Comprehensive Nuclear-Test-Ban Treaty. This method can be applied to quality control for high-volume atmospheric particulate sampler. (authors)

  9. Control techniques for an automated mixed traffic vehicle

    Science.gov (United States)

    Meisenholder, G. W.; Johnston, A. R.

    1977-01-01

    The paper describes an automated mixed traffic vehicle (AMTV), a driverless low-speed tram designed to operate in mixed pedestrian and vehicular traffic. The vehicle is a six-passenger electric tram equipped with sensing and control which permit it to function on existing streets in an automatic mode. The design includes established wire-following techniques for steering and near-IR headway sensors. A 7-mph cruise speed is reduced to 2 mph or a complete stop in response to sensor (or passenger) inputs. The AMTV performance is evaluated by operation on a loop route and by simulation. Some necessary improvements involving sensors, sensor pattern, use of an audible signal, and control lag are discussed. It is suggested that appropriate modifications will eliminate collision incidents.

  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. 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.

  12. Robust intelligent backstepping tracking control for uncertain non-linear chaotic systems using H∞ control technique

    International Nuclear Information System (INIS)

    The cerebellar model articulation controller (CMAC) is a non-linear adaptive system with built-in simple computation, good generalization capability and fast learning property. In this paper, a robust intelligent backstepping tracking control (RIBTC) system combined with adaptive CMAC and H∞ control technique is proposed for a class of chaotic systems with unknown system dynamics and external disturbance. In the proposed control system, an adaptive backstepping cerebellar model articulation controller (ABCMAC) is used to mimic an ideal backstepping control (IBC), and a robust H∞ controller is designed to attenuate the effect of the residual approximation errors and external disturbances with desired attenuation level. Moreover, the all adaptation laws of the RIBTC system are derived based on the Lyapunov stability analysis, the Taylor linearization technique and H∞ control theory, so that the stability of the closed-loop system and H∞ tracking performance can be guaranteed. Finally, three application examples, including a Duffing-Holmes chaotic system, a Genesio chaotic system and a Sprott circuit system, are used to demonstrate the effectiveness and performance of proposed robust control technique.

  13. 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.

  14. Evolutionary biology and genetic techniques for insect control.

    Science.gov (United States)

    Leftwich, Philip T; Bolton, Michael; Chapman, Tracey

    2016-01-01

    The requirement to develop new techniques for insect control that minimize negative environmental impacts has never been more pressing. Here we discuss population suppression and population replacement technologies. These include sterile insect technique, genetic elimination methods such as the release of insects carrying a dominant lethal (RIDL), and gene driving mechanisms offered by intracellular bacteria and homing endonucleases. We also review the potential of newer or underutilized methods such as reproductive interference, CRISPR technology, RNA interference (RNAi), and genetic underdominance. We focus on understanding principles and potential effectiveness from the perspective of evolutionary biology. This offers useful insights into mechanisms through which potential problems may be minimized, in much the same way that an understanding of how resistance evolves is key to slowing the spread of antibiotic and insecticide resistance. We conclude that there is much to gain from applying principles from the study of resistance in these other scenarios - specifically, the adoption of combinatorial approaches to minimize the spread of resistance evolution. We conclude by discussing the focused use of GM for insect pest control in the context of modern conservation planning under land-sparing scenarios. PMID:27087849

  15. Materials and techniques for spacecraft static charge control

    Science.gov (United States)

    Amore, L. J.; Eagles, A. E.

    1977-01-01

    An overview of the design, development, fabrication, and testing of transparent conductive coatings and conductive lattices deposited or formed on high resistivity spacecraft dielectric materials to obtain control static charge buildup on spacecraft external surfaces is presented. Fabrication techniques for the deposition of indium/tin oxide coatings and copper grid networks on Kapton and FEP Teflon films and special frit coatings for OSR and solar cell cover glasses are discussed. The techniques include sputtering, photoetching, silkscreening, and mechanical processes. A facility designed and built to simulate the electron plasma at geosynchronous altitudes is described along with test procedures. The results of material characterizations as well as electron irradiation aging effects in this facility for spacecraft polymers treated to control static charge are presented. The data presents results for electron beam energies up to 30 kV and electron current densities of 30 nA/cm squared. Parameters measured include secondary emission, surface leakage, and through the sample currents as a function of primary beam energy and voltage.

  16. GAVIAC, Sistema para la gestión y control del ganado vacuno y la inseminación artificial.GAVIAC, System for managing and control of cattle and artificial insemintaion

    Directory of Open Access Journals (Sweden)

    Roberkis Terrero Galano

    2015-07-01

    Full Text Available El control del bovino es una de las principales actividades que se debe llevar a cabo en cada una de las unidades, empresas y centros cuyo objetivo principal es la explotación del ganado vacuno. De éstos se obtienen una gran cantidad de subproductos ricos en proteínas y minerales,  los cuales son utilizados en la alimentación humana. Entre los  productos y subproductos se pueden mencionar la carne, leche, mantequilla, el queso, piel, etc. Además el mejoramiento genético del rebaño es algo que ayuda aumentar la producción, teniendo en cuenta el propósito que el centro de producción persigue. Por lo tanto la inseminación artificial en estos lugares, es muy importante para continuar mejorando la genética del lote, incrementar la productividad y contribuir de una manera eficiente en la economía del país. Para mejorar el control del ganado vacuno y la inseminación artificial, se propone como objetivo implementar un sistema informático para la gestión de estas actividades. En la realización del presente trabajo se utilizó de los métodos teóricos el analítico-sistémico y la entrevista como método empírico. Como resultado se obtuvo un sistema informatizado el cual permite la gestión de la información  relacionada con el control y la inseminación del ganado vacuno.

  17. Most frequent nematode parasites of artificially raised pheasants (Phasianus colchicus L and measures for their control

    Directory of Open Access Journals (Sweden)

    Pavlović Ivan

    2003-01-01

    Full Text Available Helminthoses have an important role in the pathology of artificially raised game pheasants. During the period 1997-2002. we examined a total of 1893 pheasant poults aged from 4 to 14 weeks and 1432 adult birds at several pheasanteries in Serbia. The following nematode species were found: Syngamus trachea, Ascaridia galli, A. columbae, Heterakis gallinarum, H. isolonche Capillaria gallinae (sin. C. caudinflata, C. columbae (sin. C. obsignata and C. phasianis. The intensity of infection in total was not high, except for infection with ascaridata and gapeworms, and depended of age of the examined birds. Consisting of anthelmintic drugs mixed with meal gave the most favourable results in therapy on rhe medicated food.

  18. Computer automation and artificial intelligence

    International Nuclear Information System (INIS)

    Rapid advances in computing, resulting from micro chip revolution has increased its application manifold particularly for computer automation. Yet the level of automation available, has limited its application to more complex and dynamic systems which require an intelligent computer control. In this paper a review of Artificial intelligence techniques used to augment automation is presented. The current sequential processing approach usually adopted in artificial intelligence has succeeded in emulating the symbolic processing part of intelligence, but the processing power required to get more elusive aspects of intelligence leads towards parallel processing. An overview of parallel processing with emphasis on transputer is also provided. A Fuzzy knowledge based controller for amination drug delivery in muscle relaxant anesthesia on transputer is described. 4 figs. (author)

  19. The application of nuclear technique for practical controlling of Ectomyelois Ceratoniae zeller (Lepidoptera: Pyralidae)

    International Nuclear Information System (INIS)

    Iran ranks the first producer and exporter of pomegranate in the world. Carob moth Ectomyelois ceratiniae(Lepidoptera: Pyralidae) has also been recognized as an important pest of pomegranate in the country. Due to biology of the pest, the application of pesticide has not been considered practical and the losses to this product are more than 30 percent of the yield. The application of Sterile Insect Technique is a method that is used on a few insects with the specific characters. This research was accomplished for evaluation of the practical control of this pest upon application of nuclear methods on pomegranate. Larval and pupal stages were collected from Saveh, transferred to Agricultural, Medical and Industrial Research School and reared on artificial diet at 28±2degreeC, 60±5% Rh, 14:10 light: dark photo period. The produced pupae (young and old) were irradiated by gamma radiation and were reared with 0:0:1:1-9:9:1:1 (Irradiated male: Irradiated female: Natural male: Natural female) ratios on pomegranate fruits in the cages. The results show that the application of sterile doses (120 and 160 Gy) on pupae (Young 1,2 days and old 3-4 days old) and releasing ratios 7:7:1:1 to 9:9:1:1 in comparison with the controlled treatment by the releasing ratio of 0:0:1:1 that prevents damage of E. ceratiniae on the pomegranate.

  20. Heat transfer optimization of two phase modeling of nanofluid in a sinusoidal wavy channel using Artificial Bee Colony technique

    Directory of Open Access Journals (Sweden)

    P. Valinataj-Bahnemiri

    2015-12-01

    Full Text Available The present study represents the heat transfer optimization of two-dimensional incompressible laminar flow of Al2O3-water nanofluids in a duct with uniform temperature corrugated walls. A two phase model is applied to investigate different governing parameters, namely: Reynolds number (100 ≤ Re ≤ 1000, nonofluids volume fraction (0% ≤ ϕ ≤ 5% and amplitude of the wavy wall (0 ≤ α ≤ 0.04 m. For optimization process, a recent spot-lighted method, called Artificial Bee Colony (ABC algorithm, is applied, and the results are shown to be in a good accuracy in comparison with another well-known heuristic method, i.e. particle swarm optimization (PSO. The results indicate that the effect of utilizing nanoparticles and increasing Reynolds number is more intensified on growing the average Nusselt number than variations of the amplitude of the wavy wall. To prevent the worst possible heat transfer, the specific amplitude which leads to a minimum average Nusselt number is detected. The effect of using nanoparticles on thermal-hydraulic performance factor (j/f is presented which considers both heat transfer and hydrodynamics aspects. The results showed that volume fraction has a direct and the wavy wall's amplitude has a converse effect on the thermal-hydraulic performance factor. Furthermore, an optimum value for Reynolds number is found to maximize the thermal-hydraulic performance factor.

  1. 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.

  2. Semen preparation techniques in intrauterine insemination: A comparison of non-temperature and temperature controlled centrifugation in cases of unexplained infertility

    OpenAIRE

    Priya Selvaraj; Kamala Selvaraj; Kalaichelvi, S.; R.Mahalakshmi

    2013-01-01

    AIM: The aim of the following study is to compare pregnancy rates between the use of non-temperature and temperature controlled centrifugation on semen preparation technique in intrauterine insemination. MATERIALS AND METHODS: The retrospective study was conducted on 671 patients of idiopathic infertility who underwent homologous artificial insemination at Fertility Research Center from the period of January 2007 to September 2012. The couples were randomized into two groups namely, Group A-p...

  3. Improvement of Power System Stability using Artificial Neural Network based HVDC Controls

    OpenAIRE

    Nagu Bhookya

    2013-01-01

    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 syste...

  4. Artificial Limbs

    Science.gov (United States)

    ... you are missing an arm or leg, an artificial limb can sometimes replace it. The device, which ... activities such as walking, eating, or dressing. Some artificial limbs let you function nearly as well as ...

  5. 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.

  6. 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.

  7. Radioimmunoassay and related techniques to improve artificial insemination programmes for cattle reared under tropical and sub-tropical conditions. Proceedings of a final research co-ordination meeting

    International Nuclear Information System (INIS)

    Artificial insemination (AI) is widely used for improvement of cattle production in developed countries. Its use in developing countries is less widespread and the results obtained are far from satisfactory. Under tropical small-farm conditions, a number of socio-economic, organizational, biological and technical factors make the service more difficult to provide and also less efficient. If the major constraints can be identified and overcome, this technology would become more widely adopted and contribute to an increased production of milk and meat, leading to better food security and poverty alleviation. The Joint FAO/IAEA Division of Nuclear Techniques in Food and Agriculture therefore convened a consultants meeting in May 1994 to advise on the applicability of radioimmunoassay (RIA) for measuring progesterone in milk of dairy cattle to identify the major causes of conception failure and reproductive wastage when AI is used under the conditions prevailing in developing countries. The consultants recommended the initiation of a co-ordinated research project (CRP) on this topic, and developed a comprehensive technical document including the sampling protocol and the range of information that needs to be recorded in order to obtain conclusive results. A five year CRP on the ''Use of RIA and Related Techniques to Identify Ways of Improving Artificial Insemination Programmes for Cattle Reared Under Tropical and Sub-Tropical Conditions'' was initiated in early 1995. The CRP resulted in the development and standardization of methodologies and protocols, including the computer software program termed AIDA (Artificial Insemination Database Application), to determine current status and identify constraints. These methodologies and protocols are now being applied on a wider scale in Member States through regional TC projects in Asia and Africa and country TC projects in Latin America. Contributing to the wider application of progesterone RIA for field level problem solving

  8. Active control technique of fractional-order chaotic complex systems

    Science.gov (United States)

    Mahmoud, Gamal M.; Ahmed, Mansour E.; Abed-Elhameed, Tarek M.

    2016-06-01

    Several kinds of synchronization of fractional-order chaotic complex systems are challenging research topics of current interest since they appear in many applications in applied sciences. Our main goal in this paper is to introduce the definition of modified projective combination-combination synchronization (MPCCS) of some fractional-order chaotic complex systems. We show that our systems are chaotic by calculating their Lyapunov exponents. The fractional Lyapunov dimension of the chaotic solutions of these systems is computed. A scheme is introduced to calculate MPCCS of four different (or identical) chaotic complex systems using the active control technique. Special cases of this type, which are projective and anti C-C synchronization, are discussed. Some figures are plotted to show that MPCCS is achieved and its errors approach zero.

  9. Nondestructive techniques for the control of conditioned radioactive wastes

    International Nuclear Information System (INIS)

    The final product of the radwaste conditioning process must satisfy certain requirments and physico-chemical properties in order to assure its safe long-term behaviour. Of course, the foreseen quality assurance and quality control should be conducted by means of non-destructive techniques. This work presents an over-view of various applicable non-destructive methods of analysis, showing their fields of investigation in testing waste packages, together with some arising practical problems. The most promising methods, such as eddy current testing, ultrasonic testing, γ-scanning, γ-spectroscopy, neutron counting and computerized tomography, are treated more deeply and some applications are presented. Particular attention is devoted to the development of a device based on computerized tomography; its essential components are reported and some design problems are also discussed

  10. Application Of Nuclear Techniques In Environmental Studies And Pollution Control

    International Nuclear Information System (INIS)

    Environmental pollution has become a world wide concern. One of the main sources of such pollution is sewage wastewater and sludge. Their utilization without proper treatment can pollute the ecosystem (plant, soil, surface and ground water). Sewage wastewater and sludge contains several pollutants such as: pathogens, toxic organic compounds, heavy metals, high level of BOD and COD, seed weed. The reuse of sewage water and sludge in agriculture can lead to the transfer of some of these pollutants into the food chain causing health hazard. In addition, most of these contaminants are not biodegradable, becoming dangerous to plant and human health. Nuclear techniques has recently been used to control environmental pollution. Ionizing radiation provide a fast and reliable means of sewage water and sludge treatment than the conventional methods. Gamma radiation ( 60Co) and electron beam (accelerator) has been successfully used for alleviation of environmental pollution. Such alleviation includes: disinfection of harmful pathogens, degradation of toxic organic pollutants, destruction of seed weed and reduction of soluble heavy metals, odor and BOD and COD. The use of radioactive and stable isotopes are a useful tools to investigate the contribution of sludge nutrients to plant nutrition. Nitrogen, using 15N-ammonium sulfate, uptake and translocation by plant from soil amended with sewage sludge was studied under field condition. The contribution of sludge to phosphorus nutrition of plants was quantified using 32p as tracer. In both cases the principal of isotopic dilution technique was applied. The information generated from these experiments could help preserve the environment. It could help optimize the application rate of sludge to meet plant requirements while avoiding the accumulation of N and P in the soil or leaching to the aquifer. Isotope exchange kinetic technique is used to evaluate nutrients availability from sludge. Neutron moisture meter is used to measure

  11. 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

  12. Advanced terahertz techniques for quality control and counterfeit detection

    Science.gov (United States)

    Ahi, Kiarash; Anwar, Mehdi

    2016-04-01

    This paper reports our invented methods for detection of counterfeit electronic. These versatile techniques are also handy in quality control applications. Terahertz pulsed laser systems are capable of giving the material characteristics and thus make it possible to distinguish between the materials used in authentic components and their counterfeit clones. Components with material defects can also be distinguished in section in this manner. In this work different refractive indices and absorption coefficients were observed for counterfeit components compared to their authentic counterparts. Existence of unexpected ingredient materials was detected in counterfeit components by Fourier Transform analysis of the transmitted terahertz pulse. Thicknesses of different layers are obtainable by analyzing the reflected terahertz pulse. Existence of unexpected layers is also detectable in this manner. Recycled, sanded and blacktopped counterfeit electronic components were detected as a result of these analyses. Counterfeit ICs with die dislocations were detected by depicting the terahertz raster scanning data in a coordinate plane which gives terahertz images. In the same manner, raster scanning of the reflected pulse gives terahertz images of the surfaces of the components which were used to investigate contaminant materials and sanded points on the surfaces. The results of the later technique, reveals the recycled counterfeit components.

  13. Limitations in artificial spin ice path selectivity: the challenges beyond topological control

    International Nuclear Information System (INIS)

    Magnetic charge is carried through nanowire networks by domain walls, and the micromagnetic structure of a domain wall provides an opportunity to manipulate its movement. We have shown previously that magnetic monopole defects exist in artificial spin ice (ASI) and result from two bar switching at a vertex. To create and manipulate monopole defects and indeed magnetic charge in general, path selectivity of the domain wall at a vertex is required. We have recently shown that in connected ASI structures, transverse wall chirality (or topology) determines wall path direction, but a mechanism known as Walker breakdown, where a wall mutates into a wall of opposite chirality partially destroys selectivity. Recently it has been claimed that in isolated Y-shaped junctions that support vortex walls, selectivity is entirely determined by chirality (or topology), the suggestion being that vortex wall chirality is robust in the Walker breakdown process. Here we demonstrate that in Y-shaped junctions, magnetic switching in the important topologically protected regime exists only for a narrow window of field and bar geometry, and that it will be challenging to access this regime in field-driven ASI. This work has implications for the wider field of magnetic charge manipulation for high density memory storage. (paper)

  14. 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

  15. Monitoring and control of UV and UV-TiO2 disinfections for municipal wastewater reclamation using artificial neural networks

    International Nuclear Information System (INIS)

    Highlights: ► ANN models can effectively control both UV and UV-TiO2 disinfections for wastewater reuse. ► Comparing to UV disinfection, UV-TiO2 disinfection can save 13.2–15.7% of UV dosage and capacity. ► SS decreases disinfection efficiency when UV doses were 2. - Abstract: The use of ultraviolet (UV) irradiation as a physical wastewater disinfection has increased in recent years, especially for wastewater reuse. The UV-TiO2 can generate OH radicals, which is highly effective to inactivate microorganisms in wastewater disinfection. However, both UV and UV-TiO2 disinfections create multiple physical, chemical, and bio-chemical phenomena that affect their germicidal efficiency. It is difficult to build a precise control model using existing mathematic models. This study applies artificial neural network (ANN) models to control UV and UV-TiO2 disinfections. Experimental results indicate that the ANN models, which precisely generate relationships among multiple monitored parameters, total coliform counts in influent and effluent, and UV doses, can be used as control models for UV and UV-TiO2 disinfections. A novel ANN control strategy is applied to control UV and UV-TiO2 disinfection processes to meet three total coliform count limits for three wastewater reuse purposes. The proposed controlled strategy effectively controls UV and UV-TiO2 disinfection, resulting in acceptable total coliform counts in effluent for the three wastewater reuse purposes. The required UV doses for UV-TiO2 disinfection were lower than those for UV disinfection, resulting in energy saving and capacity reduction of 13.2–15.7%.

  16. Modern control techniques in active flutter suppression using a control moment gyro

    Science.gov (United States)

    Buchek, P. M.

    1974-01-01

    Development of organized synthesis techniques, using concepts of modern control theory was studied for the design of active flutter suppression systems for two and three-dimensional lifting surfaces, utilizing a control moment gyro (CMG) to generate the required control torques. Incompressible flow theory is assumed, with the unsteady aerodynamic forces and moments for arbitrary airfoil motion obtained by using the convolution integral based on Wagner's indicial lift function. Linear optimal control theory is applied to find particular optimal sets of gain values which minimize a quadratic performance function. The closed loop system's response to impulsive gust disturbances and the resulting control power requirements are investigated, and the system eigenvalues necessary to minimize the maximum value of control power are determined.

  17. A graphical technique for post-analytical quality control

    International Nuclear Information System (INIS)

    No matter how great the effort, some errors will slip past quality assurance (QA), quality control (QC) and total quality management (TQM) into the analytical results. When older data or data whose QC procedures are unknown are used, the problem may be even worse. The paper demonstrates a graphical approach to 'post-analytical quality control' in elemental data for atmospheric aerosol and precipitation that relies on the chemical regularities of their three major sources, crust, sea and pollution, to display the underlying patterns of composition and to allow the analyst to visually identify data points that deviate far enough to warrant a closer look. The basic technique uses log-log scatter diagrams whose vertical axis is X/Al and whose horizontal axis is Se/Al or Na/Al. When large data sets are plotted in this way, asymptotes of either or both sources (crust/pollution or crust/marine) appear, from which elemental ratios X/Al, X/Se and X/Na in the pure crustal, pollution, and marine sources can be read directly from the plots. With practice, normal environmental variations can be distinguished from analytical errors, thus allowing various types of analytical problems to be revealed and preventing them from leading to incorrect conclusions. The paper shows several cases of analytical problems discovered in this way for aerosol and precipitation in Narragansett, Rhode Island, problems that would probably have otherwise gone unnoticed. (author)

  18. The virtual microphone technique in active sound field control systems

    Science.gov (United States)

    Lampropoulos, Iraklis E.; Shimizu, Yasushi

    2003-04-01

    Active Sound Field Control (AFC) has been proven very useful in reverberation enhancement applications in large rooms. However, feedback control is required in order to eliminate peaks in the frequency response of the system. The present research closely follows the studies of Shimizu in AFC, in which smoothing of the rooms transfer function is achieved by averaging the impulse responses of multiple microphones. ``The virtual or rotating microphone technique'' reduces the number of microphones in the aforementioned AFC technology, while still achieving the same acoustical effects in the room. After the impulse responses at previously specified pairs of microphone positions are measured, the ratio of transfer functions for every pair is calculated, thus yielding a constant K. Next, microphones are removed and their impulse responses are reproduced by processing the incoming signal of each pair through a convolver, where the computed K constants have been previously stored. Band limiting, windowing and time variance effects are critical factors, in order to reduce incoherence effects and yield reliable approximations of inverse filters and consequently calculations of K. The project is implemented in a church lacking low frequency reverberation for music and makes use of 2 physical and 2 virtual microphones.

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

    OpenAIRE

    Matija Štrbac; Slobodan Kočović; Marko Marković; 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 ...

  20. Giant Controllable Magnetization Changes Induced by Structural Phase Transitions in a Metamagnetic Artificial Multiferroic

    OpenAIRE

    Bennett, S. P.; A. T. Wong; Glavic, A.; Herklotz, A.; Urban, C; Valmianski, I.; Biegalski, M. D.; Christen, H. M.; Ward, T. Z.; Lauter, V.

    2016-01-01

    The realization of a controllable metamagnetic transition from AFM to FM ordering would open the door to a plethora of new spintronics based devices that, rather than reorienting spins in a ferromagnet, harness direct control of a materials intrinsic magnetic ordering. In this study FeRh films with drastically reduced transition temperatures and a large magneto-thermal hysteresis were produced for magnetocaloric and spintronics applications. Remarkably, giant controllable magnetization change...

  1. 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.

  2. Knowledge-Based Aircraft Automation: Managers Guide on the use of Artificial Intelligence for Aircraft Automation and Verification and Validation Approach for a Neural-Based Flight Controller

    Science.gov (United States)

    Broderick, Ron

    1997-01-01

    The ultimate goal of this report was to integrate the powerful tools of artificial intelligence into the traditional process of software development. To maintain the US aerospace competitive advantage, traditional aerospace and software engineers need to more easily incorporate the technology of artificial intelligence into the advanced aerospace systems being designed today. The future goal was to transition artificial intelligence from an emerging technology to a standard technology that is considered early in the life cycle process to develop state-of-the-art aircraft automation systems. This report addressed the future goal in two ways. First, it provided a matrix that identified typical aircraft automation applications conducive to various artificial intelligence methods. The purpose of this matrix was to provide top-level guidance to managers contemplating the possible use of artificial intelligence in the development of aircraft automation. Second, the report provided a methodology to formally evaluate neural networks as part of the traditional process of software development. The matrix was developed by organizing the discipline of artificial intelligence into the following six methods: logical, object representation-based, distributed, uncertainty management, temporal and neurocomputing. Next, a study of existing aircraft automation applications that have been conducive to artificial intelligence implementation resulted in the following five categories: pilot-vehicle interface, system status and diagnosis, situation assessment, automatic flight planning, and aircraft flight control. The resulting matrix provided management guidance to understand artificial intelligence as it applied to aircraft automation. The approach taken to develop a methodology to formally evaluate neural networks as part of the software engineering life cycle was to start with the existing software quality assurance standards and to change these standards to include neural network

  3. 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.

  4. Influence of extremely low energy radiation on artificial tissue: Effects on image quality and superficial dose

    OpenAIRE

    Al-Akhras, M.-Ali H.; Aljarrah, K.; A Al-omari; H M Al-Khateeb; Albiss, B. A.; Azez, K.; Makhadmeh, G.

    2008-01-01

    The design and slicing technique of artificial soft tissue are presented. Artificial soft tissue has optical penetration properties similar to biological tissues. The soft tissues are made of agar dissolved in water as a transparent tissue (control) incorporated with scatter materials such as polystyrene microspheres and absorbers such as artificial dairy substitute, coffee mate (Carnation Co.). The radiation's interaction with 20 and 40 keV X-ray, and visible light (400–800 nm) with differen...

  5. 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.

  6. 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

  7. Verification of the helioseismology travel-time measurement technique and the inversion procedure for sound speed using artificial data

    International Nuclear Information System (INIS)

    We performed three-dimensional numerical simulations of the solar surface acoustic wave field for the quiet Sun and for three models with different localized sound-speed perturbations in the interior with deep, shallow, and two-layer structures. We used the simulated data generated by two solar acoustics codes that employ the same standard solar model as a background model, but utilize different integration techniques and different models of stochastic wave excitation. Acoustic travel times were measured using a time-distance helioseismology technique, and compared with predictions from ray theory frequently used for helioseismic travel-time inversions. It is found that the measured travel-time shifts agree well with the helioseismic theory for sound-speed perturbations, and for the measurement procedure with and without phase-speed filtering of the oscillation signals. This testing verifies the whole measuring-filtering-inversion procedure for static sound-speed anomalies with small amplitude inside the Sun outside regions of strong magnetic field. It is shown that the phase-speed filtering, frequently used to extract specific wave packets and improve the signal-to-noise ratio, does not introduce significant systematic errors. Results of the sound-speed inversion procedure show good agreement with the perturbation models in all cases. Due to its smoothing nature, the inversion procedure may overestimate sound-speed variations in regions with sharp gradients of the sound-speed profile.

  8. Verification of the Travel Time Measurement Technique and the Helioseismic Inversion Procedure for Sound Speed Using Artificial Data

    CERN Document Server

    Parchevsky, Konstantin V; Hartlep, Thomas; Kosovichev, Alexander G

    2012-01-01

    We performed 3D numerical simulations of the solar surface wave field for the quiet Sun and for three models with different localized sound-speed variations in the interior with: (i) deep, (ii) shallow, and (iii) two-layer structures. We used simulated data generated by two different codes which use the same standard solar model as a background model, but utilize two different integration techniques and use different models of stochastic wave excitation. Acoustic travel times were measured from all data sets using the time-distance helioseismology technique and compared with the ray theory predictions, frequently used for helioseismic travel-time inversions. It is found that the measured travel-time shifts agree well with the ray theory in both cases with and without phase-speed filtering for the shallow and deep perturbations. This testing verifies the whole measuring-filtering-inversion procedure for sound-speed anomalies inside the Sun. It is shown, that the phase-speed filtering, frequently used to improv...

  9. 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)

  10. 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.

  11. Towards an Irritable Bowel Syndrome Control System Based on Artificial Neural Networks

    Science.gov (United States)

    Podolski, Ina; Rettberg, Achim

    To solve health problems with medical applications that use complex algorithms is a trend nowadays. It could also be a chance to help patients with critical problems caused from nerve irritations to overcome them and provide a better living situation. In this paper a system for monitoring and controlling the nerves from the intestine is described on a theoretical basis. The presented system could be applied to the irritable bowel syndrome. For control a neural network is used. The advantages for using a neural network for the control of irritable bowel syndrome are the adaptation and learning. These two aspects are important because the syndrome behavior varies from patient to patient and have also concerning the time a lot of variations with respect to each patient. The developed neural network is implemented and can be simulated. Therefore, it can be shown how the network monitor and control the nerves for individual input parameters.

  12. Visual reliance for balance control in older adults persists when visual information is disrupted by artificial feedback delays.

    Directory of Open Access Journals (Sweden)

    Ting Ting Yeh

    Full Text Available Sensory information from our eyes, skin and muscles helps guide and correct balance. Less appreciated, however, is that delays in the transmission of sensory information between our eyes, limbs and central nervous system can exceed several 10s of milliseconds. Investigating how these time-delayed sensory signals influence balance control is central to understanding the postural system. Here, we investigate how delayed visual feedback and cognitive performance influence postural control in healthy young and older adults. The task required that participants position their center of pressure (COP in a fixed target as accurately as possible without visual feedback about their COP location (eyes-open balance, or with artificial time delays imposed on visual COP feedback. On selected trials, the participants also performed a silent arithmetic task (cognitive dual task. We separated COP time series into distinct frequency components using low and high-pass filtering routines. Visual feedback delays affected low frequency postural corrections in young and older adults, with larger increases in postural sway noted for the group of older adults. In comparison, cognitive performance reduced the variability of rapid center of pressure displacements in young adults, but did not alter postural sway in the group of older adults. Our results demonstrate that older adults prioritize vision to control posture. This visual reliance persists even when feedback about the task is delayed by several hundreds of milliseconds.

  13. Artificial Neural Network based control for PV/T panel to track optimum thermal and electrical power

    International Nuclear Information System (INIS)

    Highlights: ► We establish a state model of PV/T panel. ► We study the effect of mass flow rate on PV/T efficiency. ► A real time PV/T control algorithm is proposed. ► A model based optimal thermal and electrical power operation point is tracked. - Abstract: As solar energy is intermittent, many algorithms and electronics have been developed to track the maximum power generation from photovoltaic and thermal panels. Following technological advances, these panels are gathered into one unit: PV/T system. PV/T delivers simultaneously two kinds of power: electrical power and thermal power. Nevertheless, no control systems have been developed in order to track maximum power generation from PV/T system. This paper suggests a PV/T control algorithm based on Artificial Neural Network (ANN) to detect the optimal power operating point (OPOP) by considering PV/T model behavior. The OPOP computes the optimum mass flow rate of PV/T for a considered irradiation and ambient temperature. Simulation results demonstrate great concordance between OPOP model based calculation and ANN outputs.

  14. A novel control strategy to improve the performances of heated wire humidifiers in artificial neonatal ventilation

    International Nuclear Information System (INIS)

    Controlling thermo-hygrometric conditions of gas delivered in neonatal mechanical ventilation shows some unresolved issues due to the design and control strategies implemented in heated wire humidifiers. We perform an in vitro evaluation of humidifier performances, which use a control strategy based on a single-point temperature as feedback, and propose a novel design of the control which consists in pre-warming the gas upwards in the humidification chamber. The ad hoc developed control approach based on a theoretical model is implemented in vitro with and without pre-warming for comparative purposes. Without pre-warming, gas at the chamber outlet needs further post-warming and, depending on the flow rate, the vapour content condensates along the breathing circuit. Whereas, with pre-warming, the proposed control strategy allows us to considerably improve steady-state thermo-hygrometric conditions (T = 37 ± 1 °C, RH = 96% ± 4%) of gas, reaching the Y-piece near to ideal ones in the whole flow rate range, even though a high inlet chamber temperature is required at low flow rate values. The proposed solution, as theoretically predicted, also allows us to limit the vapour condensation along the circuit. (paper)

  15. 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.

  16. 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.

  17. Development of a novel optimization tool for electron linacs inspired by artificial intelligence techniques in video games

    International Nuclear Information System (INIS)

    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.

  18. Cognitive environment simulation: An artificial intelligence system for human performance assessment: Cognitive reliability analysis technique: (Technical report, May 1986-June 1987)

    Energy Technology Data Exchange (ETDEWEB)

    Woods, D.D.; Roth, E.M.

    1987-11-01

    This report documents the results of Phase II of a three phase research program to develop and validate improved methods to model the cognitive behavior of nuclear power plant (NPP) personnel. In Phase II a dynamic simulation capability for modeling how people form intentions to act in NPP emergency situations was developed based on techniques from artificial intelligence. This modeling tool, Cognitive Environment Simulation or CES, simulates the cognitive processes that determine situation assessment and intention formation. It can be used to investigate analytically what situations and factors lead to intention failures, what actions follow from intention failures (e.g., errors of omission, errors of commission, common mode errors), the ability to recover from errors or additional machine failures, and the effects of changes in the NPP person-machine system. The Cognitive Reliability Assessment Technique (or CREATE) was also developed in Phase II to specify how CES can be used to enhance the measurement of the human contribution to risk in probabilistic risk assessment (PRA) studies. 34 refs., 7 figs., 1 tab.

  19. Cognitive environment simulation: An artificial intelligence system for human performance assessment: Cognitive reliability analysis technique: [Technical report, May 1986-June 1987

    International Nuclear Information System (INIS)

    This report documents the results of Phase II of a three phase research program to develop and validate improved methods to model the cognitive behavior of nuclear power plant (NPP) personnel. In Phase II a dynamic simulation capability for modeling how people form intentions to act in NPP emergency situations was developed based on techniques from artificial intelligence. This modeling tool, Cognitive Environment Simulation or CES, simulates the cognitive processes that determine situation assessment and intention formation. It can be used to investigate analytically what situations and factors lead to intention failures, what actions follow from intention failures (e.g., errors of omission, errors of commission, common mode errors), the ability to recover from errors or additional machine failures, and the effects of changes in the NPP person-machine system. The Cognitive Reliability Assessment Technique (or CREATE) was also developed in Phase II to specify how CES can be used to enhance the measurement of the human contribution to risk in probabilistic risk assessment (PRA) studies. 34 refs., 7 figs., 1 tab

  20. 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.

  1. Sustainable practices for fertilizer use through controlled release techniques

    Science.gov (United States)

    Faez, Roselena; Messa, Lucas; Froes, José; Souza, Claudinei

    2015-04-01

    Controlled release fertilizers are efficient tools that increase the sustainability of agricultural practices. However, the biodegradability of the matrices and the determination of the release into soil still require some investigation. This work describes the preparation of potassium-containing microspheres based on chitosan- montmorillonite clay as fertilizer double coated. The release profile in water (ion conductivity measurement) and soil (ion movement performed with time-domain reflectometry (TDR) technique) were evaluated. The potassium-containing microspheres were placed in a 7.5-L container filled with soil (Typic dystrophic LVd). The container was prepared with a water drainage system consisting of a thin layer of gravel at the bottom, which was followed by a geotextile fabric to prevent the loss of soil. The container was filled with soil (9 kg) in layers of 0.05 m to simulate the original bulk density of 1.30 g.cm-3. Each container received 4 g of microspheres placed at a single spot. They were placed at a depth of 10 cm. The fertilizer release was monitored using three electromagnetic probes for TDR that consisted of three continuous metal rods of 20 cm, which were in contact with the material and can be used to estimate the moisture and electrical conductivity. One probe was installed at the center of the container, which meant the rod was in contact with the microspheres in the soil. The other two probes were installed 5 cm from the central probe, and they were only in contact with the soil. Therefore, the purpose of these probes was to monitor the lateral displacement of the fertilizer from the microspheres in the soil. The release in water is fast than in soil, since the total amount of fertilizer in water was delivery during only one week and in soil during 60 days the fertilizer still continue drifting. The composite based on chitosan biopolymer as controlled release material is an efficient method to monitor the fertilizer consumption.

  2. Enhancing spill prevention and response preparedness through quality control techniques

    International Nuclear Information System (INIS)

    The year 1990 saw passage of federal and state oil spill legislation directing the US Environmental Protection Agency and the Florida Department of Environmental Regulation to require on shore bulk petroleum storage facilities to improve their oil spill response and prevention capabilities. The Florida Power ampersand Light Company (FPL), to address concerns arising out of several recent significant spills which had occurred worldwide, and to examine its current situation with regard compliance with the new laws, formed a quality improvement interdepartmental task team in July 1989. Its mission was to reduce the potential for oil spills during waterborne transportation between FPL's fuel oil terminals and its power plants and during transfer and storage of oil at these facilities. Another objective of the team was to enhance the company's spill response preparedness. Using quality control tools and reliability techniques, the team conducted a detailed analysis of seven coastal power plants and five fuel oil terminal facilities. This analysis began with the development of cause-and-effect diagrams designed to identify the root causes of spills so that corrective and preventive actions could be taken. These diagram are constructed by listing possible causes of oil spills under various major categories of possible system breakdown, such as man, method, equipment, and materials. Next, potential root causes are identified and then verified. The team identified the occurrence of surface water oil spill and reduced spill response capability as primary concerns and accordingly constructed cause-and-effect diagrams for both components. Lack of proper procedures, failure of control equipment, and inadequate facility design were identified as potential root causes leading to surface water oil spills. Lack of proper procedures, an inconsistent training program, and response equipment limitations were identified as potential root causes affecting oil spill response capabilities

  3. 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.

  4. Measurement and timing-control techniques of femtosecond electron pulse

    International Nuclear Information System (INIS)

    Updated techniques and results on the measurement and timing-control of femtosecond electron pulses are presented. Radiation emitted by an electron pulse was measured by a femtosecond streak camera, a Michelson interferometer, a 10-channel polychromator and a fluctuation method in order to estimate a longitudinal pulse shape of the electron pulse. Measurements by the streak camera, the interferometer and the polychromator agree with one another within the error of 20%, while that by the fluctuation method was different. The numerical simulation explained the reason for it that the transverse emittance of the electron pulse affects the fluctuation of incoherent Cherenkov radiation. The synchronization of the electron pulse with the femtosecond laser pulse was also carried out. The timing jitter was 330 fs in rms and the hours-long drift was more than 1 ps. The suppression of the drift is under way by introducing a stable water cooler (within 0.01 deg. C) for the accelerator tubes and RF gun, and an air-conditioner (within 2 deg. C)

  5. 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.

  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;

    2016-01-01

    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 di...

  7. 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.

  8. 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.

  9. Analysis of Dual Rotating Rake Data from the NASA Glenn Advanced Noise Control Fan Duct with Artificial Sources

    Science.gov (United States)

    Dahl, Milo D.; Sutliff, Daniel L.

    2014-01-01

    The Rotating Rake mode measurement system was designed to measure acoustic duct modes generated by a fan stage. Initially, the mode amplitudes and phases were quantified from a single rake measurement at one axial location. To directly measure the modes propagating in both directions within a duct, a second rake was mounted to the rotating system with an offset in both the axial and the azimuthal directions. The rotating rake data analysis technique was then extended to include the data measured by the second rake. The analysis resulted in a set of circumferential mode levels at each of the two rake microphone locations. Radial basis functions were then least-squares fit to this data to obtain the radial mode amplitudes for the modes propagating in both directions within the duct. Validation experiments have been conducted using artificial acoustic sources. Results are shown for the measurement of the standing waves in the duct from sound generated by one and two acoustic sources that are separated into the component modes propagating in both directions within the duct. Measured reflection coefficients from the open end of the duct are compared to analytical predictions.

  10. A predictive robust cascade position-torque control strategy for Pneumatic Artificial Muscles

    OpenAIRE

    Chikh, Lotfi; Poignet, Philippe; Pierrot, François; Michelin, Micaël

    2010-01-01

    Is it possible to synthesize an easy-to-implement predictive force controller for electropneumatic cylinders? In this paper, this problem is treated in details. As an electropneumatic cylinder is a highly nonlinear actuator, our strategy is based on the precise nonlinear modeling of the actuator and the application of a feedback linearization strategy. This enables to have an equivalent linearized model and therefore, to find an explicit solution of the predictive optimization problem. The ob...

  11. Artificial control of biocatalytic reaction; Seitai shokubai hanno no jin`iteki seigyo

    Energy Technology Data Exchange (ETDEWEB)

    Nakamura, K. [Kyoto University, Kyoto (Japan). Institute for Chemical Research

    1997-08-25

    Selective composition of optically active compounds by use of biocatalysts is discussed. No search is made for any particular microbes or enzymes, but predetermined ones are used. For an increase in the selective yield of L-type carnitine by reducing 4-chloroacetoacetic acid ester using baker`s yeast, the ester length should be enlarged to that of octyl ester. Just as in this case, steric control by ground substance modification is often effective. Lipase helps on esterification which is contrary to hydrolysis in an organic solvent and, even in the optical division in this process, steric control by ground substance modification (for example by changing the structure of the acyl section) is effective. Immobilization of biocatalysts for use in reaction occasionally exerts some effect on stereoselectivity. Two types of enzymes may be participating in a reaction and inhibiting selectivity, and then a two-layer system of water and organic solvent may be effective in performing steric control over the situation. Another measure is to inhibit the activity of either of the two enzymes by use of a selective inhibitor utilizing enzyme reaction. The kind of solvent is also an influential factor. 11 refs., 7 figs.

  12. 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

  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. Applying artificial intelligence to the control of space telescopes (extended abstract)

    Science.gov (United States)

    Drummond, Mark; Swanson, Keith; Bresina, John; Philips, Andrew; Levinson, Rich

    1992-01-01

    The field of astronomy has recently benefited from the availability of space telescopes. The Hubble Space Telescope (HST), for instance, despite its problems, provides a unique and valuable view of the universe. However, unlike HST, a telescope need not be in low Earth orbit to escape our thickening atmosphere: it is currently technologically feasible to put a telescope on the moon, and there are excellent reasons for doing this. Either in low Earth orbit or on the moon, a space telescope represents an expensive and sought-after resource. Thus, the planning, scheduling, and control of these telescopes is an important problem that must be seriously studied.

  15. 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.

  16. Formulation of a reduced order model of the climatic system by combining classical simulation methods with artificial intelligence techniques

    Science.gov (United States)

    Bounceur, Nabila; Crucifix, Michel

    2010-05-01

    The climate is a multivariable dynamic complex system, governed by equations which are strongly nonlinear. The space-time modes of climatic variability extend on a very broad scale and constitute a major difficulty to represent this variability over long time-scales. It is generally decided to separate the dynamics of the slow components (ice sheets, carbon cycle, deep oceans) which have a time scale of about thousand of years and more, from those of the fast components (atmosphere, mixed layer, earth and ice surface) for which the time scale is for about some years. In this framework, the time-evolution of the slow components depends on the statistics of the fast components, and the latter are controlled by the slow components and the external forcing particularly astronomical ones characterised by the variation of the orbital parameters: Obliquity, precession and eccentricity. The statistics of the fast components of the climate could in principle be estimated with a general circulation model of the atmosphere and ocean. However, the demand on computing resources would be far too excessive. Given the complexity of the climatic system, the great number of dynamic equations which govern it and its degree of nonlinearity we are interested in the statistical reduction rather than an analytical one. The order reduction problem is equivalent to approximator construction. We will focus on neural networks because they constitute very powerful estimators in presence of non-linearity. The training of this network would be done using the output of the climate model of intermediate complexity "LoveClim" developed and available in the Institute of Astronomy and Geophysics G.Lemaître in Belgium as a first step of statistical reduction. The output of the model are first reduced using different methods of reduction order going from linear ones as principal component analysis (PCA) and empirical orthogonal functions (EOF) to non linear ones as Non Linear Principal component

  17. 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.

  18. 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

  19. Characterization of calcareous deposits in artificial seawater by impedance techniques 3--Deposit of CaCO{sub 3} in the presence of Mg(II)

    Energy Technology Data Exchange (ETDEWEB)

    Barchiche, Ch.; Deslouis, C.; Festy, D.; Gil, O.; Refait, Ph.; Touzain, S.; Tribollet, B

    2003-05-30

    Calcareous deposits were formed on steel under cathodic protection conditions in artificial seawater at various potentials from -0.9 to -1.4 V/SCE. The deposition kinetics was analysed by chronoamperometry measurements and the calcareous layers were characterized by electrochemical and electrohydrodynamical impedance spectroscopies, scanning electron microscopy observations and X-ray diffraction analyses. At 20 deg. C, the deposits were composed of aragonite CaCO{sub 3} when formed at potentials E comprised between -0.9 and -1.1 V/SCE, of brucite Mg(OH){sub 2} and aragonite when formed at -1.2 V/SCE, and only of brucite when formed at potentials E{<=}-1.3 V/SCE. However, the in situ impedance techniques demonstrated the presence of a Mg(II)-containing porous layer along with the aragonite deposit at E{>=}-1.1 V/SCE. In seawater enriched with Mg{sup 2+}, the deposition of aragonite was almost totally inhibited, and the behavior of the film containing Mg(II) could be described.

  20. Characterization of calcareous deposits in artificial seawater by impedance techniques 3--Deposit of CaCO3 in the presence of Mg(II)

    International Nuclear Information System (INIS)

    Calcareous deposits were formed on steel under cathodic protection conditions in artificial seawater at various potentials from -0.9 to -1.4 V/SCE. The deposition kinetics was analysed by chronoamperometry measurements and the calcareous layers were characterized by electrochemical and electrohydrodynamical impedance spectroscopies, scanning electron microscopy observations and X-ray diffraction analyses. At 20 deg. C, the deposits were composed of aragonite CaCO3 when formed at potentials E comprised between -0.9 and -1.1 V/SCE, of brucite Mg(OH)2 and aragonite when formed at -1.2 V/SCE, and only of brucite when formed at potentials E≤-1.3 V/SCE. However, the in situ impedance techniques demonstrated the presence of a Mg(II)-containing porous layer along with the aragonite deposit at E≥-1.1 V/SCE. In seawater enriched with Mg2+, the deposition of aragonite was almost totally inhibited, and the behavior of the film containing Mg(II) could be described

  1. A comprehensive overview of hybrid electric vehicle: Powertrain configurations, powertrain control techniques and electronic control units

    International Nuclear Information System (INIS)

    The studies for hybrid electrical vehicle (HEV) have attracted considerable attention because of the necessity of developing alternative methods to generate energy for vehicles due to limited fuel based energy, global warming and exhaust emission limits in the last century. HEV incorporates internal composition engine, electric machines and power electronic equipments. In this study, overview of HEVs with a focus on hybrid configurations, energy management strategies and electronic control units are presented. Advantages and disadvantages of each configuration are clearly emphasized. The existing powertrain control techniques for HEVs are classified and comprehensively described. Electronic control units used in HEV configuration are also elaborated. The latest trends and technological challenges in the near future for HEVs are discussed.

  2. 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.

  3. 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.

  4. 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)

  5. Application of adaptive neuro-fuzzy inference system techniques and artificial neural networks to predict solid oxide fuel cell performance in residential microgeneration installation

    Energy Technology Data Exchange (ETDEWEB)

    Entchev, Evgueniy; Yang, Libing [Integrated Energy Systems Laboratory, CANMET Energy Technology Centre, 1 Haanel Dr., Ottawa, Ontario (Canada)

    2007-06-30

    This study applies adaptive neuro-fuzzy inference system (ANFIS) techniques and artificial neural network (ANN) to predict solid oxide fuel cell (SOFC) performance while supplying both heat and power to a residence. A microgeneration 5 kW{sub el} SOFC system was installed at the Canadian Centre for Housing Technology (CCHT), integrated with existing mechanical systems and connected in parallel to the grid. SOFC performance data were collected during the winter heating season and used for training of both ANN and ANFIS models. The ANN model was built on back propagation algorithm as for ANFIS model a combination of least squares method and back propagation gradient decent method were developed and applied. Both models were trained with experimental data and used to predict selective SOFC performance parameters such as fuel cell stack current, stack voltage, etc. The study revealed that both ANN and ANFIS models' predictions agreed well with variety of experimental data sets representing steady-state, start-up and shut-down operations of the SOFC system. The initial data set was subjected to detailed sensitivity analysis and statistically insignificant parameters were excluded from the training set. As a result, significant reduction of computational time was achieved without affecting models' accuracy. The study showed that adaptive models can be applied with confidence during the design process and for performance optimization of existing and newly developed solid oxide fuel cell systems. It demonstrated that by using ANN and ANFIS techniques SOFC microgeneration system's performance could be modelled with minimum time demand and with a high degree of accuracy. (author)

  6. Control of the energetic proton flux in the inner radiation belt by artificial means

    Science.gov (United States)

    Shao, X.; Papadopoulos, K.; Sharma, A. S.

    2009-07-01

    that such reduction requires injection of less than 10 kW of SAW power. Increasing the power will result in the further decrease of the trapped flux. The paper concludes with a brief discussion of techniques that can inject such waves using ground-based transmitters.

  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. 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.

  9. Effect of Control Techniques on the Performance of Semiactive Dampers

    OpenAIRE

    Masi, John William

    2001-01-01

    A computer simulation is used to examine the effects that various control methods have on the performance of semiactive dampers in controlling the dynamics of a single suspension (quarter car) model. The level of dynamic control of this model has a direct bearing on the ride comfort and vehicle handling, when the single suspension is interpreted as a partial model of a vehicle. The dynamic results obtained when using two alternative semiactive control methods are compared to the results obt...

  10. Speed Control of DC Motor using AC/AC/DC Converter Based on Intelligent Techniques

    OpenAIRE

    Rakan Kh Antar

    2013-01-01

       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 fo...

  11. Predictive Techniques for Spacecraft Cabin Air Quality Control

    Science.gov (United States)

    Perry, J. L.; Cromes, Scott D. (Technical Monitor)

    2001-01-01

    As assembly of the International Space Station (ISS) proceeds, predictive techniques are used to determine the best approach for handling a variety of cabin air quality challenges. These techniques use equipment offgassing data collected from each ISS module before flight to characterize the trace chemical contaminant load. Combined with crew metabolic loads, these data serve as input to a predictive model for assessing the capability of the onboard atmosphere revitalization systems to handle the overall trace contaminant load as station assembly progresses. The techniques for predicting in-flight air quality are summarized along with results from early ISS mission analyses. Results from groundbased analyses of in-flight air quality samples are compared to the predictions to demonstrate the technique's relative conservatism.

  12. Artificial vision in nuclear fuel fabrication

    International Nuclear Information System (INIS)

    The development of artificial vision techniques opens a door to the optimization of industrial processes which the nuclear industry cannot miss out on. Backing these techniques represents a revolution in security and reliability in the manufacturing of a highly technological products as in nuclear fuel. Enusa Industrias Avanzadas S. A. has successfully developed and implemented the first automatic inspection equipment for pellets by artificial vision in the European nuclear industry which is nowadays qualified and is already developing the second generation of this machine. There are many possible applications for the techniques of artificial vision in the fuel manufacturing processes. Among the practices developed by Enusa Industrias Avanzadas are, besides the pellets inspection, the rod sealing drills detection and positioning in the BWR products and the sealing drills inspection in the PWR fuel. The use of artificial vision in the arduous and precise processes of full inspection will allow the absence of human error, the increase of control in the mentioned procedures, the reduction of doses received by the personnel, a higher reliability of the whole of the operations and an improvement in manufacturing costs. (Author)

  13. Herion Servo techniques with electronic control systems in hydraulic systems

    Energy Technology Data Exchange (ETDEWEB)

    Ehrath, M.

    1981-01-01

    A description of an electro-hydraulic control circuit for the fuel pump and the injection valve of a large diesel engine is presented. Pressures of 500-1000 bar must be controlled in diesel engines. The newly-developed electronically controlled injection system uses quick-action control valves, a further developed version of the high-response valves. Electronically controlled ignition systems offer the following advantages: improved fuel-air ratio and better combustion; improved injection parameters within the total load range of the engine, better adaption to changing operational and environmental conditions and to changing fuel quality, fewer and less complicated components, and increased operational safety.

  14. 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

  15. 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

  16. 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. PMID:11763444

  17. Optimal Lyapunov quantum control of two-level systems: Convergence and extended techniques

    Energy Technology Data Exchange (ETDEWEB)

    Wang, L.C., E-mail: wanglc@dlut.edu.cn [School of Physics and Optoelectronic Technology, Dalian University of Technology, Dalian 116024 (China); Hou, S.C. [School of Physics and Optoelectronic Technology, Dalian University of Technology, Dalian 116024 (China); Yi, X.X., E-mail: yixx@dlut.edu.cn [School of Physics and Optoelectronic Technology, Dalian University of Technology, Dalian 116024 (China); Dong, Daoyi; Petersen, Ian R. [School of Engineering and Information Technology, University of New South Wales at the Australian Defence Force Academy, Canberra, ACT 2600 (Australia)

    2014-03-01

    Taking a two-level system as an example, we show that a strong control field may enhance the efficiency of optimal Lyapunov quantum control but could decrease its control fidelity. A relationship between the strength of the control field and the control fidelity is established. An extended technique, which combines free evolution and external control, is proposed to improve the control fidelity. We analytically demonstrate that the extended technique can be used to design a control law for steering a two-level system exactly to one predetermined eigenstate of the free Hamiltonian. In such a way, the convergence of the extended optimal Lyapunov quantum control can be guaranteed.

  18. Optimal Lyapunov quantum control of two-level systems: Convergence and extended techniques

    International Nuclear Information System (INIS)

    Taking a two-level system as an example, we show that a strong control field may enhance the efficiency of optimal Lyapunov quantum control but could decrease its control fidelity. A relationship between the strength of the control field and the control fidelity is established. An extended technique, which combines free evolution and external control, is proposed to improve the control fidelity. We analytically demonstrate that the extended technique can be used to design a control law for steering a two-level system exactly to one predetermined eigenstate of the free Hamiltonian. In such a way, the convergence of the extended optimal Lyapunov quantum control can be guaranteed.

  19. 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.

  20. 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....../kg. Measurement compatibility is obtained by control of traceability to certified reference materials, (C) 1994 Wiley-Liss, Inc....