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Sample records for intelligent control techniques

  1. 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.

  2. 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)

  3. VAR control in distribution systems by using artificial intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Golkar, M.A. [Curtin Univ. of Technology, Sarawak (Malaysia). School of Engineering and Science

    2005-07-01

    This paper reviewed artificial intelligence techniques used in VAR control systems. Reactive power controls in distribution systems were also reviewed. While artificial intelligence methods are widely used in power control systems, the techniques require extensive human knowledge bases and experiences in order to operate correctly. Expert systems use knowledge and interface procedures to solve problems that often require human expertise. Expert systems often cause knowledge bottlenecks as they are unable to learn or adopt to new situations. While neural networks possess learning ability, they are computationally expensive. However, test results in recent neural network studies have demonstrated that they work well in a variety of loading conditions. Fuzzy logic techniques are used to accurately represent the operational constraints of power systems. Fuzzy logic has an advantage over other artificial intelligence techniques as it is able to remedy uncertainties in data. Evolutionary computing algorithms use probabilistic transition rules which can search complicated data to determine optimal constraints and parameters. Over 95 per cent of all papers published on power systems use genetic algorithms. It was concluded that hybrid systems using various artificial intelligence techniques are now being used by researchers. 69 refs.

  4. A new approach to PWR power control using intelligent techniques

    International Nuclear Information System (INIS)

    Boroushaki, M.; Ghofrani, M.B.; Lucas, C.; Yazdanpanah, M.J.; Sadati, N.

    2004-01-01

    Improved load following capability is one of the main technical performances of advanced PWR(APWR). Controlling the nuclear reactor core during load following operation encounters some difficulties. These difficulties mainly arise from nuclear reactor core limitations in local power peaking, while the core is subject to large and sharp variation of local power density during transients. Axial offset (A.O) is the parameter usually used to represent of core power peaking, in form of a practical parameter. This paper, proposes a new intelligent approach to A.o control of PWR nuclear reactors core during load following operation. This method uses a neural network model of the core to predict the dynamic behavior of the core and a fuzzy critic based on the operator knowledge and experience for the purpose of decision-making during load following operations. Simulation results show that this method can use optimum control rod groups maneuver with variable overlapping and may improve the reactor load following capability

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

    International Nuclear Information System (INIS)

    Peng, Y.-F.

    2009-01-01

    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.

  6. Modeling and Control of Multivariable Process Using Intelligent Techniques

    Directory of Open Access Journals (Sweden)

    Subathra Balasubramanian

    2010-10-01

    Full Text Available For nonlinear dynamic systems, the first principles based modeling and control is difficult to implement. In this study, a fuzzy controller and recurrent fuzzy controller are developed for MIMO process. Fuzzy logic controller is a model free controller designed based on the knowledge about the process. In fuzzy controller there are two types of rule-based fuzzy models are available: one the linguistic (Mamdani model and the other is Takagi–Sugeno model. Of these two, Takagi-Sugeno model (TS has attracted most attention. The fuzzy controller application is limited to static processes due to their feedforward structure. But, most of the real-time processes are dynamic and they require the history of input/output data. In order to store the past values a memory unit is needed, which is introduced by the recurrent structure. The proposed recurrent fuzzy structure is used to develop a controller for the two tank heating process. Both controllers are designed and implemented in a real time environment and their performance is compared.

  7. Intelligent control systems 1990

    International Nuclear Information System (INIS)

    Shoureshi, R.

    1991-01-01

    The field of artificial intelligence (Al) has generated many useful ideas and techniques that can be integrated into the design of control systems. It is believed and, for special cases, has been demonstrated, that integration of Al into control systems would provide the necessary tools for solving many of the complex problems that present control techniques and Al algorithms are unable to do, individually. However, this integration requires the development of basic understanding and new fundamentals to provide scientific bases for achievement of its potential. This book presents an overview of some of the latest research studies in the area of intelligent control systems. These papers present techniques for formulation of intelligent control, and development of the rule-based control systems. Papers present applications of control systems in nuclear power plants and HVAC systems

  8. Intelligent Lighting Control System

    OpenAIRE

    García, Elena; Rodríguez González, Sara; de Paz Santana, Juan F.; Bajo Pérez, Javier

    2014-01-01

    This paper presents an adaptive architecture that allows centralized control of public lighting and intelligent management, in order to economise on lighting and maintain maximum comfort status of the illuminated areas. To carry out this management, architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA and a Service Oriented Aproach (SOA). It performs optim...

  9. Intelligent Mission Controller Node

    National Research Council Canada - National Science Library

    Perme, David

    2002-01-01

    The goal of the Intelligent Mission Controller Node (IMCN) project was to improve the process of translating mission taskings between real-world Command, Control, Communications, Computers, and Intelligence (C41...

  10. Artificial Intelligence Techniques and Methodology

    OpenAIRE

    Carbonell, Jaime G.; Sleeman, Derek

    1982-01-01

    Two closely related aspects of artificial intelligence that have received comparatively little attention in the recent literature are research methodology, and the analysis of computational techniques that span multiple application areas. We believe both issues to be increasingly significant as Artificial Intelligence matures into a science and spins off major application efforts. It is imperative to analyze the repertoire of AI methods with respect to past experience, utility in new domains,...

  11. 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

  12. Quality control of intelligence research

    International Nuclear Information System (INIS)

    Lu Yan; Xin Pingping; Wu Jian

    2014-01-01

    Quality control of intelligence research is the core issue of intelligence management, is a problem in study of information science This paper focuses on the performance of intelligence to explain the significance of intelligence research quality control. In summing up the results of the study on the basis of the analysis, discusses quality control methods in intelligence research, introduces the experience of foreign intelligence research quality control, proposes some recommendations to improve quality control in intelligence research. (authors)

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

    Directory of Open Access Journals (Sweden)

    F. Khammar

    2016-01-01

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

  14. Computational Intelligence Techniques for New Product Design

    CERN Document Server

    Chan, Kit Yan; Dillon, Tharam S

    2012-01-01

    Applying computational intelligence for product design is a fast-growing and promising research area in computer sciences and industrial engineering. However, there is currently a lack of books, which discuss this research area. This book discusses a wide range of computational intelligence techniques for implementation on product design. It covers common issues on product design from identification of customer requirements in product design, determination of importance of customer requirements, determination of optimal design attributes, relating design attributes and customer satisfaction, integration of marketing aspects into product design, affective product design, to quality control of new products. Approaches for refinement of computational intelligence are discussed, in order to address different issues on product design. Cases studies of product design in terms of development of real-world new products are included, in order to illustrate the design procedures, as well as the effectiveness of the com...

  15. 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)

  16. Intelligent Flow Control Valve

    Science.gov (United States)

    Kelley, Anthony R (Inventor)

    2015-01-01

    The present invention is an intelligent flow control valve which may be inserted into the flow coming out of a pipe and activated to provide a method to stop, measure, and meter flow coming from the open or possibly broken pipe. The intelligent flow control valve may be used to stop the flow while repairs are made. Once repairs have been made, the valve may be removed or used as a control valve to meter the amount of flow from inside the pipe. With the addition of instrumentation, the valve may also be used as a variable area flow meter and flow controller programmed based upon flowing conditions. With robotic additions, the valve may be configured to crawl into a desired pipe location, anchor itself, and activate flow control or metering remotely.

  17. Discrete PID Tuning Using Artificial Intelligence Techniques

    Directory of Open Access Journals (Sweden)

    Petr DOLEŽEL

    2009-06-01

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

  18. An intelligent CPIB controller

    International Nuclear Information System (INIS)

    Wikne, J.C.

    1987-12-01

    An intelligent GPIB (General Purpose Interface Bus) controller is described. It employs an autonomous slave CPU together with a dedicated controller/talker/listener chip to handle the GPIB bus protocol, thus freeing the host computer from this time-consuming task. Distribution of a large part of the necessary software to the slave side, assures that the system can be implemented on virtually any computer with a minimum of effort

  19. Automatic intelligent cruise control

    OpenAIRE

    Stanton, NA; Young, MS

    2006-01-01

    This paper reports a study on the evaluation of automatic intelligent cruise control (AICC) from a psychological perspective. It was anticipated that AICC would have an effect upon the psychology of driving—namely, make the driver feel like they have less control, reduce the level of trust in the vehicle, make drivers less situationally aware, but might reduce the workload and make driving might less stressful. Drivers were asked to drive in a driving simulator under manual and automatic inte...

  20. Computational intelligence techniques in health care

    CERN Document Server

    Zhou, Wengang; Satheesh, P

    2016-01-01

    This book presents research on emerging computational intelligence techniques and tools, with a particular focus on new trends and applications in health care. Healthcare is a multi-faceted domain, which incorporates advanced decision-making, remote monitoring, healthcare logistics, operational excellence and modern information systems. In recent years, the use of computational intelligence methods to address the scale and the complexity of the problems in healthcare has been investigated. This book discusses various computational intelligence methods that are implemented in applications in different areas of healthcare. It includes contributions by practitioners, technology developers and solution providers.

  1. Artificial Intelligence Techniques: Applications for Courseware Development.

    Science.gov (United States)

    Dear, Brian L.

    1986-01-01

    Introduces some general concepts and techniques of artificial intelligence (natural language interfaces, expert systems, knowledge bases and knowledge representation, heuristics, user-interface metaphors, and object-based environments) and investigates ways these techniques might be applied to analysis, design, development, implementation, and…

  2. Event tree analysis using artificial intelligence techniques

    International Nuclear Information System (INIS)

    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

  3. Soft computing in intelligent control

    CERN Document Server

    Jung, Jin-Woo; Kubota, Naoyuki

    2014-01-01

    Nowadays, people have tendency to be fond of smarter machines that are able to collect data, make learning, recognize things, infer meanings, communicate with human and perform behaviors. Thus, we have built advanced intelligent control affecting all around societies; automotive, rail, aerospace, defense, energy, healthcare, telecoms and consumer electronics, finance, urbanization. Consequently, users and consumers can take new experiences through the intelligent control systems. We can reshape the technology world and provide new opportunities for industry and business, by offering cost-effective, sustainable and innovative business models. We will have to know how to create our own digital life. The intelligent control systems enable people to make complex applications, to implement system integration and to meet society’s demand for safety and security. This book aims at presenting the research results and solutions of applications in relevance with intelligent control systems. We propose to researchers ...

  4. Expectation-based intelligent control

    International Nuclear Information System (INIS)

    Zak, Michail

    2006-01-01

    New dynamics paradigms-negative diffusion and terminal attractors-are introduced to control noise and chaos. The applied control forces are composed of expectations governed by the associated Fokker-Planck and Liouville equations. The approach is expanded to a general concept of intelligent control via expectations. Relevance to control in livings is emphasized and illustrated by neural nets with mirror neurons

  5. New approaches in intelligent image analysis techniques, methodologies and applications

    CERN Document Server

    Nakamatsu, Kazumi

    2016-01-01

    This book presents an Introduction and 11 independent chapters, which are devoted to various new approaches of intelligent image processing and analysis. The book also presents new methods, algorithms and applied systems for intelligent image processing, on the following basic topics: Methods for Hierarchical Image Decomposition; Intelligent Digital Signal Processing and Feature Extraction; Data Clustering and Visualization via Echo State Networks; Clustering of Natural Images in Automatic Image Annotation Systems; Control System for Remote Sensing Image Processing; Tissue Segmentation of MR Brain Images Sequence; Kidney Cysts Segmentation in CT Images; Audio Visual Attention Models in Mobile Robots Navigation; Local Adaptive Image Processing; Learning Techniques for Intelligent Access Control; Resolution Improvement in Acoustic Maps. Each chapter is self-contained with its own references. Some of the chapters are devoted to the theoretical aspects while the others are presenting the practical aspects and the...

  6. Operator support system using computational intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Bueno, Elaine Inacio, E-mail: ebueno@ifsp.edu.br [Instituto Federal de Educacao, Ciencia e Tecnologia de Sao Paulo (IFSP), Sao Paulo, SP (Brazil); Pereira, Iraci Martinez, E-mail: martinez@ipen.br [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2015-07-01

    Computational Intelligence Systems have been widely applied in Monitoring and Fault Detection Systems in several processes and in different kinds of applications. These systems use interdependent components ordered in modules. It is a typical behavior of such systems to ensure early detection and diagnosis of faults. Monitoring and Fault Detection Techniques can be divided into two categories: estimative and pattern recognition methods. The estimative methods use a mathematical model, which describes the process behavior. The pattern recognition methods use a database to describe the process. In this work, an operator support system using Computational Intelligence Techniques was developed. This system will show the information obtained by different CI techniques in order to help operators to take decision in real time and guide them in the fault diagnosis before the normal alarm limits are reached. (author)

  7. Operator support system using computational intelligence techniques

    International Nuclear Information System (INIS)

    Bueno, Elaine Inacio; Pereira, Iraci Martinez

    2015-01-01

    Computational Intelligence Systems have been widely applied in Monitoring and Fault Detection Systems in several processes and in different kinds of applications. These systems use interdependent components ordered in modules. It is a typical behavior of such systems to ensure early detection and diagnosis of faults. Monitoring and Fault Detection Techniques can be divided into two categories: estimative and pattern recognition methods. The estimative methods use a mathematical model, which describes the process behavior. The pattern recognition methods use a database to describe the process. In this work, an operator support system using Computational Intelligence Techniques was developed. This system will show the information obtained by different CI techniques in order to help operators to take decision in real time and guide them in the fault diagnosis before the normal alarm limits are reached. (author)

  8. Artificial Intelligence techniques for big data analysis

    OpenAIRE

    Aditya Khatri

    2017-01-01

    During my stay in Salamanca (Spain), I was fortunate enough to participate in the BISITE Research Group of the University of Salamanca. The University of Salamanca is the oldest university in Spain and in 2018 it celebrates its 8th centenary. As a computer science researcher, I participated in one of the many international projects that the research group has active, especially in big data analysis using Artificial Intelligence (AI) techniques. AI is one of BISITE's main lines of rese...

  9. Autonomous intelligent cruise control system

    Science.gov (United States)

    Baret, Marc; Bomer, Thierry T.; Calesse, C.; Dudych, L.; L'Hoist, P.

    1995-01-01

    Autonomous intelligent cruise control (AICC) systems are not only controlling vehicles' speed but acting on the throttle and eventually on the brakes they could automatically maintain the relative speed and distance between two vehicles in the same lane. And more than just for comfort it appears that these new systems should improve the safety on highways. By applying a technique issued from the space research carried out by MATRA, a sensor based on a charge coupled device (CCD) was designed to acquire the reflected light on standard-mounted car reflectors of pulsed laser diodes emission. The CCD is working in a unique mode called flash during transfer (FDT) which allows identification of target patterns in severe optical environments. It provides high accuracy for distance and angular position of targets. The absence of moving mechanical parts ensures high reliability for this sensor. The large field of view and the high measurement rate give a global situation assessment and a short reaction time. Then, tracking and filtering algorithms have been developed in order to select the target, on which the equipped vehicle determines its safety distance and speed, taking into account its maneuvering and the behaviors of other vehicles.

  10. 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.

  11. Intelligent power supply controller

    International Nuclear Information System (INIS)

    Rumrill, R.S.; Reinagel, D.J.

    1991-01-01

    The authors have developed a new power supply controller which would combine 20-bit precision, simple interfacing, and versatile software control. It performs many tasks internal to the power supply and also communicates with an external host computer. Parameters can be entered and/or read over a serial link using one of the 82 command words. In addition, an optional remote control panel can be located up to thousands of feet away. This new controller will reduce the software development time normally spent by the user, while increasing the reliability of the system. The cost is less than buying the equivalent separate CAMAC system. Nonvolatile memory remembers all configuration data; one generic controller can thus be programmed to use anywhere from the smallest power supply to the largest. The controllers will be used at the Clinton P. Anderson Meson Facility at Los Alamos

  12. Intelligent networked teleoperation control

    CERN Document Server

    Li, Zhijun; Su, Chun-Yi

    2015-01-01

    This book describes a unified framework for networked teleoperation systems involving multiple research fields: networked control systems for linear and nonlinear forms, bilateral teleoperation, trilateral teleoperation, multilateral teleoperation and cooperative teleoperation. It closely examines networked control as a field at the intersection of systems & control and robotics and presents a number of experimental case studies on testbeds for robotic systems, including networked haptic devices, robotic network systems and sensor network systems. The concepts and results outlined are easy to understand, even for readers fairly new to the subject. As such, the book offers a valuable reference work for researchers and engineers in the fields of systems & control and robotics.

  13. USE OF ARTIFICIAL INTELLIGENCE TECHNIQUES IN QUALITY IMPROVING PROCESS

    OpenAIRE

    KALİTE İYİLEŞTİRME SÜRECİNDE YAPAY ZEKÃ KAYA; Orhan ENGİN

    2005-01-01

    Today, changing of competition conditions and customer preferences caused to happen many differences in the viewpoint of firms' quality studies. At the same time, improvements in computer technologies accelerated use of artificial intelligence. Artificial intelligence technologies are being used to solve many industry problems. In this paper, we investigated the use of artificial intelligence techniques to solve quality problems. The artificial intelligence techniques, which are used in quali...

  14. 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.

  15. An intelligent control strategy based on ANFIS techniques in order to improve the performance of a low-cost unmanned aerial vehicle vision system

    OpenAIRE

    Marichal, G. N.; Hernández, A.; Olivares Méndez, Miguel Ángel; Acosta, L.; Campoy Cervera, Pascual

    2010-01-01

    In this paper, an intelligent control approach based on Neuro-Fuzzy systems is presented. A model of a low-cost vision platform for an unmanned aerial system is taken in the study. A simulation platform including this low-cost vision system and the influence of the helicopter vibrations over this system is shown. The intelligent control approach has been inserted in this simulation platform. Several trials taking these Neuro-Fuzzy systems as a fundamental part of the control strategy have bee...

  16. Robot Advanced Intelligent Control developed through Versatile ...

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... environments of human life exposed to great dangers such as support and repair in .... intelligent control interfaces, network quality of service, shared resources and ..... Artificial Intelligence series, volume 6556, p. 336-349 ...

  17. Artificial intelligence approach to accelerator control systems

    International Nuclear Information System (INIS)

    Schultz, D.E.; Hurd, J.W.; Brown, S.K.

    1987-01-01

    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

  18. Improving Energy Saving Techniques by Ambient Intelligence Scheduling

    DEFF Research Database (Denmark)

    Cristani, Matteo; Karafili, Erisa; Tomazzoli, Claudio

    2015-01-01

    Energy saving is one of the most challenging aspects of modern ambient intelligence technologies, for both domestic and business usages. In this paper we show how to combine Ambient Intelligence and Artificial Intelligence techniques to solve the problem of scheduling a set of devices under a given...... for Ambient Intelligence to a specific framework and exhibit a sample usage for a real life system, Elettra, that is in use in an industrial context....

  19. Combined Intelligent Control (CIC an Intelligent Decision Making Algorithm

    Directory of Open Access Journals (Sweden)

    Moteaal Asadi Shirzi

    2007-03-01

    Full Text Available The focus of this research is to introduce the concept of combined intelligent control (CIC as an effective architecture for decision-making and control of intelligent agents and multi-robot sets. Basically, the CIC is a combination of various architectures and methods from fields such as artificial intelligence, Distributed Artificial Intelligence (DAI, control and biological computing. Although any intelligent architecture may be very effective for some specific applications, it could be less for others. Therefore, CIC combines and arranges them in a way that the strengths of any approach cover the weaknesses of others. In this paper first, we introduce some intelligent architectures from a new aspect. Afterward, we offer the CIC by combining them. CIC has been executed in a multi-agent set. In this set, robots must cooperate to perform some various tasks in a complex and nondeterministic environment with a low sensory feedback and relationship. In order to investigate, improve, and correct the combined intelligent control method, simulation software has been designed which will be presented and considered. To show the ability of the CIC algorithm as a distributed architecture, a central algorithm is designed and compared with the CIC.

  20. Business Intelligence in Process Control

    Science.gov (United States)

    Kopčeková, Alena; Kopček, Michal; Tanuška, Pavol

    2013-12-01

    The Business Intelligence technology, which represents a strong tool not only for decision making support, but also has a big potential in other fields of application, is discussed in this paper. Necessary fundamental definitions are offered and explained to better understand the basic principles and the role of this technology for company management. Article is logically divided into five main parts. In the first part, there is the definition of the technology and the list of main advantages. In the second part, an overview of the system architecture with the brief description of separate building blocks is presented. Also, the hierarchical nature of the system architecture is shown. The technology life cycle consisting of four steps, which are mutually interconnected into a ring, is described in the third part. In the fourth part, analytical methods incorporated in the online analytical processing and data mining used within the business intelligence as well as the related data mining methodologies are summarised. Also, some typical applications of the above-mentioned particular methods are introduced. In the final part, a proposal of the knowledge discovery system for hierarchical process control is outlined. The focus of this paper is to provide a comprehensive view and to familiarize the reader with the Business Intelligence technology and its utilisation.

  1. Artificial Intelligence based technique for BTS placement

    Science.gov (United States)

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

    2013-12-01

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

  2. Artificial Intelligence based technique for BTS placement

    International Nuclear Information System (INIS)

    Alenoghena, C O; Emagbetere, J O; 1 Minna (Nigeria))" data-affiliation=" (Department of Telecommunications Engineering, Federal University of Techn.1 Minna (Nigeria))" >Aibinu, A M

    2013-01-01

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

  3. Memory Based Machine Intelligence Techniques in VLSI hardware

    OpenAIRE

    James, Alex Pappachen

    2012-01-01

    We briefly introduce the memory based approaches to emulate machine intelligence in VLSI hardware, describing the challenges and advantages. Implementation of artificial intelligence techniques in VLSI hardware is a practical and difficult problem. Deep architectures, hierarchical temporal memories and memory networks are some of the contemporary approaches in this area of research. The techniques attempt to emulate low level intelligence tasks and aim at providing scalable solutions to high ...

  4. THE COMPUTATIONAL INTELLIGENCE TECHNIQUES FOR PREDICTIONS - ARTIFICIAL NEURAL NETWORKS

    OpenAIRE

    Mary Violeta Bar

    2014-01-01

    The computational intelligence techniques are used in problems which can not be solved by traditional techniques when there is insufficient data to develop a model problem or when they have errors.Computational intelligence, as he called Bezdek (Bezdek, 1992) aims at modeling of biological intelligence. Artificial Neural Networks( ANNs) have been applied to an increasing number of real world problems of considerable complexity. Their most important advantage is solving problems that are too c...

  5. 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.

  6. Intelligent Flight Control Simulation Research Program

    National Research Council Canada - National Science Library

    Stolarik, Brian

    2007-01-01

    ...). Under the program, entitled "Intelligent Flight Control Simulation Research Laboratory," a variety of technologies were investigated or developed during the course of the research for AFRL/VAC...

  7. When intelligence is in control

    Energy Technology Data Exchange (ETDEWEB)

    Bellman, K.L.

    1996-12-31

    Each time a discipline redefines itself, I look at it as a sign of growth, because often such redefinition means that there is new theory, new methods, or new {open_quotes}disciples{close_quote} from other disciplines who are stretching, enlarging, and deepening the field. Such is the case with semiotics. Deeply entwined with the concepts of {open_quotes}intelligent systems{close_quotes}, {open_quotes}intelligent control{close_quotes}, and complex systems theory, semiotics struggles to develop representations, notations (systems of representations), and models (functionally-oriented sets of related representations) to study systems that may or may not be usefully described as employing representations, notations, and models themselves. That last, of course, is the main problem that semiotics faces. Semiotics, like psychology, philosophy, or any other self-referential discipline, is burdened by the eye attempting to study the eye or the mind studying the mind, or more to the point here, the modeler studying the modeling acts of others.

  8. Application of computational intelligence techniques for load shedding in power systems: A review

    International Nuclear Information System (INIS)

    Laghari, J.A.; Mokhlis, H.; Bakar, A.H.A.; Mohamad, Hasmaini

    2013-01-01

    Highlights: • The power system blackout history of last two decades is presented. • Conventional load shedding techniques, their types and limitations are presented. • Applications of intelligent techniques in load shedding are presented. • Intelligent techniques include ANN, fuzzy logic, ANFIS, genetic algorithm and PSO. • The discussion and comparison between these techniques are provided. - Abstract: Recent blackouts around the world question the reliability of conventional and adaptive load shedding techniques in avoiding such power outages. To address this issue, reliable techniques are required to provide fast and accurate load shedding to prevent collapse in the power system. Computational intelligence techniques, due to their robustness and flexibility in dealing with complex non-linear systems, could be an option in addressing this problem. Computational intelligence includes techniques like artificial neural networks, genetic algorithms, fuzzy logic control, adaptive neuro-fuzzy inference system, and particle swarm optimization. Research in these techniques is being undertaken in order to discover means for more efficient and reliable load shedding. This paper provides an overview of these techniques as applied to load shedding in a power system. This paper also compares the advantages of computational intelligence techniques over conventional load shedding techniques. Finally, this paper discusses the limitation of computational intelligence techniques, which restricts their usage in load shedding in real time

  9. Artificial Intelligence techniques for mission planning for mobile robots

    International Nuclear Information System (INIS)

    Martinez, J.M.; Nomine, J.P.

    1990-01-01

    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)

  10. 1st International Conference on Intelligent Communication, Control and Devices

    CERN Document Server

    Choudhury, Sushabhan

    2017-01-01

    The book presents high-quality research papers presented at the first international conference, ICICCD 2016, organised by the Department of Electronics, Instrumentation and Control Engineering of University of Petroleum and Energy Studies, Dehradun on 2nd and 3rd April, 2016. The book is broadly divided into three sections: Intelligent Communication, Intelligent Control and Intelligent Devices. The areas covered under these sections are wireless communication and radio technologies, optical communication, communication hardware evolution, machine-to-machine communication networks, routing techniques, network analytics, network applications and services, satellite and space communications, technologies for e-communication, wireless Ad-Hoc and sensor networks, communications and information security, signal processing for communications, communication software, microwave informatics, robotics and automation, optimization techniques and algorithms, intelligent transport, mechatronics system, guidance and navigat...

  11. Intelligent techniques in engineering management theory and applications

    CERN Document Server

    Onar, Sezi

    2015-01-01

    This book presents recently developed intelligent techniques with applications and theory in the area of engineering management. The involved applications of intelligent techniques such as neural networks, fuzzy sets, Tabu search, genetic algorithms, etc. will be useful for engineering managers, postgraduate students, researchers, and lecturers. The book has been written considering the contents of a classical engineering management book but intelligent techniques are used for handling the engineering management problem areas. This comprehensive characteristics of the book makes it an excellent reference for the solution of complex problems of engineering management. The authors of the chapters are well-known researchers with their previous works in the area of engineering management.

  12. Techniques for Intelligence Analysis of Networks

    National Research Council Canada - National Science Library

    Cares, Jeffrey R

    2005-01-01

    ...) there are significant intelligence analysis manifestations of these properties; and (4) a more satisfying theory of Networked Competition than currently exists for NCW/NCO is emerging from this research...

  13. Intelligent control and automation technology for nuclear applications

    International Nuclear Information System (INIS)

    Kim, Jae Hee; Kim, Ko Ryeo; Lee, Jae Cheol; Eom, Heung Seop; Lee, Jang Soo

    1994-01-01

    Using recently established intelligent mobile robot theory and high technologies in computer science, we have designed an inspection automation system for welded parts of the reactor vessel, and we intend to establish basic technologies. The recent status of those technologies is surveyed for various application areas, and the characteristics and availability of those techniques such as intelligent mobile robot, digital computer control, intelligent user interface, realtime data processing, ultrasonic signal processing, intelligent user interface, intelligent defect recognition, are studied and examined at first. The high performance and compact size inspection system is designed, and if implemented, it is expected to be very efficient in economic point of view. In addition, the use of integrated SW system leads to the reduction of human errors. Through the analysis results and experiences, we investigated the further feasibility of basic technology applications to the various similar operation systems in NPP. (Author)

  14. Intelligent system for lighting control in smart cities

    OpenAIRE

    de Paz Santana, Juan F.; Bajo Pérez, Javier; Rodríguez González, Sara; Villarrubia González, Gabriel; Corchado Rodríguez, Juan M.

    2017-01-01

    This paper presents an adaptive architecture that centralizes the control of public lighting and intelligent management to economize lighting and maintain maximum visual comfort in illuminated areas. To carry out this management, the architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA, and a Service Oriented Approach (SOA). It achieves optimization in ter...

  15. Automation of neutral beam source conditioning with artificial intelligence techniques

    International Nuclear Information System (INIS)

    Johnson, R.R.; Canales, T.W.; Lager, D.L.

    1985-01-01

    This paper describes a system that automates neutral beam source conditioning. The system achieves this with artificial intelligence techniques. The architecture of the system is presented followed by a description of its performance

  16. Intelligent transportation systems data compression using wavelet decomposition technique.

    Science.gov (United States)

    2009-12-01

    Intelligent Transportation Systems (ITS) generates massive amounts of traffic data, which posts : challenges for data storage, transmission and retrieval. Data compression and reconstruction technique plays an : important role in ITS data procession....

  17. Automation of neutral beam source conditioning with artificial intelligence techniques

    International Nuclear Information System (INIS)

    Johnson, R.R.; Canales, T.; Lager, D.

    1986-01-01

    This paper describes a system that automates neutral beam source conditioning. The system achieves this with artificial intelligence techniques. The architecture of the system is presented followed by a description of its performance

  18. Advances in chaos theory and intelligent control

    CERN Document Server

    Vaidyanathan, Sundarapandian

    2016-01-01

    The book reports on the latest advances in and applications of chaos theory and intelligent control. Written by eminent scientists and active researchers and using a clear, matter-of-fact style, it covers advanced theories, methods, and applications in a variety of research areas, and explains key concepts in modeling, analysis, and control of chaotic and hyperchaotic systems. Topics include fractional chaotic systems, chaos control, chaos synchronization, memristors, jerk circuits, chaotic systems with hidden attractors, mechanical and biological chaos, and circuit realization of chaotic systems. The book further covers fuzzy logic controllers, evolutionary algorithms, swarm intelligence, and petri nets among other topics. Not only does it provide the readers with chaos fundamentals and intelligent control-based algorithms; it also discusses key applications of chaos as well as multidisciplinary solutions developed via intelligent control. The book is a timely and comprehensive reference guide for graduate s...

  19. Artificial intelligence in robot control systems

    Science.gov (United States)

    Korikov, A.

    2018-05-01

    This paper analyzes modern concepts of artificial intelligence and known definitions of the term "level of intelligence". In robotics artificial intelligence system is defined as a system that works intelligently and optimally. The author proposes to use optimization methods for the design of intelligent robot control systems. The article provides the formalization of problems of robotic control system design, as a class of extremum problems with constraints. Solving these problems is rather complicated due to the high dimensionality, polymodality and a priori uncertainty. Decomposition of the extremum problems according to the method, suggested by the author, allows reducing them into a sequence of simpler problems, that can be successfully solved by modern computing technology. Several possible approaches to solving such problems are considered in the article.

  20. Instrumentation, Control, and Intelligent Systems

    Energy Technology Data Exchange (ETDEWEB)

    2005-09-01

    Abundant and affordable energy is required for U.S. economic stability and national security. Advanced nuclear power plants offer the best near-term potential to generate abundant, affordable, and sustainable electricity and hydrogen without appreciable generation of greenhouse gases. To that end, Idaho National Laboratory (INL) has been charged with leading the revitalization of nuclear power in the U.S. The INL vision is to become the preeminent nuclear energy laboratory with synergistic, world-class, multi-program capabilities and partnerships by 2015. The vision focuses on four essential destinations: (1) Be the preeminent internationally-recognized nuclear energy research, development, and demonstration laboratory; (2) Be a major center for national security technology development and demonstration; (3) Be a multi-program national laboratory with world-class capabilities; (4) Foster academic, industry, government, and international collaborations to produce the needed investment, programs, and expertise. Crucial to that effort is the inclusion of research in advanced instrumentation, control, and intelligent systems (ICIS) for use in current and advanced power and energy security systems to enable increased performance, reliability, security, and safety. For nuclear energy plants, ICIS will extend the lifetime of power plant systems, increase performance and power output, and ensure reliable operation within the system's safety margin; for national security applications, ICIS will enable increased protection of our nation's critical infrastructure. In general, ICIS will cost-effectively increase performance for all energy security systems.

  1. Instrumentation, Control, and Intelligent Systems

    International Nuclear Information System (INIS)

    Not Available

    2005-01-01

    Abundant and affordable energy is required for U.S. economic stability and national security. Advanced nuclear power plants offer the best near-term potential to generate abundant, affordable, and sustainable electricity and hydrogen without appreciable generation of greenhouse gases. To that end, Idaho National Laboratory (INL) has been charged with leading the revitalization of nuclear power in the U.S. The INL vision is to become the preeminent nuclear energy laboratory with synergistic, world-class, multi-program capabilities and partnerships by 2015. The vision focuses on four essential destinations: (1) Be the preeminent internationally-recognized nuclear energy research, development, and demonstration laboratory; (2) Be a major center for national security technology development and demonstration; (3) Be a multi-program national laboratory with world-class capabilities; (4) Foster academic, industry, government, and international collaborations to produce the needed investment, programs, and expertise. Crucial to that effort is the inclusion of research in advanced instrumentation, control, and intelligent systems (ICIS) for use in current and advanced power and energy security systems to enable increased performance, reliability, security, and safety. For nuclear energy plants, ICIS will extend the lifetime of power plant systems, increase performance and power output, and ensure reliable operation within the system's safety margin; for national security applications, ICIS will enable increased protection of our nation's critical infrastructure. In general, ICIS will cost-effectively increase performance for all energy security systems

  2. Intelligent bioinformatics : the application of artificial intelligence techniques to bioinformatics problems

    National Research Council Canada - National Science Library

    Keedwell, Edward

    2005-01-01

    ... Intelligence and Computer Science 3.1 Introduction to search 3.2 Search algorithms 3.3 Heuristic search methods 3.4 Optimal search strategies 3.5 Problems with search techniques 3.6 Complexity of...

  3. The implementation of intelligent home controller

    Science.gov (United States)

    Li, Biqing; Li, Zhao

    2018-04-01

    This paper mainly talks about the working way of smart home terminal controller and the design of hardware and software. Controlling the lights and by simulating the lamp and the test of the curtain, destroy the light of lamp ON-OFF and the curtain's UP-DOWN by simulating the lamp and the test of the cuetain. Through the sensor collects the ambient information and sends to the network, such as light, temperature and humidity. Besides, it can realise the control of intelligent home control by PCS. Terminal controller of intelligent home which is based on ZiBee technology has into the intelligent home system, it provides people with convenient, safe and intelligent household experience.

  4. Intelligent control of HVAC systems. Part I: Modeling and synthesis

    Directory of Open Access Journals (Sweden)

    Adrian TOADER

    2013-03-01

    Full Text Available This is the first part of a work on intelligent type control of Heating, Ventilating and Air-Conditioning (HVAC systems. The study is performed from the perspective of giving a unitary control method to ensure high energy efficiency and air quality improving. To illustrate the proposed HVAC control technique, in this first part it is considered as benchmark problem a single thermal space HVAC system. The construction of the mathematical model is performed only with a view to obtain a framework of HVAC intelligent control validation by numerical simulations. The latter will be reported in a second part of the study.

  5. Intelligent techniques in signal processing for multimedia security

    CERN Document Server

    Santhi, V

    2017-01-01

    This book proposes new algorithms to ensure secured communications and prevent unauthorized data exchange in secured multimedia systems. Focusing on numerous applications’ algorithms and scenarios, it offers an in-depth analysis of data hiding technologies including watermarking, cryptography, encryption, copy control, and authentication. The authors present a framework for visual data hiding technologies that resolves emerging problems of modern multimedia applications in several contexts including the medical, healthcare, education, and wireless communication networking domains. Further, it introduces several intelligent security techniques with real-time implementation. As part of its comprehensive coverage, the book discusses contemporary multimedia authentication and fingerprinting techniques, while also proposing personal authentication/recognition systems based on hand images, surveillance system security using gait recognition, face recognition under restricted constraints such as dry/wet face condi...

  6. Maximizing Function through Intelligent Robot Actuator Control

    Data.gov (United States)

    National Aeronautics and Space Administration — Maximizing Function through Intelligent Robot Actuator Control Successful missions to Mars and beyond will only be possible with the support of high-performance...

  7. Intelligent Electronic Speed Controller, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — This project intends to design and develop an Intelligent Electronic Speed Controller (IESC) for use on Unmanned Aerial Vehicles (UAVs). The IESC will advance the...

  8. Intelligent control systems: an introduction with examples

    National Research Council Canada - National Science Library

    Hangos, K. M; Lakner, Rozália; Gerzson, Miklós

    2001-01-01

    ... The structure of the knowledge base 1.2 The reasoning algorithm 1.3 Conflict resolution 31 31 32 33 36 viiviii INTELLIGENT CONTROL SYSTEMS 2. 3. 4. 5. 1.4 Explanation of the reasoning Forward r...

  9. Intelligent control and automation technology for nuclear applications

    International Nuclear Information System (INIS)

    Kim, Jae Hui; Huh, Young Hwan; Lee, Jang Soo; Kim, Ko Ryeo; Cha, Kyoung Ho; Lee, Jae Cheol; Dong, In Sook

    1993-01-01

    This project intends to establish the basic technology of intelligent control and automation to be applied to the next generation nuclear plant. For that, the research status of those technologies is surveyed for various application areas at first. The characteristics and availability of those techniques such as neural network, fuzzy rule based control and reasoning, multimedia, real-time software and qualitative modelling are studied through a series of simulations and experiments. By integrating each technologies studied above, we developed a hierarchical, intelligent control system for an autonomous mobile robot as a test bed. The system is composed of several modules of software and hardware subsystems, which are implemented by use of the intelligent techniques. Through the analysis of the results and experiences, we investigated the feasibility of application of the basic technology to the next generation plant. (Author)

  10. 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.

  11. 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.

  12. 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.

  13. Operation optimization of distributed generation using artificial intelligent techniques

    Directory of Open Access Journals (Sweden)

    Mahmoud H. Elkazaz

    2016-06-01

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

  14. Intelligent Traffic Light Based on PLC Control

    Science.gov (United States)

    Mei, Lin; Zhang, Lijian; Wang, Lingling

    2017-11-01

    The traditional traffic light system with a fixed control mode and single control function is contradicted with the current traffic section. The traditional one has been unable to meet the functional requirements of the existing flexible traffic control system. This paper research and develop an intelligent traffic light called PLC control system. It uses PLC as control core, using a sensor module for receiving real-time information of vehicles, traffic control mode for information to select the traffic lights. Of which control mode is flexible and changeable, and it also set the countdown reminder to improve the effectiveness of traffic lights, which can realize the goal of intelligent traffic diversion, intelligent traffic diversion.

  15. 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....

  16. Multimedia techniques for device and ambient intelligence: A continuing endeavor

    NARCIS (Netherlands)

    van den Broek, Egon

    2011-01-01

    The edited volume "Multimedia techniques for device and ambient intelligence" consists of two parts: i) an introduction to a variety of basic low level image processing techniques, leaving aside other modalities, and ii) work on high level, knowledge based processing, including interesting chapters

  17. Application of artificial intelligence in process control

    CERN Document Server

    Krijgsman, A

    1993-01-01

    This book is the result of a united effort of six European universities to create an overall course on the appplication of artificial intelligence (AI) in process control. The book includes an introduction to key areas including; knowledge representation, expert, logic, fuzzy logic, neural network, and object oriented-based approaches in AI. Part two covers the application to control engineering, part three: Real-Time Issues, part four: CAD Systems and Expert Systems, part five: Intelligent Control and part six: Supervisory Control, Monitoring and Optimization.

  18. F-15 IFCS: Intelligent Flight Control System

    Science.gov (United States)

    Bosworth, John

    2007-01-01

    This viewgraph presentation describes the F-15 Intelligent Flight Control System (IFCS). The goals of this project include: 1) Demonstrate revolutionary control approaches that can efficiently optimize aircraft performance in both normal and failure conditions; and 2) Demonstrate advance neural network-based flight control technology for new aerospace systems designs.

  19. Artificial intelligence techniques for sizing photovoltaic systems. A review

    Energy Technology Data Exchange (ETDEWEB)

    Mellit, A. [Department of Electronics, Faculty of Science Engineering, LAMEL Laboratory, Jijel University, P.O. Box 98, Oulad Aissa, Jijel 18000 (Algeria); Kalogirou, S.A. [Department of Mechanical Engineering and Materials Science and Engineering, Cyprus University of Technology, P.O. Box 50329, Limassol 3603 (Cyprus); Hontoria, L. [Grupo Investigacion y Desarrollo en Energia Solar y Automatica, Dpto. de Electronica, E.P.S. Jaen, Universidad de Jaen, Avda., Madrid, 35, 23071 Jaen (Spain); Shaari, S. [Faculty of Applied Sciences, Universiti Teknologi MARA 40450 Shah Alam, Selangor (Malaysia)

    2009-02-15

    Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming more and more popular nowadays. AI-techniques have the following features: can learn from examples; are fault tolerant in the sense that they are able to handle noisy and incomplete data; are able to deal with non-linear problems; and once trained can perform prediction and generalization at high speed. AI-based systems are being developed and deployed worldwide in a myriad of applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. AI have been used and applied in different sectors, such as engineering, economics, medicine, military, marine, etc. They have also been applied for modeling, identification, optimization, prediction, forecasting, and control of complex systems. The main objective of this paper is to present an overview of the AI-techniques for sizing photovoltaic (PV) systems: stand-alone PVs, grid-connected PV systems, PV-wind hybrid systems, etc. Published literature presented in this paper show the potential of AI as a design tool for the optimal sizing of PV systems. Additionally, the advantage of using an AI-based sizing of PV systems is that it provides good optimization, especially in isolated areas, where the weather data are not always available. (author)

  20. BWR shutdown analyzer using artificial intelligence (AI) techniques

    International Nuclear Information System (INIS)

    Cain, D.G.

    1986-01-01

    A prototype alarm system for detecting abnormal reactor shutdowns based on artificial intelligence technology is described. The system incorporates knowledge about Boiling Water Reactor (BWR) plant design and component behavior, as well as knowledge required to distinguish normal, abnormal, and ATWS accident conditions. The system was developed using a software tool environment for creating knowledge-based applications on a LISP machine. To facilitate prototype implementation and evaluation, a casual simulation of BWR shutdown sequences was developed and interfaced with the alarm system. An intelligent graphics interface for execution and control is described. System performance considerations and general observations relating to artificial intelligence application to nuclear power plant problems are provided

  1. Advances in soft computing, intelligent robotics and control

    CERN Document Server

    Fullér, Robert

    2014-01-01

    Soft computing, intelligent robotics and control are in the core interest of contemporary engineering. Essential characteristics of soft computing methods are the ability to handle vague information, to apply human-like reasoning, their learning capability, and ease of application. Soft computing techniques are widely applied in the control of dynamic systems, including mobile robots. The present volume is a collection of 20 chapters written by respectable experts of the fields, addressing various theoretical and practical aspects in soft computing, intelligent robotics and control. The first part of the book concerns with issues of intelligent robotics, including robust xed point transformation design, experimental verification of the input-output feedback linearization of differentially driven mobile robot and applying kinematic synthesis to micro electro-mechanical systems design. The second part of the book is devoted to fundamental aspects of soft computing. This includes practical aspects of fuzzy rule ...

  2. Development of intelligent supervisory control system

    International Nuclear Information System (INIS)

    Takizawa, Y.; Fukumoto, A.; Makino, M.; Takiguchi, S.

    1994-01-01

    The objective of the development of an intelligent supervisory control system for next generation plants is enhancement of the operational reliability by applying the recent outcome of artificial intelligence and computer technologies. This system consists of the supervisory control and monitoring for automatic operation, the equipment operation support for historical data management and for test scheduling, the operators' decision making support for accidental plant situations and the human-friendly interface of these support functions. The verification test results showed the validity of the functions realized by this system for the next generation control room. (author)

  3. Intelligent distributed control for nuclear power plants

    International Nuclear Information System (INIS)

    Klevans, E.H.

    1991-01-01

    In September of 1989 work began on the DOE University Program grant DE-FG07-89ER12889. The grant provides support for a three year project to develop and demonstrate Intelligent Distributed Control (IDC) for Nuclear Power Plants. The body of this First Annual Technical Progress report summarizes the first year tasks while the appendices provide detailed information presented at conference meetings. One major addendum report, authored by M.A. Schultz, describes the ultimate goals and projected structure of an automatic distributed control system for EBR-2. The remaining tasks of the project develop specific implementations of various components required to demonstrate the intelligent distributed control concept

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

    International Nuclear Information System (INIS)

    Sharma, D.D.; Miller, D.D.; Hajek, B.; Chandrasekaran, B.

    1986-01-01

    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

  5. Computational Intelligence based techniques for islanding detection of distributed generation in distribution network: A review

    International Nuclear Information System (INIS)

    Laghari, J.A.; Mokhlis, H.; Karimi, M.; Bakar, A.H.A.; Mohamad, Hasmaini

    2014-01-01

    Highlights: • Unintentional and intentional islanding, their causes, and solutions are presented. • Remote, passive, active and hybrid islanding detection techniques are discussed. • The limitation of these techniques in accurately detect islanding are discussed. • Computational intelligence techniques ability in detecting islanding is discussed. • Review of ANN, fuzzy logic control, ANFIS, Decision tree techniques is provided. - Abstract: Accurate and fast islanding detection of distributed generation is highly important for its successful operation in distribution networks. Up to now, various islanding detection technique based on communication, passive, active and hybrid methods have been proposed. However, each technique suffers from certain demerits that cause inaccuracies in islanding detection. Computational intelligence based techniques, due to their robustness and flexibility in dealing with complex nonlinear systems, is an option that might solve this problem. This paper aims to provide a comprehensive review of computational intelligence based techniques applied for islanding detection of distributed generation. Moreover, the paper compares the accuracies of computational intelligence based techniques over existing techniques to provide a handful of information for industries and utility researchers to determine the best method for their respective system

  6. Artificial intelligence techniques for photovoltaic applications: A review

    Energy Technology Data Exchange (ETDEWEB)

    Mellit, Adel [Department of Electronics, Faculty of Sciences Engineering, LAMEL Laboratory, Jijel University, Oulad-aissa, P.O. Box 98, Jijel 18000 (Algeria); Kalogirou, Soteris A. [Department of Mechanical Engineering and Materials Science and Engineering, Cyprus University of Technology, P.O. Box 50329, Limassol 3603 (Cyprus)

    2008-10-15

    Artificial intelligence (AI) techniques are becoming useful as alternate approaches to conventional techniques or as components of integrated systems. They have been used to solve complicated practical problems in various areas and are becoming more popular nowadays. They can learn from examples, are fault tolerant in the sense that they are able to handle noisy and incomplete data, are able to deal with nonlinear problems and once trained can perform prediction and generalization at high speed. AI-based systems are being developed and deployed worldwide in a wide variety of applications, mainly because of their symbolic reasoning, flexibility and explanation capabilities. AI has been used in different sectors, such as engineering, economics, medicine, military, marine, etc. They have also been applied for modeling, identification, optimization, prediction, forecasting and control of complex systems. The paper outlines an understanding of how AI systems operate by way of presenting a number of problems in photovoltaic systems application. Problems presented include three areas: forecasting and modeling of meteorological data, sizing of photovoltaic systems and modeling, simulation and control of photovoltaic systems. Published literature presented in this paper show the potential of AI as design tool in photovoltaic systems. (author)

  7. Dynamic vulnerability assessment and intelligent control for sustainable power systems

    CERN Document Server

    Gonzalez-Longatt, Francisco

    2018-01-01

    Identifying, assessing, and mitigating electric power grid vulnerabilities is a growing focus in short-term operational planning of power systems. Through illustrated application, this important guide surveys state-of-the-art methodologies for the assessment and enhancement of power system security in short-term operational planning and real-time operation. The methodologies employ advanced methods from probabilistic theory, data mining, artificial intelligence, and optimization, to provide knowledge-based support for monitoring, control (preventive and corrective), and decision making tasks. Key features: Introduces behavioural recognition in wide-area monitoring and security constrained optimal power flow for intelligent control and protection and optimal grid management. Provides in-depth understanding of risk-based reliability and security assessment, dynamic vulnerability as essment methods, supported by the underpinning mathematics. Develops expertise in mitigation techniques using intelligent protect...

  8. Contribution to intelligent vehicle platoon control

    OpenAIRE

    Zhao , Jin

    2010-01-01

    This PhD thesis is dedicated to the control strategies for intelligent vehicle platoon in highway with the main aims of alleviating traffic congestion and improving traffic safety. After a review of the different existing automated driving systems, the vehicle longitudinal and lateral dynamic models are derived. Then, the longitudinal control and lateral control strategies are studied respectively. At first, the longitudinal control system is designed to be hierarchical with an upper level co...

  9. Express: the reliability of complex systems and artificial intelligence techniques

    International Nuclear Information System (INIS)

    Ancelin, C.; Le, P.; Saint-Quentin, S. de

    1987-01-01

    The probabilistic safety study for the Paluel nuclear power station, commissioned by EDF in 1986, involved development of data processing methods and equipment which was to be given an entirely new impetus by the use of artificial intelligence techniques. The authors describe the salient features of the approach which was adopted and the lessons learnt from the way it was applied in practice [fr

  10. 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.

  11. Contamination Control Techniques

    International Nuclear Information System (INIS)

    EBY, J.L.

    2000-01-01

    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

  12. E-learning systems intelligent techniques for personalization

    CERN Document Server

    Klašnja-Milićević, Aleksandra; Ivanović, Mirjana; Budimac, Zoran; Jain, Lakhmi C

    2017-01-01

    This monograph provides a comprehensive research review of intelligent techniques for personalisation of e-learning systems. Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented. This approach incorporates a recommender system based on collaborative tagging techniques that adapts to the interests and level of students' knowledge. These innovations are important contributions of this monograph. Theoretical models and techniques are illustrated on a real personalised tutoring system for teaching Java programming language. The monograph is directed to, students and researchers interested in the e-learning and personalization techniques. .

  13. Application of artificial intelligence techniques to TRR operation

    International Nuclear Information System (INIS)

    Ho, L.; Tseng, C.; Chang, S.

    1986-01-01

    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

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

    OpenAIRE

    Aarshay Jain; Deepansh Jagotra; Vijayant Agarwal

    2014-01-01

    The primary focus of this study is implementation of Artificial Intelligence (AI) technique for developing an inverse kinematics solution for the Raven-IITM surgical research robot [1]. First, the kinematic model of the Raven-IITM robot was analysed along with the proposed analytical solution [2] for inverse kinematics problem. Next, The Artificial Neural Network (ANN) techniques was implemented. The training data for the same was careful selected by keeping manipulability constraints in mind...

  15. Fuzzy Logic Controller Design for Intelligent Robots

    Directory of Open Access Journals (Sweden)

    Ching-Han Chen

    2017-01-01

    Full Text Available This paper presents a fuzzy logic controller by which a robot can imitate biological behaviors such as avoiding obstacles or following walls. The proposed structure is implemented by integrating multiple ultrasonic sensors into a robot to collect data from a real-world environment. The decisions that govern the robot’s behavior and autopilot navigation are driven by a field programmable gate array- (FPGA- based fuzzy logic controller. The validity of the proposed controller was demonstrated by simulating three real-world scenarios to test the bionic behavior of a custom-built robot. The results revealed satisfactorily intelligent performance of the proposed fuzzy logic controller. The controller enabled the robot to demonstrate intelligent behaviors in complex environments. Furthermore, the robot’s bionic functions satisfied its design objectives.

  16. Hybrid Intelligent Control for Submarine Stabilization

    Directory of Open Access Journals (Sweden)

    Minghui Wang

    2013-05-01

    Full Text Available Abstract While sailing near the sea surface, submarines will often undergo rolling motion caused by wave disturbance. Fierce rolling motion seriously affects their normal operation and even threatens their security. We propose a new control method for roll stabilization. This paper studies hybrid intelligent control combining a fuzzy control, a neural network and extension control technology. Every control strategy can achieve the ideal control effect within the scope of its effective control. The neuro-fuzzy control strategy is used to improve the robustness of the controller. The speed control strategy and the course control strategy are conducted to extend the control range. The paper also proposes the design of the controller and carries out the simulation experiment in different sea conditions. The simulation results show that the control method proposed can indeed effectively improve the control performance of submarine stabilization.

  17. An Artificial Neural Network Controller for Intelligent Transportation Systems Applications

    Science.gov (United States)

    1996-01-01

    An Autonomous Intelligent Cruise Control (AICC) has been designed using a feedforward artificial neural network, as an example for utilizing artificial neural networks for nonlinear control problems arising in intelligent transportation systems appli...

  18. Intelligent Mechatronic Systems Modeling, Control and Diagnosis

    CERN Document Server

    Merzouki, Rochdi; Pathak, Pushparaj Mani; Ould Bouamama, Belkacem

    2013-01-01

    Acting as a support resource for practitioners and professionals looking to advance their understanding of complex mechatronic systems, Intelligent Mechatronic Systems explains their design and recent developments from first principles to practical applications. Detailed descriptions of the mathematical models of complex mechatronic systems, developed from fundamental physical relationships, are built on to develop innovative solutions with particular emphasis on physical model-based control strategies. Following a concurrent engineering approach, supported by industrial case studies, and drawing on the practical experience of the authors, Intelligent Mechatronic Systems covers range of topic and includes:  • An explanation of a common graphical tool for integrated design and its uses from modeling and simulation to the control synthesis • Introductions to key concepts such as different means of achieving fault tolerance, robust overwhelming control and force and impedance control • Dedicated chapters ...

  19. Operating control techniques for maglev transport systems

    Energy Technology Data Exchange (ETDEWEB)

    Kraft, K H; Schnieder, E

    1984-06-01

    The technical and operational possibilities of magnetic levitation transport systems can only be fully exploited by introducing 'intelligent' control systems which ensure automatic and trouble-free train running. The solution of exacting requirements in the fields of traction dynamics, security and control as well as information gathering transmission and processing is an important prior condition in that respect. The authors report here on the present state of research and development in operating control techniques applicable to maglev transport systems.

  20. Intelligent Techniques for Power Systems Vulnerability Assessment

    OpenAIRE

    Mohamed A. El-Sharkawi

    2002-01-01

    With power grids considered national security matters, the reliable operation of the system is of top priority to utilities.  This concern is amplified by the utility’s deregulation, which increases the system’s openness while simultaneously decreasing the applied degree of control.  Vulnerability Assessment (VA) deals with the power system’s ability to continue to provide service in case of an unforeseen catastrophic contingency.  Such contingencies may include unauthorized tripping, breaks ...

  1. Applications of artificial intelligence to reactor and plant control

    International Nuclear Information System (INIS)

    Bernard, J.A.

    1989-01-01

    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)

  2. Intelligent distributed control for nuclear power plants

    International Nuclear Information System (INIS)

    Klevans, E.H.

    1993-01-01

    This project was initiated in September 1989 as a three year project to develop and demonstrate Intelligent Distributed Control (IDC) for Nuclear Power Plants. There were two primary goals of this research project. The first goal was to combine diagnostics and control to achieve a highly automated power plant as described by M.A. Schultz. The second goal was to apply this research to develop a prototype demonstration on an actual power plant system, the EBR-2 steam plant. Described in this Final (Third Annual) Technical Progress Report is the accomplishment of the project's final milestone, an in-plant intelligent control experiment conducted on April 1, 1993. The development of the experiment included: simulation validation, experiment formulation and final programming, procedure development and approval, and experimental results. Other third year developments summarized in this report are: (1) a theoretical foundation for Reconfigurable Hybrid Supervisory Control, (2) a steam plant diagnostic system, (3) control console design tools and (4) other advanced and intelligent control

  3. Launch vehicle operations cost reduction through artificial intelligence techniques

    Science.gov (United States)

    Davis, Tom C., Jr.

    1988-01-01

    NASA's Kennedy Space Center has attempted to develop AI methods in order to reduce the cost of launch vehicle ground operations as well as to improve the reliability and safety of such operations. Attention is presently given to cost savings estimates for systems involving launch vehicle firing-room software and hardware real-time diagnostics, as well as the nature of configuration control and the real-time autonomous diagnostics of launch-processing systems by these means. Intelligent launch decisions and intelligent weather forecasting are additional applications of AI being considered.

  4. Search techniques in intelligent classification systems

    CERN Document Server

    Savchenko, Andrey V

    2016-01-01

    A unified methodology for categorizing various complex objects is presented in this book. Through probability theory, novel asymptotically minimax criteria suitable for practical applications in imaging and data analysis are examined including the special cases such as the Jensen-Shannon divergence and the probabilistic neural network. An optimal approximate nearest neighbor search algorithm, which allows faster classification of databases is featured. Rough set theory, sequential analysis and granular computing are used to improve performance of the hierarchical classifiers. Practical examples in face identification (including deep neural networks), isolated commands recognition in voice control system and classification of visemes captured by the Kinect depth camera are included. This approach creates fast and accurate search procedures by using exact probability densities of applied dissimilarity measures. This book can be used as a guide for independent study and as supplementary material for a technicall...

  5. Intelligent Techniques for Power Systems Vulnerability Assessment

    Directory of Open Access Journals (Sweden)

    Mohamed A. El-Sharkawi

    2002-06-01

    Full Text Available With power grids considered national security matters, the reliable operation of the system is of top priority to utilities.  This concern is amplified by the utility’s deregulation, which increases the system’s openness while simultaneously decreasing the applied degree of control.  Vulnerability Assessment (VA deals with the power system’s ability to continue to provide service in case of an unforeseen catastrophic contingency.  Such contingencies may include unauthorized tripping, breaks in communication links, sabotage or intrusion by external agents, human errors, natural calamities and faults.  These contingencies could lead to a disruption of service to part or all of the system.  The service disruption is known as outage or blackout.  The paper outlines an approach by which feature extraction and boundary tracking can be implemented to achieve on line vulnerability assessment.

  6. Intelligent sensing and control of gas metal arc welding

    International Nuclear Information System (INIS)

    Smartt, H.B.; Johnson, J.A.

    1993-01-01

    Intelligent sensing and control is a multidisciplinary approach that attempts to build adequate sensing capability, knowledge of process physics, control capability, and welding engineering into the welding system such that the welding machine is aware of the state of the weld and knows how to make a good weld. The sensing and control technology should reduce the burden on the welder and welding engineer while providing the great adaptability needed to accommodate the variability found in the production world. This approach, accomplished with application of AI techniques, breaks the tradition of separate development of procedure and control technology

  7. Artificial intelligence and accelerator control

    International Nuclear Information System (INIS)

    Weygand, D.P.

    1987-01-01

    In this paper we review a knowledge-based, domain specific expert system which is under development at Brookhaven National Laboratory to aid in the control of the Heavy Ion Transfer Line (HITL). The expert system is being developed in order to minimize down time after a change of running conditions or at the start of a new run. While the control of HITL is relatively simple compared to a synchrotron, conceptually, many of the problems that are encountered may be extrapolated to more complex machines

  8. Intelligent control with implementation on the wind energy conversion system

    International Nuclear Information System (INIS)

    Basma, Mohamad Khalil

    1997-05-01

    In this thesis our main job is to compare intelligent control and conventional control algorithms, by applying each scheme to the same control problem. Based on simulation, we analyze and compare the results of applying fuzzy logic and neural networks controllers on a popular control problem: variable speed wind energy conversion system. The reason behind our choice is the challenging nature of the problem where the plant should be controlled to maximize the power generated, while respecting its hardware constraints under varying operating conditions and disturbances. We have shown the effectiveness of fuzzy logic exciter controller for the adopted wind energy generator when compared to a conventional PI exciter. It showed better performance in the whole operating range. However, in the high wind speeds region, both controllers were unable to deliver the rpm requirements. We proposed the use of neural network intelligent techniques to supply us the optimal pitch. Our aim was to develop a simple and reliable controller that can deliver this optimal output, while remaining adaptive to system uncertainties and disturbances. The proposed fuzzy controller with a neural pitch controller showed best dynamic and robust performance as compared to the adaptive pitch controller together with the PI exciter. This study has shown that artificial neural networks and fuzzy logic control algorithms can be implemented for real time control implementations. the neuro-fuzzy control approach is robust and its performance is superior to that of traditional control methods. (author)

  9. Greenhouse intelligent control system based on microcontroller

    Science.gov (United States)

    Zhang, Congwei

    2018-04-01

    As one of the hallmarks of agricultural modernization, intelligent greenhouse has the advantages of high yield, excellent quality, no pollution and continuous planting. Taking AT89S52 microcontroller as the main controller, the greenhouse intelligent control system uses soil moisture sensor, temperature and humidity sensors, light intensity sensor and CO2 concentration sensor to collect measurements and display them on the 12864 LCD screen real-time. Meantime, climate parameter values can be manually set online. The collected measured values are compared with the set standard values, and then the lighting, ventilation fans, warming lamps, water pumps and other facilities automatically start to adjust the climate such as light intensity, CO2 concentration, temperature, air humidity and soil moisture of the greenhouse parameter. So, the state of the environment in the greenhouse Stabilizes and the crop grows in a suitable environment.

  10. Intelligent control on wind farm

    DEFF Research Database (Denmark)

    Wei, Mu; Chen, Zhe

    2010-01-01

    with the wind farm makes the grid more vulnerable. The communication technologies have been considered as a solution to solve the problems according to the IEC 61400-25 series protocols. This paper presents the significance of communication technologies in wind farm system by the simulations on some practical......Since the renewable energy is popularly applied in power industry, especially the smart grid is fast developing all over the world during these years, the reliable connection between a wind farm and the main grid has been focused on. Due to the difficult control on the wind energy, the connection...... scenarios. By delivering the signals among WTs (wind turbines) and control centers, they both are able to recognize another side’s operation situation and to adjust its own state to realize the optimization. A scenario is designed in this paper, in which a fault occurs in wind farm; then the protection...

  11. Intelligent buildings, automatic fire alarm and fire-protection control system

    International Nuclear Information System (INIS)

    Tian Deyuan

    1999-01-01

    The author describes in brief the intelligent buildings, and the automatic fire alarm and fire-protection control system. On the basis of the four-bus, three-bus and two-bus, a new transfer technique was developed

  12. An artificial intelligence approach to accelerator control systems

    International Nuclear Information System (INIS)

    Schultz, D.E.; Hurd, J.W.; Brown, S.K.

    1987-01-01

    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

  13. Determination of rock depth using artificial intelligence techniques

    Institute of Scientific and Technical Information of China (English)

    R. Viswanathan; Pijush Samui

    2016-01-01

    This article adopts three artificial intelligence techniques, Gaussian Process Regression (GPR), Least Square Support Vector Machine (LSSVM) and Extreme Learning Machine (ELM), for prediction of rock depth (d) at any point in Chennai. GPR, ELM and LSSVM have been used as regression techniques. Latitude and longitude are also adopted as inputs of the GPR, ELM and LSSVM models. The performance of the ELM, GPR and LSSVM models has been compared. The developed ELM, GPR and LSSVM models produce spatial variability of rock depth and offer robust models for the prediction of rock depth.

  14. Stochastic Feedforward Control Technique

    Science.gov (United States)

    Halyo, Nesim

    1990-01-01

    Class of commanded trajectories modeled as stochastic process. Advanced Transport Operating Systems (ATOPS) research and development program conducted by NASA Langley Research Center aimed at developing capabilities for increases in capacities of airports, safe and accurate flight in adverse weather conditions including shear, winds, avoidance of wake vortexes, and reduced consumption of fuel. Advances in techniques for design of modern controls and increased capabilities of digital flight computers coupled with accurate guidance information from Microwave Landing System (MLS). Stochastic feedforward control technique developed within context of ATOPS program.

  15. Automation of fusion first wall design using artificial intelligence technique

    International Nuclear Information System (INIS)

    Yoshimura, Shinobu; Yagawa, Genki; Mochizuki, Yoshihiko

    1990-01-01

    This paper describes the application of artificial intelligence techniques to a design automation of the fusion first wall to be operated in the complex environment where huge electromagnetic and thermal loading as well as heavy neutron irradiation occur. As a basic strategy of designing structure shape considering many coupled phenomena, an ordinary design procedure based on the generate and test strategy is adopted because of its simplicity and broad applicability. To automate the design procedure with maintaining its flexibility, extensibility and efficiency, artificial intelligence techniques are utilized in the following. An object-oriented knowledge representation technique is adopted to store knowledge modules, that is, objects, related to the first wall design, while a data-flow processing technique is utilized as an inference mechanism among the knowledge modules. These techniques realize the flexibility and extensibility of the system. Moreover, as an efficient design modification mechanism, which is essential in a design process, an empirical approach based on experts' empirical knowledge and a mathematical approach based on a kind of numerical sensitivity analysis are introduced. The developed system is applied to a simple example of the design of a two-dimensional model of the first wall with a cooling channel, and its fundamental performance is clearly demonstrated. (author)

  16. Adaptive Distributed Intelligent Control Architecture for Future Propulsion Systems (Preprint)

    National Research Council Canada - National Science Library

    Behbahani, Alireza R

    2007-01-01

    .... Distributed control is potentially an enabling technology for advanced intelligent propulsion system concepts and is one of the few control approaches that is able to provide improved component...

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

    International Nuclear Information System (INIS)

    Plander, I.

    1987-01-01

    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

  18. Intelligent control aspects of fuzzy logic and neural nets

    CERN Document Server

    Harris, C J; Brown, M

    1993-01-01

    With increasing demands for high precision autonomous control over wide operating envelopes, conventional control engineering approaches are unable to adequately deal with system complexity, nonlinearities, spatial and temporal parameter variations, and with uncertainty. Intelligent Control or self-organising/learning control is a new emerging discipline that is designed to deal with problems. Rather than being model based, it is experiential based. Intelligent Control is the amalgam of the disciplines of Artificial Intelligence, Systems Theory and Operations Research. It uses most recent expe

  19. Intelligent Power Control of DC Microgrid

    DEFF Research Database (Denmark)

    Hajizadeh, Amin; N. Soltani, Mohsen; Norum, Lars

    2017-01-01

    In this paper, an intelligent power management strategy is proposed for hybrid DC microgrid, including wind turbine, fuel cell and battery energy storage. The considered wind turbine has a permanent magnet synchronous generator (PMSG). In the considered structure, wind turbine operates as the main...... condition and fuel cell will not generate excessive power. The proposed control scheme is based on the fuzzy algorithm. All simulations in variant operational modes are performed by MATLAB/Simulink and results show the effectiveness of the proposed control strategy....

  20. Intelligent Control and Operation of Distribution System

    DEFF Research Database (Denmark)

    Bhattarai, Bishnu Prasad

    methodology to ensure efficient control and operation of the future distribution networks. The major scientific challenge is thus to develop control models and strategies to coordinate responses from widely distributed controllable loads and local generations. Detailed models of key Smart Grid (SG) elements...... in this direction but also benefit distribution system operators in the planning and development of the distribution network. The major contributions of this work are described in the following four stages: In the first stage, an intelligent Demand Response (DR) control architecture is developed for coordinating...... the key SG actors, namely consumers, network operators, aggregators, and electricity market entities. A key intent of the architecture is to facilitate market participation of residential consumers and prosumers. A Hierarchical Control Architecture (HCA) having primary, secondary, and tertiary control...

  1. Intelligent distributed control for nuclear power plants

    International Nuclear Information System (INIS)

    Klevans, E.H.

    1992-01-01

    This project was initiated in September 1989 as a three year project to develop and demonstrate Intelligent Distributed Control (IDC) for Nuclear Power Plants. The body of this Third Annual Technical Progress report summarizes the period from September 1991 to October 1992. There were two primary goals of this research project. The first goal was to combine diagnostics and control to achieve a highly automated power plant as described by M.A. Schultz. His philosophy, is to improve public perception of the safety of nuclear power plants by incorporating a high degree of automation where a greatly simplified operator control console minimizes the possibility of human error in power plant operations. To achieve this goal, a hierarchically distributed control system with automated responses to plant upset conditions was pursued in this research. The second goal was to apply this research to develop a prototype demonstration on an actual power plant system, the EBR-2 stem plant. Emphasized in this Third Annual Technical Progress Report is the continuing development of the in-plant intelligent control demonstration for the final project milestone and includes: simulation validation and the initial approach to experiment formulation

  2. Intelligent tutors for control center operator training

    Energy Technology Data Exchange (ETDEWEB)

    Vale, Z.A. [Porto Univ. (Portugal). Dept. of Electrical and Computer Engineering; Fernandes, M.F.; Marques, A. [Electricity of Portugal, Sacavem (Portugal)

    1995-12-31

    Power systems are presently remotely operated and controlled from control centers that receive on-line information about the power system state. Control center operators have very high-demanding tasks what makes their training a key issue for the performance of the whole power system. Simulators are usually used by electrical utilities for this purpose but they are very expensive applications and their use requires the preparation of the training sessions by qualified training staff which is a very time consuming task. Due to this, these simulators are only used a few times a year. Intelligent Tutoring Systems (ITS) provide some new possibilities for control center operator training making easier its use without much assistance of the teaching staff. On the other hand, an expert system in use in a control center can be adapted to an ITS to train operators without much effort. 18 refs

  3. The Need for Intelligent Control of Space Power Systems

    Science.gov (United States)

    May, Ryan David; Soeder, James F.; Beach, Raymond F.; McNelis, Nancy B.

    2013-01-01

    As manned spacecraft venture farther from Earth, the need for reliable, autonomous control of vehicle subsystems becomes critical. This is particularly true for the electrical power system which is critical to every other system. Autonomy can not be achieved by simple scripting techniques due to the communication latency times and the difficulty associated with failures (or combinations of failures) that need to be handled in as graceful a manner as possible to ensure system availability. Therefore an intelligent control system must be developed that can respond to disturbances and failures in a robust manner and ensure that critical system loads are served and all system constraints are respected.

  4. 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.

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

    Science.gov (United States)

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

    2013-02-01

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

  6. Experimental development of power reactor intelligent control

    International Nuclear Information System (INIS)

    Edwards, R.M.; Garcia, H.E.; Lee, K.Y.

    1992-01-01

    The US nuclear utility industry initiated an ambitious program to modernize the control systems at a minimum of ten existing nuclear power plants by the year 2000. That program addresses urgent needs to replace obsolete instrumentation and analog controls with highly reliable state-of-the-art computer-based digital systems. Large increases in functionality that could theoretically be achieved in a distributed digital control system are not an initial priority in the industry program but could be logically considered in later phases. This paper discusses the initial development of an experimental sequence for developing, testing, and verifying intelligent fault-accommodating control for commercial nuclear power plant application. The sequence includes an ultra-safe university research reactor (TRIGA) and a passively safe experimental power plant (Experimental Breeder Reactor 2)

  7. Intelligent CAMAC crate controller incorporating a transputer

    International Nuclear Information System (INIS)

    Saeki, T.; Ueda, I.; Anraku, K.

    1995-01-01

    A CAMAC crate controller module having a built-in transputer was developed, being named the ''Intelligent CAMAC Crate Controller (ICCC)''. Due to the transputer's architecture, multiple ICCCs can be networked by simple serial link connections. The control programs are developed in Occam or C language, which support conccurrent algorithms and their implementation in transputer networks. Each ICCC controls the front-end CAMAC modules in the crate, operates in parallel, and interpretes commands from the host computer. Data read from the modules is concurrently and autonomously processed, and then transmitted to the network where it is gathered into the host computer file system. The present paper describes the ICCC's hardware and software using a simple configuration network. Our particular device application for a balloon-borne experiment is also discussed, i.e., a data acquisition system networking twenty-seven transputers. ((orig.))

  8. State and data techniques for control of discontinuous systems

    International Nuclear Information System (INIS)

    Kisner, R.A.

    1986-01-01

    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

  9. Robust algebraic image enhancement for intelligent control systems

    Science.gov (United States)

    Lerner, Bao-Ting; Morrelli, Michael

    1993-01-01

    Robust vision capability for intelligent control systems has been an elusive goal in image processing. The computationally intensive techniques a necessary for conventional image processing make real-time applications, such as object tracking and collision avoidance difficult. In order to endow an intelligent control system with the needed vision robustness, an adequate image enhancement subsystem capable of compensating for the wide variety of real-world degradations, must exist between the image capturing and the object recognition subsystems. This enhancement stage must be adaptive and must operate with consistency in the presence of both statistical and shape-based noise. To deal with this problem, we have developed an innovative algebraic approach which provides a sound mathematical framework for image representation and manipulation. Our image model provides a natural platform from which to pursue dynamic scene analysis, and its incorporation into a vision system would serve as the front-end to an intelligent control system. We have developed a unique polynomial representation of gray level imagery and applied this representation to develop polynomial operators on complex gray level scenes. This approach is highly advantageous since polynomials can be manipulated very easily, and are readily understood, thus providing a very convenient environment for image processing. Our model presents a highly structured and compact algebraic representation of grey-level images which can be viewed as fuzzy sets.

  10. Intelligent Control Wheelchair Using a New Visual Joystick

    Directory of Open Access Journals (Sweden)

    Yassine Rabhi

    2018-01-01

    Full Text Available A new control system of a hand gesture-controlled wheelchair (EWC is proposed. This smart control device is suitable for a large number of patients who cannot manipulate a standard joystick wheelchair. The movement control system uses a camera fixed on the wheelchair. The patient’s hand movements are recognized using a visual recognition algorithm and artificial intelligence software; the derived corresponding signals are thus used to control the EWC in real time. One of the main features of this control technique is that it allows the patient to drive the wheelchair with a variable speed similar to that of a standard joystick. The designed device “hand gesture-controlled wheelchair” is performed at low cost and has been tested on real patients and exhibits good results. Before testing the proposed control device, we have created a three-dimensional environment simulator to test its performances with extreme security. These tests were performed on real patients with diverse hand pathologies in Mohamed Kassab National Institute of Orthopedics, Physical and Functional Rehabilitation Hospital of Tunis, and the validity of this intelligent control system had been proved.

  11. Intelligent control-III: fuzzy control system

    International Nuclear Information System (INIS)

    Nagrial, M.H.

    2004-01-01

    During the last decade or so, fuzzy logic control (FLC) has emerged as one of the most active and fruitful areas of research and development. The applications include industrial process control to medical diagnostic and financial markets. Many consumer products using this technology are available in the market place. FLC is best suited to complex ill-defined processes that can be controlled by a skilled human operator without much knowledge of their underlying dynamics. This lecture will cover the basic architecture and the design methodology of fuzzy logic controllers. FLC will be strongly based on the concepts of fuzzy set theory, introduced in first lecture. Some practical applications will also be discussed and presented. (author)

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

    Directory of Open Access Journals (Sweden)

    Marvin T. Chan

    2015-01-01

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

  13. Using Artificial Intelligence Techniques to Implement a Multifactor Authentication System

    Directory of Open Access Journals (Sweden)

    Jackson Phiri

    2011-08-01

    Full Text Available The recent years have seen a rise in the number of cases of cyber-crime committed through identity theft and fraud. To address this problem, this paper uses adaptive neural-fuzzy inference system, fuzzy logic and artificial neural network to implement a multifactor authentication system through a technique of information fusion. To begin with, the identity attributes are mined using the three corpora from three major sources namely the social networks, a set of questionnaires and application forms from the various services offered both in the real and cyberspace. The statistical information generated by the corpora is then used to compose an identity attribute metric model. The composed identity attributes metrics values classified as biometrics, device metrics and pseudo metrics are then fused at the score level through a technique of information fusion in a multifactor authentication system by using each of the above artificial intelligence technologies and the results compared.

  14. Artificial intelligence techniques for embryo and oocyte classification.

    Science.gov (United States)

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

    2013-01-01

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

  15. The development of advanced robotic technology. A study on the tele-existence and intelligent control of a robot system for nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Chung, Myung Jin; Byun, Jueng Nam; Kim, Jong Hwan; Lee, Ju Jang; Bang, Seok Won; Chu, Gil Hwan; Park, Jong Cheol; Choi, Jong Seok; Yang, Jung Min; Hong, Sun Ki [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

    1995-07-01

    To increase the efficiency of human intelligence it is required to develop an intelligent monitoring and system. In this research, we develop intelligent control methods related with tele-operation, tele-existence, real-time control technique, and intelligent control technique. Those are key techniques in tele-operation, especially for the repair and maintenance of nuclear power plants. The objective of this project is to develop of the tele-existence and intelligent control system for a robot used in the nuclear power plants. (author). 20 refs.

  16. Modelling and Intelligent Control of an Elastic Link Robot Manipulator

    Directory of Open Access Journals (Sweden)

    Malik Loudini

    2013-01-01

    Full Text Available In this paper, precise control of the end-point position of a planar single-link elastic manipulator robot is discussed. The Timoshenko beam theory (TBT has been used to characterize the structural link elasticity including important damping mechanisms. A suitable nonlinear model is derived based on the Lagrangian assumed modes method. Elastic link manipulators are classified as systems possessing highly complex dynamics. In addition, the environment in which they operate may have a lot of disturbances. These give rise to special problems that may be solved using intelligent control techniques. The application of two advanced control strategies based on fuzzy set theory is investigated. The first closed-loop control scheme to be applied is the standard Proportional-Derivative (PD type fuzzy logic controller (FLC, also known as PD-type Mamdani's FLC (MPDFLC. Then, a genetic algorithm (GA is used to optimize the MPDFLC parameters with innovative tuning procedures. Both the MPDFLC and the GA optimized FLC (GAOFLC are implemented and tested to achieve a precise control of the manipulator end-point. The performances of the adopted closed-loop intelligent control strategies are examined via simulation experiments.

  17. Intelligent manipulation technique for multi-branch robotic systems

    Science.gov (United States)

    Chen, Alexander Y. K.; Chen, Eugene Y. S.

    1990-01-01

    New analytical development in kinematics planning is reported. The INtelligent KInematics Planner (INKIP) consists of the kinematics spline theory and the adaptive logic annealing process. Also, a novel framework of robot learning mechanism is introduced. The FUzzy LOgic Self Organized Neural Networks (FULOSONN) integrates fuzzy logic in commands, control, searching, and reasoning, the embedded expert system for nominal robotics knowledge implementation, and the self organized neural networks for the dynamic knowledge evolutionary process. Progress on the mechanical construction of SRA Advanced Robotic System (SRAARS) and the real time robot vision system is also reported. A decision was made to incorporate the Local Area Network (LAN) technology in the overall communication system.

  18. 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...

  19. An intelligent content discovery technique for health portal content management.

    Science.gov (United States)

    De Silva, Daswin; Burstein, Frada

    2014-04-23

    Continuous content management of health information portals is a feature vital for its sustainability and widespread acceptance. Knowledge and experience of a domain expert is essential for content management in the health domain. The rate of generation of online health resources is exponential and thereby manual examination for relevance to a specific topic and audience is a formidable challenge for domain experts. Intelligent content discovery for effective content management is a less researched topic. An existing expert-endorsed content repository can provide the necessary leverage to automatically identify relevant resources and evaluate qualitative metrics. This paper reports on the design research towards an intelligent technique for automated content discovery and ranking for health information portals. The proposed technique aims to improve efficiency of the current mostly manual process of portal content management by utilising an existing expert-endorsed content repository as a supporting base and a benchmark to evaluate the suitability of new content A model for content management was established based on a field study of potential users. The proposed technique is integral to this content management model and executes in several phases (ie, query construction, content search, text analytics and fuzzy multi-criteria ranking). The construction of multi-dimensional search queries with input from Wordnet, the use of multi-word and single-word terms as representative semantics for text analytics and the use of fuzzy multi-criteria ranking for subjective evaluation of quality metrics are original contributions reported in this paper. The feasibility of the proposed technique was examined with experiments conducted on an actual health information portal, the BCKOnline portal. Both intermediary and final results generated by the technique are presented in the paper and these help to establish benefits of the technique and its contribution towards effective

  20. 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.

  1. Promises in intelligent plant control systems

    International Nuclear Information System (INIS)

    Otaduy, P.J.

    1987-01-01

    The control system is the brain of a power plant. The traditional goal of control systems has been productivity. However, in nuclear power plants the potential for disaster requires safety to be the dominant concern, and the worldwide political climate demands trustworthiness for nuclear power plants. To keep nuclear generation as a viable option for power in the future, trust is the essential critical goal which encompasses all others. In most of today's nuclear plants the control system is a hybrid of analog, digital, and human components that focuses on productivity and operates under the protective umbrella of an independent engineered safety system. Operation of the plant is complex, and frequent challenges to the safety system occur which impact on their trustworthiness. Advances in nuclear reactor design, computer sciences, and control theory, and in related technological areas such as electronics and communications as well as in data storage, retrieval, display, and analysis have opened a promise for control systems with more acceptable human brain-like capabilities to pursue the required goals. This paper elaborates on the promise of futuristic nuclear power plants with intelligent control systems and addresses design requirements and implementation approaches

  2. Intelligent control of dynamic LED lighting; Intelligent styring af dynamisk LED belysning. Slutrapport

    Energy Technology Data Exchange (ETDEWEB)

    Thorseth, A.; Corell, D.; Hansen, Soeren S.; Dam-Hansen, C.; Petersen, Paul Michael

    2013-01-15

    The project has resulted in a prototype of a new intelligent lighting control system. The control system enables the end user to control his or her own local lighting environment (lighting zone) according to individual preferences and needs. The report provides a description of how the developed intelligent lighting system is composed and functions. The system is designed as a work lamp that enables dynamic change of the light color scheme according to a number of light control algorithms. It is specifically designed in relation to user tests of the intelligent lighting system, which is carried out in the final part of the project. An intelligent and advanced control of LED lighting was developed, which enables optimization of the user's light conditions in a given situation. Based on a number of known parameters, the system can control lighting so that at any time optimal light conditions are created, using a minimum of electric power. (LN)

  3. Applying Artificial Intelligence and Internet Techniques in Rural Tourism Domain

    OpenAIRE

    Turcu, Cristina; Turcu, Cornel

    2017-01-01

    Society has become more dependent on automated intelligent systems, at the same time, these systems have become more and more complicated. Society's expectation regarding the capabilities and intelligence of such systems has also grown. We have become a more complicated society with more complicated problems. As the expectation of intelligent systems rises, we discover many more applications for artificial intelligence. Additionally, as the difficulty level and computational requirements of s...

  4. Computer Aided Automatic Control - CAAC artificial intelligence block

    Energy Technology Data Exchange (ETDEWEB)

    Balate, J.; Chramcov, B.; Princ, M. [Brno Univ. of Technology (Czech Republic). Faculty of Technology in Zlin

    2000-07-01

    The aim of the plan to build up the system CAAC - Computer Aided Automatic Control is to create modular setup of partial computing programs including theory of automatic control, algorithms of programs for processing signals and programs of control algorithms. To approach its informative contents to students and professional public the CAAC system utilizes Internet services http in the form of WWW pages. The CAAC system is being processed at the Institute of Automation and Control Technique of the Faculty of Technology in Zlin of the Brno University of Technology and is determined particularly for pedagogic purposes. Recently also the methods of artificial intelligence have been included to the open CAAC system and that is comprised in this article. (orig.)

  5. Intelligent system for improving dosage control

    Directory of Open Access Journals (Sweden)

    Fabio Cosme Rodrigues dos Santos

    2017-02-01

    Full Text Available Coagulation is one of the most important processes in a drinking-water treatment plant, and it is applied to destabilize impurities in water for the subsequent flocculation stage. Several techniques are currently used in the water industry to determine the best dosage of the coagulant, such as the jar-test method, zeta potential measurements, artificial intelligence methods, comprising neural networks, fuzzy and expert systems, and the combination of the above-mentioned techniques to help operators and engineers in the water treatment process. Current paper presents an artificial neural network approach to evaluate optimum coagulant dosage for various scenarios in raw water quality, using parameters such as raw water color, raw water turbidity, clarified and filtered water turbidity and a calculated Dose Rate to provide the best performance in the filtration process. Another feature in current approach is the use of a backpropagation neural network method to estimate the best coagulant dosage simultaneously at two points of the water treatment plant. Simulation results were compared to the current dosage rate and showed that the proposed system may reduce costs of raw material in water treatment plant.

  6. Intelligent distributed control for nuclear power plants

    International Nuclear Information System (INIS)

    Klevans, E.H.; Edwards, R.M.; Ray, A.; Lee, K.Y.; Garcia, H.E.: Chavez, C.M.; Turso, J.A.; BenAbdennour, A.

    1991-01-01

    In September of 1989 work began on the DOE University Program grant DE-FG07-89ER12889. The grant provides support for a three year project to develop and demonstrate Intelligent Distributed Control (IDC) for Nuclear Power Plants. The body of this Second Annual Technical Progress report covers the period from September 1990 to September 1991. It summarizes the second year accomplishments while the appendices provide detailed information presented at conference meetings. These are two primary goals of this research. The first is to combine diagnostics and control to achieve a highly automated power plant as described by M.A. Schultz, a project consultant during the first year of the project. This philosophy, as presented in the first annual technical progress report, is to improve public perception of the safety of nuclear power plants by incorporating a high degree automation where greatly simplified operator control console minimizes the possibility of human error in power plant operations. A hierarchically distributed control system with automated responses to plant upset conditions is the focus of our research to achieve this goal. The second goal is to apply this research to develop a prototype demonstration on an actual power plant system, the EBR-II steam plant

  7. 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.

  8. Intelligent computational control of multi-fingered dexterous robotic hand

    OpenAIRE

    Chen, Disi; Li, Gongfa; Jiang, Guozhang; Fang, Yinfeng; Ju, Zhaojie; Liu, Honghai

    2015-01-01

    We discuss the intelligent computational control theory and introduce the hardware structure of HIT/DLR II dexterous robotic hand, which is the typical dexterous robotic hand. We show that how DSP or FPGA controller can be used in the dexterous robotic hand. A popular intelligent dexterous robotic hand control system, which named Electromyography (EMG) control is investigated. We introduced some mathematical algorithms in EMG controlling, such as Gauss mixture model (GMM), artificial neural n...

  9. Hybrid intelligent control concepts for optimal data fusion

    Science.gov (United States)

    Llinas, James

    1994-02-01

    In the post-Cold War era, Naval surface ship operations will be largely conducted in littoral waters to support regional military missions of all types, including humanitarian and evacuation activities, and amphibious mission execution. Under these conditions, surface ships will be much more isolated and vulnerable to a variety of threats, including maneuvering antiship missiles. To deal with these threats, the optimal employment of multiple shipborne sensors for maximum vigilance is paramount. This paper characterizes the sensor management problem as one of intelligent control, identifies some of the key issues in controller design, and presents one approach to controller design which is soon to be implemented and evaluated. It is argued that the complexity and hierarchical nature of problem formulation demands a hybrid combination of knowledge-based methods and scheduling techniques from 'hard' real-time systems theory for its solution.

  10. TOWARDS MEASURES OF INTELLIGENCE BASED ON SEMIOTIC CONTROL

    Energy Technology Data Exchange (ETDEWEB)

    C. JOSLYN

    2000-08-01

    We address the question of how to identify and measure the degree of intelligence in systems. We define the presence of intelligence as equivalent to the presence of a control relation. We contrast the distinct atomic semioic definitions of models and controls, and discuss hierarchical and anticipatory control. We conclude with a suggestion about moving towards quantitative measures of the degree of such control in systems.

  11. Integrating adjustable autonomy in an intelligent control framework

    Science.gov (United States)

    DeKoven, Elyon A. M.; Wood, Scott D.

    2005-10-01

    Currently, multiple humans are needed to operate a single uninhabited aerial vehicle (UAV). In the near future, combat techniques will involve single operators controlling multiple uninhabited ground and air vehicles. This situation creates both technological hurdles as well as interaction design challenges that must be addressed to support future fighters. In particular, the system will need to negotiate with the operator about proper task delegation, keeping the operator appropriately apprised of autonomous actions. This in turn implies that the system must know what the user is doing, what needs to be done in the present situation, and the comparative strengths for of the human and the system in each task. Towards building such systems, we are working on an Intelligent Control Framework (ICF) that provides a layer of intelligence to support future warfighters in complex task environments. The present paper presents the Adjustable Autonomy Module (AAM) in ICF. The AAM encapsulates some capabilities for user plan recognition, situation reasoning, and authority delegation control. The AAM has the knowledge necessary to support operator-system dialogue about autonomy changes, and it also provides the system with the ability to act on this knowledge. Combined with careful interaction design, planning and plan-execution capabilities, the AAM enables future design and development of effective human-robot teams.

  12. Intelligent control and cooperation for mobile robots

    Science.gov (United States)

    Stingu, Petru Emanuel

    The topic discussed in this work addresses the current research being conducted at the Automation & Robotics Research Institute in the areas of UAV quadrotor control and heterogenous multi-vehicle cooperation. Autonomy can be successfully achieved by a robot under the following conditions: the robot has to be able to acquire knowledge about the environment and itself, and it also has to be able to reason under uncertainty. The control system must react quickly to immediate challenges, but also has to slowly adapt and improve based on accumulated knowledge. The major contribution of this work is the transfer of the ADP algorithms from the purely theoretical environment to the complex real-world robotic platforms that work in real-time and in uncontrolled environments. Many solutions are adopted from those present in nature because they have been proven to be close to optimal in very different settings. For the control of a single platform, reinforcement learning algorithms are used to design suboptimal controllers for a class of complex systems that can be conceptually split in local loops with simpler dynamics and relatively weak coupling to the rest of the system. Optimality is enforced by having a global critic but the curse of dimensionality is avoided by using local actors and intelligent pre-processing of the information used for learning the optimal controllers. The system model is used for constructing the structure of the control system, but on top of that the adaptive neural networks that form the actors use the knowledge acquired during normal operation to get closer to optimal control. In real-world experiments, efficient learning is a strong requirement for success. This is accomplished by using an approximation of the system model to focus the learning for equivalent configurations of the state space. Due to the availability of only local data for training, neural networks with local activation functions are implemented. For the control of a formation

  13. Artificial Intelligence Techniques for Predicting and Mapping Daily Pan Evaporation

    Science.gov (United States)

    Arunkumar, R.; Jothiprakash, V.; Sharma, Kirty

    2017-09-01

    In this study, Artificial Intelligence techniques such as Artificial Neural Network (ANN), Model Tree (MT) and Genetic Programming (GP) are used to develop daily pan evaporation time-series (TS) prediction and cause-effect (CE) mapping models. Ten years of observed daily meteorological data such as maximum temperature, minimum temperature, relative humidity, sunshine hours, dew point temperature and pan evaporation are used for developing the models. For each technique, several models are developed by changing the number of inputs and other model parameters. The performance of each model is evaluated using standard statistical measures such as Mean Square Error, Mean Absolute Error, Normalized Mean Square Error and correlation coefficient (R). The results showed that daily TS-GP (4) model predicted better with a correlation coefficient of 0.959 than other TS models. Among various CE models, CE-ANN (6-10-1) resulted better than MT and GP models with a correlation coefficient of 0.881. Because of the complex non-linear inter-relationship among various meteorological variables, CE mapping models could not achieve the performance of TS models. From this study, it was found that GP performs better for recognizing single pattern (time series modelling), whereas ANN is better for modelling multiple patterns (cause-effect modelling) in the data.

  14. Inter-cooperative collective intelligence techniques and applications

    CERN Document Server

    Bessis, Nik

    2014-01-01

    This book covers the latest advances in the rapid growing field of inter-cooperative collective intelligence aiming the integration and cooperation of various computational resources, networks and intelligent processing paradigms to collectively build intelligence and advanced decision support and interfaces for end-users. The book brings a comprehensive view of the state-of-the-art in the field of integration of sensor networks, IoT and Cloud computing, massive and intelligent querying and processing of data. As a result, the book presents lessons learned so far and identifies new research issues, challenges and opportunities for further research and development agendas. Emerging areas of applications are also identified and usefulness of inter-cooperative collective intelligence is envisaged.   Researchers, software developers, practitioners and students interested in the field of inter-cooperative collective intelligence will find the comprehensive coverage of this book useful for their research, academic...

  15. State and data techniques for control of discontinuous systems

    International Nuclear Information System (INIS)

    Kisner, R.A.

    1986-01-01

    The need for automated control systems becomes clear as the complexity of nuclear power plants increases and economic incentives demand higher plant availability. A control system with intelligence distributed throughout its controllers allows reduction in operator workload, perhaps reduction in crew size, and potentially a reduction in on-line human error. In automated systems of this kind, each controller should be capable of making decisions and carrying out a plan of action. 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 I design (basic automatic control action), in which no maintenance, testing, or contingency capability is attempted

  16. Utilization of artificial intelligence techniques for the Space Station power system

    Science.gov (United States)

    Evatt, Thomas C.; Gholdston, Edward W.

    1988-01-01

    Due to the complexity of the Space Station Electrical Power System (EPS) as currently envisioned, artificial intelligence/expert system techniques are being investigated to automate operations, maintenance, and diagnostic functions. A study was conducted to investigate this technology as it applies to failure detection, isolation, and reconfiguration (FDIR) and health monitoring of power system components and of the total system. Control system utilization of expert systems for load scheduling and shedding operations was also researched. A discussion of the utilization of artificial intelligence/expert systems for Initial Operating Capability (IOC) for the Space Station effort is presented along with future plans at Rocketdyne for the utilization of this technology for enhanced Space Station power capability.

  17. A framework for the intelligent control of nuclear rockets

    International Nuclear Information System (INIS)

    Parlos, A.G.; Metzger, J.D.

    1993-01-01

    An intelligent control system architecture is proposed for nuclear rockets, and its various components are briefly described. The objective of the intelligent controller is the satisfaction of performance, robustness, fault-tolerance and reliability design specifications. The proposed hierarchical architecture consists of three levels: hardware, signal processing, and knowledge processing. The functionality of the intelligent controller is implemented utilizing advanced information processing technologies such as artificial neutral networks and fuzzy expert systems. The feasibility of a number of the controller architecture components have been independently validated using computer simulations. Preliminary results are presented demonstrating some of the signal processing capabilities of the intelligent nuclear rocket controller. Further work, currently in progress, is attempting to implement a number of the knowledge processing capabilities of the controller and their interface with the lower levels of the proposed architecture

  18. Intelligent Transportation Control based on Proactive Complex Event Processing

    Directory of Open Access Journals (Sweden)

    Wang Yongheng

    2016-01-01

    Full Text Available Complex Event Processing (CEP has become the key part of Internet of Things (IoT. Proactive CEP can predict future system states and execute some actions to avoid unwanted states which brings new hope to intelligent transportation control. In this paper, we propose a proactive CEP architecture and method for intelligent transportation control. Based on basic CEP technology and predictive analytic technology, a networked distributed Markov decision processes model with predicting states is proposed as sequential decision model. A Q-learning method is proposed for this model. The experimental evaluations show that this method works well when used to control congestion in in intelligent transportation systems.

  19. Adaptive Intelligent Ventilation Noise Control, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — To address the NASA need for quiet on-orbit crew quarters (CQ), Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...

  20. Adaptive Intelligent Ventilation Noise Control, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — To address NASA needs for quiet crew volumes in a space habitat, Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...

  1. Computational intelligence applications in modeling and control

    CERN Document Server

    Vaidyanathan, Sundarapandian

    2015-01-01

    The development of computational intelligence (CI) systems was inspired by observable and imitable aspects of intelligent activity of human being and nature. The essence of the systems based on computational intelligence is to process and interpret data of various nature so that that CI is strictly connected with the increase of available data as well as capabilities of their processing, mutually supportive factors. Developed theories of computational intelligence were quickly applied in many fields of engineering, data analysis, forecasting, biomedicine and others. They are used in images and sounds processing and identifying, signals processing, multidimensional data visualization, steering of objects, analysis of lexicographic data, requesting systems in banking, diagnostic systems, expert systems and many other practical implementations. This book consists of 16 contributed chapters by subject experts who are specialized in the various topics addressed in this book. The special chapters have been brought ...

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

    International Nuclear Information System (INIS)

    Lhuillier, C.; Malvache, P.

    1987-01-01

    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

  3. 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

  4. Crack identification based on synthetic artificial intelligent technique

    International Nuclear Information System (INIS)

    Shim, Mun Bo; Suh, Myung Won

    2001-01-01

    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

  5. Macrocell path loss prediction using artificial intelligence techniques

    Science.gov (United States)

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

    2014-04-01

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

  6. Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

    Energy Technology Data Exchange (ETDEWEB)

    Zarzalejo, L.F.; Ramirez, L.; Polo, J. [DER-CIEMAT, Madrid (Spain). Renewable Energy Dept.

    2005-07-01

    Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models. (author)

  7. Artificial intelligence techniques applied to hourly global irradiance estimation from satellite-derived cloud index

    International Nuclear Information System (INIS)

    Zarzalejo, Luis F.; Ramirez, Lourdes; Polo, Jesus

    2005-01-01

    Artificial intelligence techniques, such as fuzzy logic and neural networks, have been used for estimating hourly global radiation from satellite images. The models have been fitted to measured global irradiance data from 15 Spanish terrestrial stations. Both satellite imaging data and terrestrial information from the years 1994, 1995 and 1996 were used. The results of these artificial intelligence models were compared to a multivariate regression based upon Heliosat I model. A general better behaviour was observed for the artificial intelligence models

  8. Intelligent Predictive Control of Nonlienar Processes Using

    DEFF Research Database (Denmark)

    Nørgård, Peter Magnus; Sørensen, Paul Haase; Poulsen, Niels Kjølstad

    1996-01-01

    This paper presents a novel approach to design of generalized predictive controllers (GPC) for nonlinear processes. A neural network is used for modelling the process and a gain-scheduling type of GPC is subsequently designed. The combination of neural network models and predictive control has...... frequently been discussed in the neural network community. This paper proposes an approximate scheme, the approximate predictive control (APC), which facilitates the implementation and gives a substantial reduction in the required amount of computations. The method is based on a technique for extracting...... linear models from a nonlinear neural network and using them in designing the control system. The performance of the controller is demonstrated in a simulation study of a pneumatic servo system...

  9. Fixed Point Learning Based Intelligent Traffic Control System

    Science.gov (United States)

    Zongyao, Wang; Cong, Sui; Cheng, Shao

    2017-10-01

    Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

  10. Emotional intelligence and locus of control of adult patients with ...

    African Journals Online (AJOL)

    2011-03-15

    Mar 15, 2011 ... Keywords: breast cancer, treatment, positive psychology, emotional intelligence, locus of control ... branches are organised in a hierarchy with perception of ..... Asian. Development Bank Knowledge Solutions [serial online].

  11. INTELLIGENT AUTOMATED SYSTEM OF CONTROL OF KNOWLEDGE: LINGUISTIC SUBSYSTEM

    Directory of Open Access Journals (Sweden)

    I. Katerynchuk

    2010-08-01

    Full Text Available A flowchart linguistic structure (morfological, syntactical, semantic and pragmatic analysis of sentences of the automated system of control of intellectual knowledge. The model of artificial intelligence recognition and evaluation of textual answers.

  12. DESIGN AN INTELLIGENT CONTROLLER FOR FULL VEHICLE NONLINEAR ACTIVE SUSPENSION SYSTEMS

    OpenAIRE

    Aldair, A. A.; Wang, W. J.

    2011-01-01

    The main objective of designed the controller for a vehicle suspension system is to reduce the discomfort sensed by passengers which arises from road roughness and to increase the ride handling associated with the pitching and rolling movements. This necessitates a very fast and accurate controller to meet as much control objectives, as possible. Therefore, this paper deals with an artificial intelligence Neuro-Fuzzy (NF) technique to design a robust controller to meet the control objectives....

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

    International Nuclear Information System (INIS)

    Saini, K. K.; Saini, Sanju

    2008-01-01

    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.

  14. Intelligent Transportation Control based on Proactive Complex Event Processing

    OpenAIRE

    Wang Yongheng; Geng Shaofeng; Li Qian

    2016-01-01

    Complex Event Processing (CEP) has become the key part of Internet of Things (IoT). Proactive CEP can predict future system states and execute some actions to avoid unwanted states which brings new hope to intelligent transportation control. In this paper, we propose a proactive CEP architecture and method for intelligent transportation control. Based on basic CEP technology and predictive analytic technology, a networked distributed Markov decision processes model with predicting states is p...

  15. Intelligent supervision control for the VASPS separator

    Energy Technology Data Exchange (ETDEWEB)

    Melo, A.V.; Mendes, J.R.P. [Universidade Estadual de Campinas (UNICAMP), SP (Brazil)], E-mail: jricardo@dep.fem.unicamp.br; Serapiao, A.B.S [Universidade Estadual Paulista Julio de Mesquita Filho (UNESP), Rio Claro, SP (Brazil)

    2007-10-15

    The Vertical Annular Separation and Pumping System, VASPS, has been applied to low-pressure subsea wells with high gas production potential. In this system, the separation is carried out on the sea bed, thus allowing the monophase transmission through different pipelines. In the present work, an analysis has been established between two conceptually distinct models for the control system, which is under development and uses the Fuzzy Control technique for the Electrical Submersible Pump (ESP) speed selection. The contrast is held on the objective of each controller, placing the operational performance against the stability of the control signal, which leads to the exploration of many specific aspects of the system, its behavior and requirements. (author)

  16. SART: an intelligent assistant system for subway control

    Directory of Open Access Journals (Sweden)

    P. Brézillon

    2000-12-01

    Full Text Available One of the main characteristics of a subway line is its large transport capacity (e.g., about 60000 travelers per hour in the Parisian subway combined with a regular transport supply. The regularity is particularly important at rush time - peak hours - when an incident can provoke important delays. Experience shows that the consequences of an incident are highly dependent on the context in which the incident occurs (e.g., peak hours or not. The decisions taken by the operators are heavily relied on the incident context, and operators often make different decisions for the same incident in different contexts. The project SART (French acronym for Support system for traffic control aims at developing an intelligent decision support system able of helping the operator in making decisions to solve an incident occurring on a line. This system relies on the notion of context. Context includes information and knowledge on the situation that do not intervene directly in the incident solving, but constrain the way in which the operator will choose a strategy at each step of the incident solving. The paper describes the SART project and highlights how Artificial Intelligence (AI techniques can contributeto knowledge acquisition and knowledge representation associated with its context of use. Particularly we discuss the notion of context and show how we use this notion to solve a real-world problem.

  17. Use of artificial intelligence in supervisory control

    Science.gov (United States)

    Cohen, Aaron; Erickson, Jon D.

    1989-01-01

    Viewgraphs describing the design and testing of an intelligent decision support system called OFMspert are presented. In this expert system, knowledge about the human operator is represented through an operator/system model referred to as the OFM (Operator Function Model). OFMspert uses the blackboard model of problem solving to maintain a dynamic representation of operator goals, plans, tasks, and actions given previous operator actions and current system state. Results of an experiment to assess OFMspert's intent inferencing capability are outlined. Finally, the overall design philosophy for an intelligent tutoring system (OFMTutor) for operators of complex dynamic systems is summarized.

  18. Application of artificial intelligence in load frequency control of ...

    African Journals Online (AJOL)

    This paper presents the use of artificial intelligence to study the load frequency control of interconnected power system. In the proposed scheme, a control methodology is developed using Artificial Neural Network (ANN) and Fuzzy Logic controller (FLC) for interconnected hydro-thermal power system. The control strategies ...

  19. Intelligent on-line fault tolerant control for unanticipated catastrophic failures.

    Science.gov (United States)

    Yen, Gary G; Ho, Liang-Wei

    2004-10-01

    As dynamic systems become increasingly complex, experience rapidly changing environments, and encounter a greater variety of unexpected component failures, solving the control problems of such systems is a grand challenge for control engineers. Traditional control design techniques are not adequate to cope with these systems, which may suffer from unanticipated dynamic failures. In this research work, we investigate the on-line fault tolerant control problem and propose an intelligent on-line control strategy to handle the desired trajectories tracking problem for systems suffering from various unanticipated catastrophic faults. Through theoretical analysis, the sufficient condition of system stability has been derived and two different on-line control laws have been developed. The approach of the proposed intelligent control strategy is to continuously monitor the system performance and identify what the system's current state is by using a fault detection method based upon our best knowledge of the nominal system and nominal controller. Once a fault is detected, the proposed intelligent controller will adjust its control signal to compensate for the unknown system failure dynamics by using an artificial neural network as an on-line estimator to approximate the unexpected and unknown failure dynamics. The first control law is derived directly from the Lyapunov stability theory, while the second control law is derived based upon the discrete-time sliding mode control technique. Both control laws have been implemented in a variety of failure scenarios to validate the proposed intelligent control scheme. The simulation results, including a three-tank benchmark problem, comply with theoretical analysis and demonstrate a significant improvement in trajectory following performance based upon the proposed intelligent control strategy.

  20. Active vibration control by robust control techniques

    International Nuclear Information System (INIS)

    Lohar, F.A.

    2001-01-01

    This paper studies active vibration control of multi-degree-of-freedom system. The control techniques considered are LTR, H/sup 2/ and H/sup infinite/. The results show that LTR controls the vibration but its respective settling time is higher than that of the other techniques. The control performance of H/sup infinite/ control is similar to that of H/sup 2/ control in the case of it weighting functions. However, H/sup infinite/ control is superior to H/sup 2/ control with respect to robustness, steady state error and settling time. (author)

  1. Innovation in Active Vibration Control Strategy of Intelligent Structures

    Directory of Open Access Journals (Sweden)

    A. Moutsopoulou

    2014-01-01

    Full Text Available Large amplitudes and attenuating vibration periods result in fatigue, instability, and poor structural performance. In light of past approaches in this field, this paper intends to discuss some innovative approaches in vibration control of intelligent structures, particularly in the case of structures with embedded piezoelectric materials. Control strategies are presented, such as the linear quadratic control theory, as well as more advanced theories, such as robust control theory. The paper presents sufficiently a recognizable advance in knowledge of active vibration control in intelligent structures.

  2. Intelligent Home Control System Based on ARM10

    Science.gov (United States)

    Chen, G. X.; Jiang, J.; Zhong, L. H.

    2017-10-01

    Intelligent home is becoming the hot spot of social attention in the 21st century. When it is in China, it is a really new industry. However, there is no doubt that Intelligent home will become a new economic growth point of social development; it will change the life-style of human being. To develop the intelligent home, we should keep up with the development trend of technology. This is the reason why I talk about the intelligent home control system here. In this paper, intelligent home control system is designed for alarm and remote control on gas- leaking, fire disaster, earthquake prediction, etc., by examining environmental changes around house. When the Intelligent home control system has detected an accident occurs, the processor will communicate with the GSM module, informing the house keeper the occurrence of accident. User can receive and send the message to the system to cut the power by mobile phone. The system can get access to DCCthrough ARM10 JTAG interface, using DCC to send and receive messages. At the same time, the debugger on the host is mainly used to receive the user’s command and send it to the debug component in the target system. The data that returned from the target system is received and displayed to the user in a certain format.

  3. Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)

    Science.gov (United States)

    Niewoehner, Kevin R.; Carter, John (Technical Monitor)

    2001-01-01

    The research accomplishments for the cooperative agreement 'Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)' include the following: (1) previous IFC program data collection and analysis; (2) IFC program support site (configured IFC systems support network, configured Tornado/VxWorks OS development system, made Configuration and Documentation Management Systems Internet accessible); (3) Airborne Research Test Systems (ARTS) II Hardware (developed hardware requirements specification, developing environmental testing requirements, hardware design, and hardware design development); (4) ARTS II software development laboratory unit (procurement of lab style hardware, configured lab style hardware, and designed interface module equivalent to ARTS II faceplate); (5) program support documentation (developed software development plan, configuration management plan, and software verification and validation plan); (6) LWR algorithm analysis (performed timing and profiling on algorithm); (7) pre-trained neural network analysis; (8) Dynamic Cell Structures (DCS) Neural Network Analysis (performing timing and profiling on algorithm); and (9) conducted technical interchange and quarterly meetings to define IFC research goals.

  4. 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

  5. Intelligent control of mixed-culture bioprocesses

    International Nuclear Information System (INIS)

    Stoner, D.L.; Larsen, E.D.; Miller, K.S.

    1995-01-01

    A hierarchical control system is being developed and applied to a mixed culture bioprocess in a continuous stirred tank reactor. A bioreactor, with its inherent complexity and non-linear behavior was an interesting, yet, difficult application for control theory. The bottom level of the hierarchy was implemented as a number of integrated set point controls and data acquisition modules. Within the second level was a diagnostic system that used expert knowledge to determine the operational status of the sensors, actuators, and control modules. A diagnostic program was successfully implemented for the detection of stirrer malfunctions, and to monitor liquid delivery rates and recalibrate the pumps when deviations from desired flow rates occurred. The highest control level was a supervisory shell that was developed using expert knowledge and the history of the reactor operation to determine the set points required to meet a set of production criteria. At this stage the supervisory shell analyzed the data to determine the state of the system. In future implementations, this shell will determine the set points required to optimize a cost function using expert knowledge and adaptive learning techniques

  6. Intelligent control of mixed-culture bioprocesses

    Energy Technology Data Exchange (ETDEWEB)

    Stoner, D.L.; Larsen, E.D.; Miller, K.S. [Idaho National Engineering Lab., Idaho Falls, ID (United States)] [and others

    1995-12-31

    A hierarchical control system is being developed and applied to a mixed culture bioprocess in a continuous stirred tank reactor. A bioreactor, with its inherent complexity and non-linear behavior was an interesting, yet, difficult application for control theory. The bottom level of the hierarchy was implemented as a number of integrated set point controls and data acquisition modules. Within the second level was a diagnostic system that used expert knowledge to determine the operational status of the sensors, actuators, and control modules. A diagnostic program was successfully implemented for the detection of stirrer malfunctions, and to monitor liquid delivery rates and recalibrate the pumps when deviations from desired flow rates occurred. The highest control level was a supervisory shell that was developed using expert knowledge and the history of the reactor operation to determine the set points required to meet a set of production criteria. At this stage the supervisory shell analyzed the data to determine the state of the system. In future implementations, this shell will determine the set points required to optimize a cost function using expert knowledge and adaptive learning techniques.

  7. Intelligent Shutter Speech Control System Based on DSP

    Directory of Open Access Journals (Sweden)

    Yonghong Deng

    2017-01-01

    Full Text Available Based on TMS320F28035 DSP, this paper designed a smart shutters voice control system, which realized the functions of opening and closing shutters, intelligent switching of lighting mode and solar power supply through voice control. The traditional control mode is converted to voice control at the same time with automatic lighting and solar power supply function. In the convenience of people’s lives at the same time more satisfied with today’s people on the intelligent and environmental protection of the two concepts of the pursuit. The whole system is simple, low cost, safe and reliable.

  8. [An object-oriented intelligent engineering design approach for lake pollution control].

    Science.gov (United States)

    Zou, Rui; Zhou, Jing; Liu, Yong; Zhu, Xiang; Zhao, Lei; Yang, Ping-Jian; Guo, Huai-Cheng

    2013-03-01

    Regarding the shortage and deficiency of traditional lake pollution control engineering techniques, a new lake pollution control engineering approach was proposed in this study, based on object-oriented intelligent design (OOID) from the perspective of intelligence. It can provide a new methodology and framework for effectively controlling lake pollution and improving water quality. The differences between the traditional engineering techniques and the OOID approach were compared. The key points for OOID were described as object perspective, cause and effect foundation, set points into surface, and temporal and spatial optimization. The blue algae control in lake was taken as an example in this study. The effect of algae control and water quality improvement were analyzed in details from the perspective of object-oriented intelligent design based on two engineering techniques (vertical hydrodynamic mixer and pumping algaecide recharge). The modeling results showed that the traditional engineering design paradigm cannot provide scientific and effective guidance for engineering design and decision-making regarding lake pollution. Intelligent design approach is based on the object perspective and quantitative causal analysis in this case. This approach identified that the efficiency of mixers was much higher than pumps in achieving the goal of low to moderate water quality improvement. However, when the objective of water quality exceeded a certain value (such as the control objective of peak Chla concentration exceeded 100 microg x L(-1) in this experimental water), the mixer cannot achieve this goal. The pump technique can achieve the goal but with higher cost. The efficiency of combining the two techniques was higher than using one of the two techniques alone. Moreover, the quantitative scale control of the two engineering techniques has a significant impact on the actual project benefits and costs.

  9. Design optimum frac jobs using virtual intelligence techniques

    Science.gov (United States)

    Mohaghegh, Shahab; Popa, Andrei; Ameri, Sam

    2000-10-01

    Designing optimal frac jobs is a complex and time-consuming process. It usually involves the use of a two- or three-dimensional computer model. For the computer models to perform as intended, a wealth of input data is required. The input data includes wellbore configuration and reservoir characteristics such as porosity, permeability, stress and thickness profiles of the pay layers as well as the overburden layers. Among other essential information required for the design process is fracturing fluid type and volume, proppant type and volume, injection rate, proppant concentration and frac job schedule. Some of the parameters such as fluid and proppant types have discrete possible choices. Other parameters such as fluid and proppant volume, on the other hand, assume values from within a range of minimum and maximum values. A potential frac design for a particular pay zone is a combination of all of these parameters. Finding the optimum combination is not a trivial process. It usually requires an experienced engineer and a considerable amount of time to tune the parameters in order to achieve desirable outcome. This paper introduces a new methodology that integrates two virtual intelligence techniques, namely, artificial neural networks and genetic algorithms to automate and simplify the optimum frac job design process. This methodology requires little input from the engineer beyond the reservoir characterizations and wellbore configuration. The software tool that has been developed based on this methodology uses the reservoir characteristics and an optimization criteria indicated by the engineer, for example a certain propped frac length, and provides the detail of the optimum frac design that will result in the specified criteria. An ensemble of neural networks is trained to mimic the two- or three-dimensional frac simulator. Once successfully trained, these networks are capable of providing instantaneous results in response to any set of input parameters. These

  10. Design optimum frac jobs using virtual intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Shahab Mohaghegh; Andrei Popa; Sam Ameri [West Virginia University, Morgantown, WV (United States). Petroleum and Natural Gas Engineering

    2000-10-01

    Designing optimal frac jobs is a complex and time-consuming process. It usually involves the use of a two- or three-dimensional computer model. For the computer models to perform as intended, a wealth of input data is required. The input data includes wellbore configuration and reservoir characteristics such as porosity, permeability, stress and thickness profiles of the pay layers as well as the overburden layers. Among other essential information required for the design process is fracturing fluid type and volume, proppant type and volume, injection rate, proppant concentration and frac job schedule. Some of the parameters such as fluid and proppant types have discrete possible choices. Other parameters such as fluid and proppant volume, on the other hand, assume values from within a range of minimum and maximum values. A potential frac design for a particular pay zone is a combination of all of these parameters. Finding the optimum combination is not a trivial process. It usually requires an experienced engineer and a considerable amount of time to tune the parameters in order to achieve desirable outcome. This paper introduces a new methodology that integrates two virtual intelligence techniques, namely, artificial neural networks and genetic algorithms to automate and simplify the optimum frac job design process. This methodology requires little input from the engineer beyond the reservoir characterizations and wellbore configuration. The software tool that has been developed based on this methodology uses the reservoir characteristics and an optimization criteria indicated by the engineer, for example a certain propped frac length, and provides the detail of the optimum frac design that will result in the specified criteria. An ensemble of neural networks is trained to mimic the two- or three-dimensional frac simulator. Once successfully trained, these networks are capable of providing instantaneous results in response to any set of input parameters. These

  11. Hacking web intelligence open source intelligence and web reconnaissance concepts and techniques

    CERN Document Server

    Chauhan, Sudhanshu

    2015-01-01

    Open source intelligence (OSINT) and web reconnaissance are rich topics for infosec professionals looking for the best ways to sift through the abundance of information widely available online. In many cases, the first stage of any security assessment-that is, reconnaissance-is not given enough attention by security professionals, hackers, and penetration testers. Often, the information openly present is as critical as the confidential data. Hacking Web Intelligence shows you how to dig into the Web and uncover the information many don't even know exists. The book takes a holistic approach

  12. Flight Test of an Intelligent Flight-Control System

    Science.gov (United States)

    Davidson, Ron; Bosworth, John T.; Jacobson, Steven R.; Thomson, Michael Pl; Jorgensen, Charles C.

    2003-01-01

    The F-15 Advanced Controls Technology for Integrated Vehicles (ACTIVE) airplane (see figure) was the test bed for a flight test of an intelligent flight control system (IFCS). This IFCS utilizes a neural network to determine critical stability and control derivatives for a control law, the real-time gains of which are computed by an algorithm that solves the Riccati equation. These derivatives are also used to identify the parameters of a dynamic model of the airplane. The model is used in a model-following portion of the control law, in order to provide specific vehicle handling characteristics. The flight test of the IFCS marks the initiation of the Intelligent Flight Control System Advanced Concept Program (IFCS ACP), which is a collaboration between NASA and Boeing Phantom Works. The goals of the IFCS ACP are to (1) develop the concept of a flight-control system that uses neural-network technology to identify aircraft characteristics to provide optimal aircraft performance, (2) develop a self-training neural network to update estimates of aircraft properties in flight, and (3) demonstrate the aforementioned concepts on the F-15 ACTIVE airplane in flight. The activities of the initial IFCS ACP were divided into three Phases, each devoted to the attainment of a different objective. The objective of Phase I was to develop a pre-trained neural network to store and recall the wind-tunnel-based stability and control derivatives of the vehicle. The objective of Phase II was to develop a neural network that can learn how to adjust the stability and control derivatives to account for failures or modeling deficiencies. The objective of Phase III was to develop a flight control system that uses the neural network outputs as a basis for controlling the aircraft. The flight test of the IFCS was performed in stages. In the first stage, the Phase I version of the pre-trained neural network was flown in a passive mode. The neural network software was running using flight data

  13. Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation through the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The applications of several different types of AI techniques for flight are explored during this research effort. The research concentration is directed to the application of different AI methods within the UAV arena. By evaluating AI and biological system approaches. which include Expert Systems, Neural Networks. Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI and CAS techniques applied to achieving true autonomous operation of these systems. Although flight systems were explored, the benefits should apply to many Unmanned Vehicles such as: Rovers. Ocean Explorers, Robots, and autonomous operation systems. A portion of the flight system is broken down into control agents that represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework for applying an intelligent agent is presented. The initial results from simulation of a security agent for communication are presented.

  14. Controls and Health Management Technologies for Intelligent Aerospace Propulsion Systems

    Science.gov (United States)

    Garg, Sanjay

    2004-01-01

    With the increased emphasis on aircraft safety, enhanced performance and affordability, and the need to reduce the environmental impact of aircraft, there are many new challenges being faced by the designers of aircraft propulsion systems. The Controls and Dynamics Technology Branch at NASA (National Aeronautics and Space Administration) Glenn Research Center (GRC) in Cleveland, Ohio, is leading and participating in various projects in partnership with other organizations within GRC and across NASA, the U.S. aerospace industry, and academia to develop advanced controls and health management technologies that will help meet these challenges through the concept of an Intelligent Engine. The key enabling technologies for an Intelligent Engine are the increased efficiencies of components through active control, advanced diagnostics and prognostics integrated with intelligent engine control to enhance component life, and distributed control with smart sensors and actuators in an adaptive fault tolerant architecture. This paper describes the current activities of the Controls and Dynamics Technology Branch in the areas of active component control and propulsion system intelligent control, and presents some recent analytical and experimental results in these areas.

  15. Seismic activity prediction using computational intelligence techniques in northern Pakistan

    Science.gov (United States)

    Asim, Khawaja M.; Awais, Muhammad; Martínez-Álvarez, F.; Iqbal, Talat

    2017-10-01

    Earthquake prediction study is carried out for the region of northern Pakistan. The prediction methodology includes interdisciplinary interaction of seismology and computational intelligence. Eight seismic parameters are computed based upon the past earthquakes. Predictive ability of these eight seismic parameters is evaluated in terms of information gain, which leads to the selection of six parameters to be used in prediction. Multiple computationally intelligent models have been developed for earthquake prediction using selected seismic parameters. These models include feed-forward neural network, recurrent neural network, random forest, multi layer perceptron, radial basis neural network, and support vector machine. The performance of every prediction model is evaluated and McNemar's statistical test is applied to observe the statistical significance of computational methodologies. Feed-forward neural network shows statistically significant predictions along with accuracy of 75% and positive predictive value of 78% in context of northern Pakistan.

  16. Artificial Intelligence Techniques Applications for Power Disturbances Classification

    OpenAIRE

    K.Manimala; Dr.K.Selvi; R.Ahila

    2008-01-01

    Artificial Intelligence (AI) methods are increasingly being used for problem solving. This paper concerns using AI-type learning machines for power quality problem, which is a problem of general interest to power system to provide quality power to all appliances. Electrical power of good quality is essential for proper operation of electronic equipments such as computers and PLCs. Malfunction of such equipment may lead to loss of production or disruption of critical services resulting in huge...

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

    Science.gov (United States)

    1983-06-06

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

  18. Intelligent control of HVAC systems. Part II: perceptron performance analysis

    Directory of Open Access Journals (Sweden)

    Ioan URSU

    2013-09-01

    Full Text Available This is the second part of a paper on intelligent type control of Heating, Ventilating, and Air-Conditioning (HVAC systems. The whole study proposes a unified approach in the design of intelligent control for such systems, to ensure high energy efficiency and air quality improving. In the first part of the study it is considered as benchmark system a single thermal space HVAC system, for which it is assigned a mathematical model of the controlled system and a mathematical model(algorithm of intelligent control synthesis. The conception of the intelligent control is of switching type, between a simple neural network, a perceptron, which aims to decrease (optimize a cost index,and a fuzzy logic component, having supervisory antisaturating role for neuro-control. Based on numerical simulations, this Part II focuses on the analysis of system operation in the presence only ofthe neural control component. Working of the entire neuro-fuzzy system will be reported in a third part of the study.

  19. Tokamak impurity-control techniques

    International Nuclear Information System (INIS)

    Schmidt, J.A.

    1980-01-01

    A brief review is given of the impurity-control functions in tokamaks, their relative merits and disadvantages and some prominent edge-interaction-control techniques, and there is a discussion of a new proposal, the particle scraper, and its potential advantages. (author)

  20. The Role of Intelligence Quotient and Emotional Intelligence in Cognitive Control Processes

    Science.gov (United States)

    Checa, Purificación; Fernández-Berrocal, Pablo

    2015-01-01

    The relationship between intelligence quotient (IQ) and cognitive control processes has been extensively established. Several studies have shown that IQ correlates with cognitive control abilities, such as interference suppression, as measured with experimental tasks like the Stroop and Flanker tasks. By contrast, there is a debate about the role of Emotional Intelligence (EI) in individuals' cognitive control abilities. The aim of this study is to examine the relation between IQ and EI, and cognitive control abilities evaluated by a typical laboratory control cognitive task, the Stroop task. Results show a negative correlation between IQ and the interference suppression index, the ability to inhibit processing of irrelevant information. However, the Managing Emotions dimension of EI measured by the Mayer-Salovey-Caruso Emotional Intelligence Test (MSCEIT), but not self-reported of EI, negatively correlates with the impulsivity index, the premature execution of the response. These results suggest that not only is IQ crucial, but also competences related to EI are essential to human cognitive control processes. Limitations and implications of these results are also discussed. PMID:26648901

  1. The role of Intelligence Quotient and Emotional Intelligence in cognitive control processes

    Directory of Open Access Journals (Sweden)

    Purificación eCheca

    2015-12-01

    Full Text Available The relationship between intelligence quotient (IQ and cognitive control processes has been extensively established. Several studies have shown that IQ correlates with cognitive control abilities, such as interference suppression, as measured with experimental tasks like the Stroop and Flanker tasks. By contrast, there is a debate about the role of Emotional Intelligence (EI in individuals’ cognitive control abilities. The aim of this study is to examine the relation between IQ and EI, and cognitive control abilities evaluated by a typical laboratory control cognitive task, the Stroop task. Results show a negative correlation between IQ and the interference suppression index, the ability to inhibit processing of irrelevant information. However, the Managing Emotions dimension of EI measured by the Mayer-Salovey-Caruso Emotional Intelligence Test, but not self-reported of EI, negatively correlates with the impulsivity index, the premature execution of the response. These results suggest that not only is IQ crucial, but also competences related to EI are essential to human cognitive control processes. Limitations and implications of these results are also discussed

  2. [Control of intelligent car based on electroencephalogram and neurofeedback].

    Science.gov (United States)

    Li, Song; Xiong, Xin; Fu, Yunfa

    2018-02-01

    To improve the performance of brain-controlled intelligent car based on motor imagery (MI), a method based on neurofeedback (NF) with electroencephalogram (EEG) for controlling intelligent car is proposed. A mental strategy of MI in which the energy column diagram of EEG features related to the mental activity is presented to subjects with visual feedback in real time to train them to quickly master the skills of MI and regulate their EEG activity, and combination of multi-features fusion of MI and multi-classifiers decision were used to control the intelligent car online. The average, maximum and minimum accuracy of identifying instructions achieved by the trained group (trained by the designed feedback system before the experiment) were 85.71%, 90.47% and 76.19%, respectively and the corresponding accuracy achieved by the control group (untrained) were 73.32%, 80.95% and 66.67%, respectively. For the trained group, the average, longest and shortest time consuming were 92 s, 101 s, and 85 s, respectively, while for the control group the corresponding time were 115.7 s, 120 s, and 110 s, respectively. According to the results described above, it is expected that this study may provide a new idea for the follow-up development of brain-controlled intelligent robot by the neurofeedback with EEG related to MI.

  3. Active Detection for Exposing Intelligent Attacks in Control Systems

    Energy Technology Data Exchange (ETDEWEB)

    Weerakkody, Sean [Carnegie Mellon Univ., Pittsburgh, PA (United States); Ozel, Omur [Carnegie Mellon Univ., Pittsburgh, PA (United States); Griffioen, Paul [Carnegie Mellon Univ., Pittsburgh, PA (United States); Sinopoli, Bruno [Carnegie Mellon Univ., Pittsburgh, PA (United States)

    2017-07-01

    In this paper, we consider approaches for detecting integrity attacks carried out by intelligent and resourceful adversaries in control systems. Passive detection techniques are often incorporated to identify malicious behavior. Here, the defender utilizes finely-tuned algorithms to process information and make a binary decision, whether the system is healthy or under attack. We demonstrate that passive detection can be ineffective against adversaries with model knowledge and access to a set of input/output channels. We then propose active detection as a tool to detect attacks. In active detection, the defender leverages degrees of freedom he has in the system to detect the adversary. Specifically, the defender will introduce a physical secret kept hidden from the adversary, which can be utilized to authenticate the dynamics. In this regard, we carefully review two approaches for active detection: physical watermarking at the control input, and a moving target approach for generating system dynamics. We examine practical considerations for implementing these technologies and discuss future research directions.

  4. Intelligent color recognition system using micro-controller

    International Nuclear Information System (INIS)

    Mohd Ashhar Khalid; Khairiah Yazid; Nur Aira Abd Rahman; Azaman Ahmad

    2006-01-01

    Color is widely used in categorizing the quality of products as well as a marker for automatic selection and discrimination of products. Most of color recognizing process is done manually and due to the fact that human perceived color differently, different of opinion frequently occur. This paper deals with the development of an intelligent color recognition system used for discriminating the ripeness of oil palm fruits into three categories namely ripe, under-ripe and un-ripe. In deciding the categories of fruit a sample belong, a technique of decision making similar to human thinking called neural network has been implemented. Implementation of neural network using a micro-controller is not so common, due to a limited capability in floating point calculation. To overcome the problem, a floating-point co-processor specially designed for micro-controller is used. The paper will report the system design and the network training and implementation methods. The effectiveness of the system compared to human decision method is also reported. (Author)

  5. Intelligent energy efficiency control in hospitals

    Energy Technology Data Exchange (ETDEWEB)

    Nykaenen, E., Email: esa.nykanen@vtt.fi

    2012-06-15

    The concern of European society for the well-being of its residents and the sustainability of the environment has led to the consciousness that energy savings need to be at the top of the political agenda. Until recently, the focus of energy reduction has been on schools and offices. Hospitals, however, also use large amounts of energy. Therefore, the project will address specifically the hospital domain. HosPilot will address the two main technology areas Lighting and HVAC (Heating, Ventilation and Air Conditioning), thus covering the largest part of the energy-consuming areas. By adding intelligence, ICT (Information and Communication Technology) will play a vital role to achieve significant energy reduction in the complex environment of a hospital. (orig.)

  6. Personality disorder, emotional intelligence, and locus of control of patients with alcohol dependence

    OpenAIRE

    Prakash, Om; Sharma, Neelu; Singh, Amool R.; Sengar, K. S.; Chaudhury, Suprakash; Ranjan, Jay Kumar

    2015-01-01

    Aim: To assess personality disorder (PD), emotional intelligence (EI), and locus of control of alcohol dependent (AD) patients and its comparison with normal controls. Materials and Methods: Based on purposive sampling technique, 33 AD patients were selected from the De-Addiction Ward of Ranchi Institute of Neuro-Psychiatry and Allied Sciences (RINPAS) and 33 matched normal subjects were selected from Ranchi and nearby places. Both the groups were matched on various sociodemographic parameter...

  7. Multi-intelligence critical rating assessment of fusion techniques (MiCRAFT)

    Science.gov (United States)

    Blasch, Erik

    2015-06-01

    Assessment of multi-intelligence fusion techniques includes credibility of algorithm performance, quality of results against mission needs, and usability in a work-domain context. Situation awareness (SAW) brings together low-level information fusion (tracking and identification), high-level information fusion (threat and scenario-based assessment), and information fusion level 5 user refinement (physical, cognitive, and information tasks). To measure SAW, we discuss the SAGAT (Situational Awareness Global Assessment Technique) technique for a multi-intelligence fusion (MIF) system assessment that focuses on the advantages of MIF against single intelligence sources. Building on the NASA TLX (Task Load Index), SAGAT probes, SART (Situational Awareness Rating Technique) questionnaires, and CDM (Critical Decision Method) decision points; we highlight these tools for use in a Multi-Intelligence Critical Rating Assessment of Fusion Techniques (MiCRAFT). The focus is to measure user refinement of a situation over the information fusion quality of service (QoS) metrics: timeliness, accuracy, confidence, workload (cost), and attention (throughput). A key component of any user analysis includes correlation, association, and summarization of data; so we also seek measures of product quality and QuEST of information. Building a notion of product quality from multi-intelligence tools is typically subjective which needs to be aligned with objective machine metrics.

  8. Assessing the Value of Structured Analytic Techniques in the U.S. Intelligence Community

    Science.gov (United States)

    2016-01-01

    Analytic Techniques, and Why Do Analysts Use Them? SATs are methods of organizing and stimulating thinking about intelligence problems. These methods... thinking ; and imaginative thinking techniques encourage new perspectives, insights, and alternative scenarios. Among the many SATs in use today, the...more transparent, so that other analysts and customers can bet - ter understand how the judgments were reached. SATs also facilitate group involvement

  9. Artificial Intelligence Techniques for Automatic Screening of Amblyogenic Factors

    Science.gov (United States)

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

    2008-01-01

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

  10. Artificial intelligence techniques for automatic screening of amblyogenic factors.

    Science.gov (United States)

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

    2008-01-01

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

  11. IT-tool Concept for Design and Intelligent Motion Control

    DEFF Research Database (Denmark)

    Conrad, Finn; Hansen, Poul Erik; Sørensen, Torben

    2000-01-01

    The paper presents results obtained from a Danish mechatronic research program focusing on intelligent motion control as well as results from the Esprit project SWING on IT-tools for rapid prototyping of fluid power components and systems. A mechatronic test facility with digital controllers for ....... Furthermore, a developed IT-tool concept for controller and system design utilising the ISO 10303 STEP Standard is proposed....

  12. Sliding Mode Control for Trajectory Tracking of an Intelligent Wheelchair

    Directory of Open Access Journals (Sweden)

    Razvan SOLEA

    2009-12-01

    Full Text Available This paper deal with a robust sliding-mode trajectory tracking controller, fornonholonomic wheeled mobile robots and its experimental evaluation by theimplementation in an intelligent wheelchair (RobChair. The proposed control structureis based on two nonlinear sliding surfaces ensuring the tracking of the three outputvariables, with respect to the nonholonomic constraint. The performances of theproposed controller for the trajectory planning problem with comfort constraint areverified through the real time acceleration provided by an inertial measurement unit.

  13. F-15 837 IFCS Intelligent Flight Control System Project

    Science.gov (United States)

    Bosworth, John T.

    2007-01-01

    This viewgraph presentation reviews the use of Intelligent Flight Control System (IFCS) for the F-15. The goals of the project are: (1) Demonstrate Revolutionary Control Approaches that can Efficiently Optimize Aircraft Performance in both Normal and Failure Conditions (2) Advance Neural Network-Based Flight Control Technology for New Aerospace Systems Designs. The motivation for the development are to reduce the chance and skill required for survival.

  14. An Intelligent Lighting Control System (ILCS) using LabVIEW ...

    African Journals Online (AJOL)

    An Intelligent Lighting Control System (ILCS) was proposed and designed by considering ergonomic setting and energy efficiency. The integration of CompactRIO as a main hardware and National Instrument Laboratory Virtual Instrument Engineering Workbench (NI LabVIEW) 2012 as a platform to design an interactive ...

  15. Evolving intelligent vehicle control using multi-objective NEAT

    NARCIS (Netherlands)

    Willigen, W.H. van; Haasdijk, E.; Kester, L.J.H.M.

    2013-01-01

    The research in this paper is inspired by a vision of intelligent vehicles that autonomously move along motorways: they join and leave trains of vehicles (platoons), overtake other vehicles, etc. We propose a multi-objective algorithm based on NEAT and SPEA2 that evolves controllers for such

  16. Intelligent Flight Control System and Aeronautics Research at NASA Dryden

    Science.gov (United States)

    Brown, Nelson A.

    2009-01-01

    This video presentation reviews the F-15 Intelligent Flight Control System and contains clips of flight tests and aircraft performance in the areas of target tracking, takeoff and differential stabilators. Video of the APG milestone flight 1g formation is included.

  17. A generic model for camera based intelligent road crowd control ...

    African Journals Online (AJOL)

    This research proposes a model for intelligent traffic flow control by implementing camera based surveillance and feedback system. A series of cameras are set minimum three signals ahead from the target junction. The complete software system is developed to help integrating the multiple camera on road as feedback to ...

  18. Emotional intelligence and locus of control of adult patients with ...

    African Journals Online (AJOL)

    Background: This article investigates emotional intelligence and locus of control in an adult breast cancer population receiving treatment. Gaining insight into these constructs will contribute to improving breast cancer patients' psychological well-being and to reducing physical vulnerability to disease before and during ...

  19. Approach for Autonomous Control of Unmanned Aerial Vehicle Using Intelligent Agents for Knowledge Creation

    Science.gov (United States)

    Dufrene, Warren R., Jr.

    2004-01-01

    This paper describes the development of a planned approach for Autonomous operation of an Unmanned Aerial Vehicle (UAV). A Hybrid approach will seek to provide Knowledge Generation thru the application of Artificial Intelligence (AI) and Intelligent Agents (IA) for UAV control. The application of many different types of AI techniques for flight will be explored during this research effort. The research concentration will be directed to the application of different AI methods within the UAV arena. By evaluating AI approaches, which will include Expert Systems, Neural Networks, Intelligent Agents, Fuzzy Logic, and Complex Adaptive Systems, a new insight may be gained into the benefits of AI techniques applied to achieving true autonomous operation of these systems thus providing new intellectual merit to this research field. The major area of discussion will be limited to the UAV. The systems of interest include small aircraft, insects, and miniature aircraft. Although flight systems will be explored, the benefits should apply to many Unmanned Vehicles such as: Rovers, Ocean Explorers, Robots, and autonomous operation systems. The flight system will be broken down into control agents that will represent the intelligent agent approach used in AI. After the completion of a successful approach, a framework of applying a Security Overseer will be added in an attempt to address errors, emergencies, failures, damage, or over dynamic environment. The chosen control problem was the landing phase of UAV operation. The initial results from simulation in FlightGear are presented.

  20. 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...

  1. F-15 Intelligent Flight Control System and Aeronautics Research at NASA Dryden

    Science.gov (United States)

    Brown, Nelson A.

    2009-01-01

    This viewgraph presentation reviews the F-15 Intelligent Flight Control System and Aeronautics including Autonomous Aerial Refueling Demonstrations, X-48B Blended Wing Body, F-15 Quiet Spike, and NF-15 Intelligent Flight Controls.

  2. International conference on Advances in Intelligent Control and Innovative Computing

    CERN Document Server

    Castillo, Oscar; Huang, Xu; Intelligent Control and Innovative Computing

    2012-01-01

    In the lightning-fast world of intelligent control and cutting-edge computing, it is vitally important to stay abreast of developments that seem to follow each other without pause. This publication features the very latest and some of the very best current research in the field, with 32 revised and extended research articles written by prominent researchers in the field. Culled from contributions to the key 2011 conference Advances in Intelligent Control and Innovative Computing, held in Hong Kong, the articles deal with a wealth of relevant topics, from the most recent work in artificial intelligence and decision-supporting systems, to automated planning, modelling and simulation, signal processing, and industrial applications. Not only does this work communicate the current state of the art in intelligent control and innovative computing, it is also an illuminating guide to up-to-date topics for researchers and graduate students in the field. The quality of the contents is absolutely assured by the high pro...

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

    Directory of Open Access Journals (Sweden)

    Venkata Rami Reddy K

    2017-03-01

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

  4. Advanced Control Architectures for Intelligent MicroGrids, Part I

    DEFF Research Database (Denmark)

    Guerrero, Josep M.; Chandorkar, Mukul; Lee, Tzung-Lin

    2013-01-01

    This paper presents a review of advanced control techniques for microgrids. The paper covers decentralized, distributed, and hierarchical control of grid connected and islanded microgrids. At first, decentralized control techniques for microgrids are reviewed. Then, the recent developments in the...

  5. Scalable Clustering of High-Dimensional Data Technique Using SPCM with Ant Colony Optimization Intelligence

    Directory of Open Access Journals (Sweden)

    Thenmozhi Srinivasan

    2015-01-01

    Full Text Available Clusters of high-dimensional data techniques are emerging, according to data noisy and poor quality challenges. This paper has been developed to cluster data using high-dimensional similarity based PCM (SPCM, with ant colony optimization intelligence which is effective in clustering nonspatial data without getting knowledge about cluster number from the user. The PCM becomes similarity based by using mountain method with it. Though this is efficient clustering, it is checked for optimization using ant colony algorithm with swarm intelligence. Thus the scalable clustering technique is obtained and the evaluation results are checked with synthetic datasets.

  6. Relationship of emotional intelligence and health locus of control among female breast cancer patients in pakistan

    International Nuclear Information System (INIS)

    Naz, R.; Kamal, A.

    2016-01-01

    Objective: To investigate relationship between emotional intelligence and health locus of control in married women with breast cancer disease. Study Design: Cross sectional study. Place and Duration of Study: The data was collected from Nuclear Oncology and Radiology Institute (NORI Hospital) Islamabad (n=210) and from Combined Military Hospital (CMH) Rawalpindi (n=101). Data collection was completed between the period from Oct 2013 to Feb 2014. Patients and Methods: The sample was selected using non- probability sampling technique. Collected breast cancer patients sample was n= 311 whose age range was from 18-80 years. A biographical sheet that contain personal and disease information of patient, and two scales were used: Self Report Measure of Emotional Intelligence (Khan and Kamal, 2010), and Multidimensional Health Locus of Control (Wallston, Stein, and Smith, 1994) were used to assess the constructs explored in this study. Results: Results depict that there was significant positive correlation between emotional intelligence (EI), including its sub scales Emotional Self-Regulation Skills (ESRS), Emotional Self Awareness Skills (ESAS), and Interpersonal Skills Scale (ISS) with the Internal Health Locus of Control (IHLOC). Doctors Health Locus of Control (DHLOC) also have significant relationship to emotional intelligence's all sub divisions, whereas external health locus of control including Chance Health Locus of Control (CHLOC) and Powerful Other people Health Locus of Control (PHLOC) both are related to psychological distresses but it was observed in breast cancer population that chance was significantly correlated to ESAS, and ISS and powerful other people locus. Further on group comparison One Way Analysis of Variance (ANOVA) depicted no significant difference on disease stage groups. Conclusion: The strength factors of EI and HLOC are highlighted in current study. It was concluded that Emotional Intelligence (EI) and health locus of control (IHLOC, and

  7. Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Alejandro Carrasco Elizalde

    2008-01-01

    Full Text Available The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.

  8. The strategy for intelligent integrated instrumentation and control system development

    International Nuclear Information System (INIS)

    Kwon, Kee Choon; Ham, Chang Shik

    1995-01-01

    All of the nuclear power plants in Korea are operating with analog instrumentation and control ( I and C) equipment which are increasingly faced with frequent troubles, obsolescence and high maintenance expenses. Electrical and computer technology has improved rapidly in recent years and has been applied to other industries. So it is strongly recommended we adopt modern digital and computer technology to improve plant safety and availability. The advanced I and C system, namely, Integrated Intelligent Instrumentation and Control System (I 3 Cs) will be developed for beyond the next generation nuclear power plant. I 3 CS consists of three major parts, the advanced compact workstation, distributed digital control and protection system including Automatic Start-up/Shutdown Intelligent Control System (ASICS) and the computer-based alarm processing and operator support system, namely, Diagnosis, Response, and operator Aid Management System (DREAMS)

  9. Automatic Satellite Telemetry Analysis for SSA using Artificial Intelligence Techniques

    Science.gov (United States)

    Stottler, R.; Mao, J.

    In April 2016, General Hyten, commander of Air Force Space Command, announced the Space Enterprise Vision (SEV) (http://www.af.mil/News/Article-Display/Article/719941/hyten-announces-space-enterprise-vision/). The SEV addresses increasing threats to space-related systems. The vision includes an integrated approach across all mission areas (communications, positioning, navigation and timing, missile warning, and weather data) and emphasizes improved access to data across the entire enterprise and the ability to protect space-related assets and capabilities. "The future space enterprise will maintain our nation's ability to deliver critical space effects throughout all phases of conflict," Hyten said. Satellite telemetry is going to become available to a new audience. While that telemetry information should be valuable for achieving Space Situational Awareness (SSA), these new satellite telemetry data consumers will not know how to utilize it. We were tasked with applying AI techniques to build an infrastructure to process satellite telemetry into higher abstraction level symbolic space situational awareness and to initially populate that infrastructure with useful data analysis methods. We are working with two organizations, Montana State University (MSU) and the Air Force Academy, both of whom control satellites and therefore currently analyze satellite telemetry to assess the health and circumstances of their satellites. The design which has resulted from our knowledge elicitation and cognitive task analysis is a hybrid approach which combines symbolic processing techniques of Case-Based Reasoning (CBR) and Behavior Transition Networks (BTNs) with current Machine Learning approaches. BTNs are used to represent the process and associated formulas to check telemetry values against anticipated problems and issues. CBR is used to represent and retrieve BTNs that represent an investigative process that should be applied to the telemetry in certain circumstances

  10. Development of NPTC-11 intelligence control instrument with digital display

    International Nuclear Information System (INIS)

    Wang Chengming; Pu Li; Yu Jiang; Xue Yuping; Zhang Bo; Chen Yong

    2007-01-01

    The accurate of the process control gauge has direct influence on the safe operation of nuclear power plants. Therefore it is necessary to accumulate experiences for the domestic development of this Instrument. In this paper, NPTC-11 intelligence control Instrument with digital display is developed based on the design code for nuclear Instrument, considering the actual application requirements and technical redundancy. Its application in nuclear power plant for almost one year indicates that this Instrument satisfies the development purpose and requirements. (authors)

  11. 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.

  12. Vehicle following controller design for autonomous intelligent vehicles

    Science.gov (United States)

    Chien, C. C.; Lai, M. C.; Mayr, R.

    1994-01-01

    A new vehicle following controller is proposed for autonomous intelligent vehicles. The proposed vehicle following controller not only provides smooth transient maneuvers for unavoidable nonzero initial conditions but also guarantees the asymptotic platoon stability without the availability of feedforward information. Furthermore, the achieved asymptotic platoon stability is shown to be robust to sensor delays and an upper bound for the allowable sensor delays is also provided in this paper.

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

    Energy Technology Data Exchange (ETDEWEB)

    Na, M. G.; Lee, S. H.; Kim, D. S.; No, Y. G.; Lee, S. W. [Chosun University, Gwangju (Korea, Republic of); Ahn, K. I. [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2010-06-15

    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

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

    International Nuclear Information System (INIS)

    Na, M. G.; Lee, S. H.; Kim, D. S.; No, Y. G.; Lee, S. W.; Ahn, K. I.

    2010-06-01

    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

  15. Advances in Intelligent Modelling and Simulation Artificial Intelligence-Based Models and Techniques in Scalable Computing

    CERN Document Server

    Khan, Samee; Burczy´nski, Tadeusz

    2012-01-01

    One of the most challenging issues in today’s large-scale computational modeling and design is to effectively manage the complex distributed environments, such as computational clouds, grids, ad hoc, and P2P networks operating under  various  types of users with evolving relationships fraught with  uncertainties. In this context, the IT resources and services usually belong to different owners (institutions, enterprises, or individuals) and are managed by different administrators. Moreover, uncertainties are presented to the system at hand in various forms of information that are incomplete, imprecise, fragmentary, or overloading, which hinders in the full and precise resolve of the evaluation criteria, subsequencing and selection, and the assignment scores. Intelligent scalable systems enable the flexible routing and charging, advanced user interactions and the aggregation and sharing of geographically-distributed resources in modern large-scale systems.   This book presents new ideas, theories, models...

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

    Science.gov (United States)

    Stottler, D.

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

  17. Intelligent Overload Control for Composite Web Services

    NARCIS (Netherlands)

    Meulenhoff, P.J.; Ostendorf, D.R.; Zivkovic, Miroslav; Meeuwissen, H.B.; Gijsen, B.M.M.

    2009-01-01

    In this paper, we analyze overload control for composite web services in service oriented architectures by an orchestrating broker, and propose two practical access control rules which effectively mitigate the effects of severe overloads at some web services in the composite service. These two rules

  18. Intelligent Control for the BEES Flyer

    Science.gov (United States)

    Krishnakumar, K.; Gundy-Burlet, Karen; Aftosmis, Mike; Nemec, Marian; Limes, Greg; Berry, Misty; Logan, Michael

    2004-01-01

    This paper describes the effort to provide a preliminary capability analysis and a neural network based adaptive flight control system for the JPL-led BEES aircraft project. The BEES flyer was envisioned to be a small, autonomous platform with sensing and control systems mimicking those of biological systems for the purpose of scientific exploration on the surface of Mars. The platform is physically tightly constrained by the necessity of efficient packing within rockets for the trip to Mars. Given the physical constraints, the system is not an ideal configuration for aerodynamics or stability and control. The objectives of this effort are to evaluate the aerodynamics characteristics of the existing design, to make recommendaaons as to potential improvements and to provide a control system that stabilizes the existing aircraft for nominal flight and damaged conditions. Towards this several questions are raised and analyses are presented to arrive at answers to some of the questions raised. CART3D, a high-fidelity inviscid analysis package for conceptual and preliminary aerodynamic design, was used to compute a parametric set of solutions over the expected flight domain. Stability and control derivatives were extracted from the database and integrated with the neural flight control system. The Integrated Vehicle Modeling Environment (IVME) was also used for estimating aircraft geometric, inertial, and aerodynamic characteristics. A generic neural flight control system is used to provide adaptive control without the requirement for extensive gain scheduling or explicit system identification. The neural flight control system uses reference models to specify desired handling qualities in the roll, pitch, and yaw axes, and incorporates both pre-trained and on-line learning neural networks in the inverse model portion of the controller. Results are presented for the BEES aircraft in the subsonic regime for terrestrial and Martian environments.

  19. Artificial intelligence-based speed control of DTC induction motor drives - A comparative study

    Energy Technology Data Exchange (ETDEWEB)

    Gadoue, S.M.; Giaouris, D.; Finch, J.W. [School of Electrical, Electronic and Computer Engineering, Newcastle University, Newcastle upon Tyne NE1 7RU (United Kingdom)

    2009-01-15

    The design of the speed controller greatly affects the performance of an electric drive. A common strategy to control an induction machine is to use direct torque control combined with a PI speed controller. These schemes require proper and continuous tuning and therefore adaptive controllers are proposed to replace conventional PI controllers to improve the drive's performance. This paper presents a comparison between four different speed controller design strategies based on artificial intelligence techniques; two are based on tuning of conventional PI controllers, the third makes use of a fuzzy logic controller and the last is based on hybrid fuzzy sliding mode control theory. To provide a numerical comparison between different controllers, a performance index based on speed error is assigned. All methods are applied to the direct torque control scheme and each control strategy has been tested for its robustness and disturbance rejection ability. (author)

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

    International Nuclear Information System (INIS)

    Lai, C.

    1990-01-01

    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

  1. Intelligence

    Science.gov (United States)

    Sternberg, Robert J.

    2012-01-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

  2. Intelligence.

    Science.gov (United States)

    Sternberg, Robert J

    2012-03-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

  3. Intelligent Controller Design for a Chemical Process

    OpenAIRE

    Mr. Glan Devadhas G; Dr.Pushpakumar S.

    2010-01-01

    Chemical process control is a challenging problem due to the strong on*line non*linearity and extreme sensitivity to disturbances of the process. Ziegler – Nichols tuned PI and PID controllers are found to provide poor performances for higher*order and non–linear systems. This paper presents an application of one*step*ahead fuzzy as well as ANFIS (adaptive*network*based fuzzy inference system) tuning scheme for an Continuous Stirred Tank Reactor CSTR process. The controller is designed based ...

  4. Intelligent multi-unit disk controller

    International Nuclear Information System (INIS)

    Poirot, Lucien

    1982-01-01

    This controller has been designed as a link between a 16 bits minicomputer and two types of disks units interface: the SMD interface and an equivalent to the DRI unit interface. Four units of each type can be handled by the controller. A bit slice microprocessor controls the interface with the disks units. The maximum exchange rate is 8 megabits per second. A CRC feature has been provided for error detection. A 16 bits microprocessor implements the interface to the computer, assuring head positioning, the management of bad tracks, as well as the supervision of each transfer. A internal buffer memory allows an asynchronous dialogue with the computer. The implementation of the controller makes easy the adaptation to disks units of various types, and though it has been initially intended for a minicomputer of the MITRA type, its microprocessor based design makes it fitted to any minicomputer. (author) [fr

  5. Intelligent energy management control for independent microgrid

    Indian Academy of Sciences (India)

    Energy management control; multi-agent system; microgrid; energy forecast; hybrid power ... power to the local load most of the time in this energy management strategy. ... Electrical and Electronics Engineering Department, PSG College of ...

  6. Design and Realization of Intelligent Flow Controller

    Directory of Open Access Journals (Sweden)

    Jianxiong Ye

    2014-09-01

    Full Text Available According to accurate flow rate control requirements in large irrigation zone, a fuzzy controller with dead-band is designed on the characteristics analysis and comparison of PID and Fuzzy. The setting values of water flow for gates are determined by real-time water level detection sensors, and the realistic value of discharged water and gate opening are detected out with relative sensors, simulation manifest that the specific control strategy can adjust the gate swiftly in circumstance of huge offset, and regulate the gate slightly in time of small bias, it is realized with Siemens S315 PLC (Programmable Logical Controller and has being working steadily for 2 years, the aim of regulation is performed properly.

  7. Unified Controller Design for Intelligent Manufacturing Automation

    National Research Council Canada - National Science Library

    Kosut, Robert

    1997-01-01

    .... The demonstration system selected was rapid thermal processing (RTP) of semiconductor wafers. This novel approach in integrated circuit manufacturing demands fast tracking control laws that achieve near uniform spatial temperature distributions...

  8. F-15 IFCS Intelligent Flight Control System

    Science.gov (United States)

    Bosworth, John T.

    2008-01-01

    This viewgraph presentation gives a detailed description of the F-15 aircraft, flight tests, aircraft performance and overall advanced neural network based flight control technologies for aerospace systems designs.

  9. Intelligent Control and Health Monitoring. Chapter 3

    Science.gov (United States)

    Garg, Sanjay; Kumar, Aditya; Mathews, H. Kirk; Rosenfeld, Taylor; Rybarik, Pavol; Viassolo, Daniel E.

    2009-01-01

    Advanced model-based control architecture overcomes the limitations state-of-the-art engine control and provides the potential of virtual sensors, for example for thrust and stall margin. "Tracking filters" are used to adapt the control parameters to actual conditions and to individual engines. For health monitoring standalone monitoring units will be used for on-board analysis to determine the general engine health and detect and isolate sudden faults. Adaptive models open up the possibility of adapting the control logic to maintain desired performance in the presence of engine degradation or to accommodate any faults. Improved and new sensors are required to allow sensing at stations within the engine gas path that are currently not instrumented due in part to the harsh conditions including high operating temperatures and to allow additional monitoring of vibration, mass flows and energy properties, exhaust gas composition, and gas path debris. The environmental and performance requirements for these sensors are summarized.

  10. Advanced instrumentation and control techniques for nuclear power plants

    International Nuclear Information System (INIS)

    Hayakawa, Hiroyasu; Makino, Maomi

    1989-01-01

    Toshiba has been promoting the development and improvement of control and instrumentation (C and I) systems employing the latest technologies, to fulfill the requirements of nuclear power plants for increased reliability, the upgrading of functions, improved maintainability, and reasonable cost. Such development has been systematically performed based on a schematic view of integrated digital control and instrumentation systems, actively adopting state-of-the-art techniques such as the latest man-machine interfaces, digital and optical multiplexing techniques, and artificial intelligence. In addition, comprehensive feedback has been obtained from the accumulation of operating experience. This paper describes the purpose, contents and status of applications of representative newly-developed systems. (author)

  11. The single chip microcomputer technique in an intelligent nuclear instrument

    International Nuclear Information System (INIS)

    Wang Tieliu; Sun Punan; Wang Ying

    1995-01-01

    The authors present that how to acquire and process the output signals from the nuclear detector adopting single chip microcomputer technique, including working principles and the designing method of the computer's software and hardware in the single chip microcomputer instrument

  12. Intelligent automated control of robotic systems for environmental restoration

    International Nuclear Information System (INIS)

    Harrigan, R.W.

    1992-01-01

    The US Department of Energy's Office of Technology Development (OTD) has sponsored the development of the Generic Intelligent System Controller (GISC) for application to remote system control. Of primary interest to the OTD is the development of technologies which result in faster, safer, and cheaper cleanup of hazardous waste sites than possible using conventional approaches. The objective of the GISC development project is to support these goals by developing a modular robotics control approach which reduces the time and cost of development by allowing reuse of control system software and uses computer models to improve the safety of remote site cleanup while reducing the time and life cycle costs

  13. Directions for rf-controlled intelligent microvalve

    Science.gov (United States)

    Enderling, Stefan; Varadan, Vijay K.; Abbott, Derek

    2001-03-01

    In this paper, we consider the novel concept of a Radio Frequency (RF) controllable microvalve for different medical applications. Wireless communication via a Surface Acoustic Wave Identification-mark (SAW ID-tag) is used to control, drive and locate the microvalve inside the human body. The energy required for these functions is provided by RF pulses, which are transmitted to the valve and back by a reader/transmitter system outside of the body. These RF bursts are converted into Surface Acoustic Waves (SAWs), which propagate along the piezoelectric actuator material of the microvalve. These waves cause deflections, which are employed to open and close the microvalve. We identified five important areas of application of the microvalve in biomedicine: 1) fertility control; 2) artificial venous valves; 3) flow cytometry; 4) drug delivery and 5) DNA mapping.

  14. The Automator: Intelligent control system monitoring

    International Nuclear Information System (INIS)

    M. Bickley; D.A. Bryan; K.S. White

    1999-01-01

    A large-scale control system may contain several hundred thousand control points which must be monitored to ensure smooth operation. Knowledge of the current state of such a system is often implicit in the values of these points and operators must be cognizant of the state while making decisions. Repetitive operators requiring human intervention lead to fatigue, which can in turn lead to mistakes. The authors propose a tool called the Automator based on a middleware software server. This tool would provide a user-configurable engine for monitoring control points. Based on the status of these control points, a specified action could be taken. The action could range from setting another control point, to triggering an alarm, to running an executable. Often the data presented by a system is meaningless without context information from other channels. Such a tool could be configured to present interpreted information based on values of other channels. Additionally, this tool could translate numerous values in a non-friendly form (such as numbers, bits, or return codes) into meaningful strings of information. Multiple instances of this server could be run, allowing individuals or groups to configure their own Automators. The configuration of the tool will be file-based. In the future, these files could be generated by graphical design tools, allowing for rapid development of new configurations. In addition, the server will be able to explicitly maintain information about the state of the control system. This state information can be used in decision-making processes and shared with other applications. A conceptual framework and software design for the tool are presented

  15. Using Game Theory Techniques and Concepts to Develop Proprietary Models for Use in Intelligent Games

    Science.gov (United States)

    Christopher, Timothy Van

    2011-01-01

    This work is about analyzing games as models of systems. The goal is to understand the techniques that have been used by game designers in the past, and to compare them to the study of mathematical game theory. Through the study of a system or concept a model often emerges that can effectively educate students about making intelligent decisions…

  16. Intelligent Techniques Using Molecular Data Analysis in Leukaemia: An Opportunity for Personalized Medicine Support System.

    Science.gov (United States)

    Banjar, Haneen; Adelson, David; Brown, Fred; Chaudhri, Naeem

    2017-01-01

    The use of intelligent techniques in medicine has brought a ray of hope in terms of treating leukaemia patients. Personalized treatment uses patient's genetic profile to select a mode of treatment. This process makes use of molecular technology and machine learning, to determine the most suitable approach to treating a leukaemia patient. Until now, no reviews have been published from a computational perspective concerning the development of personalized medicine intelligent techniques for leukaemia patients using molecular data analysis. This review studies the published empirical research on personalized medicine in leukaemia and synthesizes findings across studies related to intelligence techniques in leukaemia, with specific attention to particular categories of these studies to help identify opportunities for further research into personalized medicine support systems in chronic myeloid leukaemia. A systematic search was carried out to identify studies using intelligence techniques in leukaemia and to categorize these studies based on leukaemia type and also the task, data source, and purpose of the studies. Most studies used molecular data analysis for personalized medicine, but future advancement for leukaemia patients requires molecular models that use advanced machine-learning methods to automate decision-making in treatment management to deliver supportive medical information to the patient in clinical practice.

  17. Intelligent electrical outlet for collective load control

    Science.gov (United States)

    Lentine, Anthony L.; Ford, Justin R.; Spires, Shannon V.; Goldsmith, Steven Y.

    2015-10-27

    Various technologies described herein pertain to an electrical outlet that autonomously manages loads in a microgrid. The electrical outlet can provide autonomous load control in response to variations in electrical power generation supply in the microgrid. The electrical outlet includes a receptacle, a sensor operably coupled to the receptacle, and an actuator configured to selectively actuate the receptacle. The sensor measures electrical parameters at the receptacle. Further, a processor autonomously controls the actuator based at least in part on the electrical parameters measured at the receptacle, electrical parameters from one or more disparate electrical outlets in the microgrid, and a supply of generated electric power in the microgrid at a given time.

  18. Computational intelligence techniques for biological data mining: An overview

    Science.gov (United States)

    Faye, Ibrahima; Iqbal, Muhammad Javed; Said, Abas Md; Samir, Brahim Belhaouari

    2014-10-01

    Computational techniques have been successfully utilized for a highly accurate analysis and modeling of multifaceted and raw biological data gathered from various genome sequencing projects. These techniques are proving much more effective to overcome the limitations of the traditional in-vitro experiments on the constantly increasing sequence data. However, most critical problems that caught the attention of the researchers may include, but not limited to these: accurate structure and function prediction of unknown proteins, protein subcellular localization prediction, finding protein-protein interactions, protein fold recognition, analysis of microarray gene expression data, etc. To solve these problems, various classification and clustering techniques using machine learning have been extensively used in the published literature. These techniques include neural network algorithms, genetic algorithms, fuzzy ARTMAP, K-Means, K-NN, SVM, Rough set classifiers, decision tree and HMM based algorithms. Major difficulties in applying the above algorithms include the limitations found in the previous feature encoding and selection methods while extracting the best features, increasing classification accuracy and decreasing the running time overheads of the learning algorithms. The application of this research would be potentially useful in the drug design and in the diagnosis of some diseases. This paper presents a concise overview of the well-known protein classification techniques.

  19. An intelligent remote control system for ECEI on EAST

    Science.gov (United States)

    Chen, Dongxu; Zhu, Yilun; Zhao, Zhenling; Qu, Chengming; Liao, Wang; Xie, Jinlin; Liu, Wandong

    2017-08-01

    An intelligent remote control system based on a power distribution unit (PDU) and Arduino has been designed for the electron cyclotron emission imaging (ECEI) system on Experimental Advanced Superconducting Tokamak (EAST). This intelligent system has three major functions: ECEI system reboot, measurement region adjustment and signal amplitude optimization. The observation region of ECEI can be modified for different physics proposals by remotely tuning the optical and electronics systems. Via the remote adjustment of the attenuation level, the ECEI intermediate frequency signal amplitude can be efficiently optimized. The remote control system provides a feasible and reliable solution for the improvement of signal quality and the efficiency of the ECEI diagnostic system, which is also valuable for other diagnostic systems.

  20. Applications Of Artificial Intelligence In Control System Analysis And Design

    Science.gov (United States)

    Birdwell, J. D.

    1987-10-01

    To date, applications of artificial intelligence in control system analysis and design are primarily associated with the design process. These applications take the form of knowledge bases incorporating expertise on a design method, such as multivariable linear controller design, or on a field such as identification. My experience has demonstrated that, while such expert systems are useful, perhaps a greater benefit will come from applications in the maintenance of technical databases, as are found in real-time data acquisition systems, and of modeling and design databases, which represent the status of a computer-aided design process for a human user. This reflects the observation that computers are best at maintaining relations about large sets of objects, whereas humans are best at maintaining knowledge of depth, as occurs when a design option involving a sequence of steps is explored. This paper will discuss some of these issues, and will provide some examples which illustrate the potential of artificial intelligence.

  1. Novel intelligent PID control of traveling wave ultrasonic motor.

    Science.gov (United States)

    Jingzhuo, Shi; Yu, Liu; Jingtao, Huang; Meiyu, Xu; Juwei, Zhang; Lei, Zhang

    2014-09-01

    A simple control strategy with acceptable control performance can be a good choice for the mass production of ultrasonic motor control system. In this paper, through the theoretic and experimental analyses of typical control process, a simpler intelligent PID speed control strategy of TWUM is proposed, involving only two expert rules to adjust the PID control parameters based on the current status. Compared with the traditional PID controller, this design requires less calculation and more cheap chips which can be easily involved in online performance. Experiments with different load torques and voltage amplitudes show that the proposed controller can deal with the nonlinearity and load disturbance to maintain good control performance of TWUM. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

  2. Recent advances in sliding modes from control to intelligent mechatronics

    CERN Document Server

    Efe, Mehmet

    2015-01-01

    This volume is dedicated to Professor Okyay Kaynak to commemorate his life time impactful research and scholarly achievements and outstanding services to profession. The 21 invited chapters have been written by leading researchers who, in the past, have had association with Professor Kaynak as either his students and associates or colleagues and collaborators. The focal theme of the volume is the Sliding Modes covering a broad scope of topics from theoretical investigations to their significant applications from Control to Intelligent Mechatronics.  

  3. Intelligent control of a planning system for astronaut training.

    Science.gov (United States)

    Ortiz, J; Chen, G

    1999-07-01

    This work intends to design, analyze and solve, from the systems control perspective, a complex, dynamic, and multiconstrained planning system for generating training plans for crew members of the NASA-led International Space Station. Various intelligent planning systems have been developed within the framework of artificial intelligence. These planning systems generally lack a rigorous mathematical formalism to allow a reliable and flexible methodology for their design, modeling, and performance analysis in a dynamical, time-critical, and multiconstrained environment. Formulating the planning problem in the domain of discrete-event systems under a unified framework such that it can be modeled, designed, and analyzed as a control system will provide a self-contained theory for such planning systems. This will also provide a means to certify various planning systems for operations in the dynamical and complex environments in space. The work presented here completes the design, development, and analysis of an intricate, large-scale, and representative mathematical formulation for intelligent control of a real planning system for Space Station crew training. This planning system has been tested and used at NASA-Johnson Space Center.

  4. Functional requirements for an intelligent RPC. [remote power controller for spaceborne electrical distribution system

    Science.gov (United States)

    Aucoin, B. M.; Heller, R. P.

    1990-01-01

    An intelligent remote power controller (RPC) based on microcomputer technology can implement advanced functions for the accurate and secure detection of all types of faults on a spaceborne electrical distribution system. The intelligent RPC will implement conventional protection functions such as overcurrent, under-voltage, and ground fault protection. Advanced functions for the detection of soft faults, which cannot presently be detected, can also be implemented. Adaptive overcurrent protection changes overcurrent settings based on connected load. Incipient and high-impedance fault detection provides early detection of arcing conditions to prevent fires, and to clear and reconfigure circuits before soft faults progress to a hard-fault condition. Power electronics techniques can be used to implement fault current limiting to prevent voltage dips during hard faults. It is concluded that these techniques will enhance the overall safety and reliability of the distribution system.

  5. ADAA: new software for intelligent instrument control

    International Nuclear Information System (INIS)

    Butman, M.; Wannberg, A.; Mellergaard, A.; Zetterstroem, P.; McGreevy, R.L.

    2004-01-01

    Automated data acquisition and analysis (ADAA) is a new platform for automation of experiments, including data reduction, analysis and feedback. The objective of ADAA is to develop software that enables scientific control of the progress of an experiment, e.g. monitoring in terms of analysed data as opposed to measured data, one obvious aim being to maximize the scientific output from a given period of beam time. Basic design considerations will be outlined and discussed in the context of several types of experiments

  6. A Novel Intelligent Transportation Control Supported by Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Zhe Qian

    2013-05-01

    Full Text Available With the development of wireless sensor unit, and improvement of real-time and quality of wireless communication, the intelligent transportation control system employ these technologies to realize sensing, positioning, computing, and communication for voiding collisions. This paper discusses the framework of transportation control system, and emphases TDOA positioning algorithm and the new weighted least square optimization method. The simulation result shows that, our method achieves high-accuracy of positioning, which can satisfy the need of transportation control. Finally, we outline the urgent work need to address in the future.

  7. Intelligence Control System for Landfills Based on Wireless Sensor Network

    Science.gov (United States)

    Zhang, Qian; Huang, Chuan; Gong, Jian

    2018-06-01

    This paper put forward an intelligence system for controlling the landfill gas in landfills to make the landfill gas (LFG) exhaust controllably and actively. The system, which is assigned by the wireless sensor network, were developed and supervised by remote applications in workshop instead of manual work. An automatic valve control depending on the sensor units embedded is installed in tube, the air pressure and concentration of LFG are detected to decide the level of the valve switch. The paper also proposed a modified algorithm to solve transmission problem, so that the system can keep a high efficiency and long service life.

  8. Intelligence Control System for Landfills Based on Wireless Sensor Network

    Directory of Open Access Journals (Sweden)

    Zhang Qian

    2018-01-01

    Full Text Available This paper put forward an intelligence system for controlling the landfill gas in landfills to make the landfill gas (LFG exhaust controllably and actively. The system, which is assigned by the wireless sensor network, were developed and supervised by remote applications in workshop instead of manual work. An automatic valve control depending on the sensor units embedded is installed in tube, the air pressure and concentration of LFG are detected to decide the level of the valve switch. The paper also proposed a modified algorithm to solve transmission problem, so that the system can keep a high efficiency and long service life.

  9. An Intelligent Control for the Distributed Flexible Network Photovoltaic System using Autonomous Control and Agent

    Science.gov (United States)

    Park, Sangsoo; Miura, Yushi; Ise, Toshifumi

    This paper proposes an intelligent control for the distributed flexible network photovoltaic system using autonomous control and agent. The distributed flexible network photovoltaic system is composed of a secondary battery bank and a number of subsystems which have a solar array, a dc/dc converter and a load. The control mode of dc/dc converter can be selected based on local information by autonomous control. However, if only autonomous control using local information is applied, there are some problems associated with several cases such as voltage drop on long power lines. To overcome these problems, the authors propose introducing agents to improve control characteristics. The autonomous control with agents is called as intelligent control in this paper. The intelligent control scheme that employs the communication between agents is applied for the model system and proved with simulation using PSCAD/EMTDC.

  10. Fuzzy Cognitive Map for Software Testing Using Artificial Intelligence Techniques

    OpenAIRE

    Larkman , Deane; Mohammadian , Masoud; Balachandran , Bala; Jentzsch , Ric

    2010-01-01

    International audience; This paper discusses a framework to assist test managers to evaluate the use of AI techniques as a potential tool in software testing. Fuzzy Cognitive Maps (FCMs) are employed to evaluate the framework and make decision analysis easier. A what-if analysis is presented that explores the general application of the framework. Simulations are performed to show the effectiveness of the proposed method. The framework proposed is innovative and it assists managers in making e...

  11. Intelligent systems supporting the control room operators

    International Nuclear Information System (INIS)

    Berger, E.

    1997-01-01

    The operational experience obtained with the various applications of the systems discussed in this paper shows that more consequent use of the systems will make detection and management of disturbances still more efficient and faster. This holds true both for a low level of process automation and for power plants with a high level of automation. As for conventional power plants, the trend clearly is towards higher degrees of automation and consequent application of supporting systems. Thus, higher availability and rapid failure management are achieved, at low effects on normal operation. These systems are monitoring and process control systems, expert systems, and systems for optimal use of the equipment, or systems for post-incident analyses and computer-assisted on-shift protocols, or operating manuals. (orig./CB) [de

  12. Intelligent Control of Home Appliances via Network

    DEFF Research Database (Denmark)

    Rossello Busquet, Ana

    platform which guaranties interoperability, as well as scalability and flexibility. Therefore, a home gateway prototype has been developed in JAVA. This implementation offers the required capabilities for a Home Energy Management System, i.e. it enables the user to monitor and control the home devices......, in addition to providing energy management strategies to reduce electricity consumption. Reducing energy consumption in home environments has become crucial to meet the "20-20-20" targets set by European Commission Climate Action. However, reducing energy in home environments is not sufficient. The power grid......This thesis addresses selected topics of energy management in home environments and ICT for the Smart Grid. However, those two topics are vast and only a few aspects of them have been discussed. This thesis focuses on providing a home energy management solution based on a technology independent...

  13. Regenerative Intelligent Brake Control for Electric Motorcycles

    Directory of Open Access Journals (Sweden)

    Juan Jesús Castillo Aguilar

    2017-10-01

    Full Text Available Vehicle models whose propulsion system is based on electric motors are increasing in number within the automobile industry. They will soon become a reliable alternative to vehicles with conventional propulsion systems. The main advantages of this type of vehicles are the non-emission of polluting gases and noise and the effectiveness of electric motors compared to combustion engines. Some of the disadvantages that electric vehicle manufacturers still have to solve are their low autonomy due to inefficient energy storage systems, vehicle cost, which is still too high, and reducing the recharging time. Current regenerative systems in motorcycles are designed with a low fixed maximum regeneration rate in order not to cause the rear wheel to slip when braking with the regenerative brake no matter what the road condition is. These types of systems do not make use of all the available regeneration power, since more importance is placed on safety when braking. An optimized regenerative braking strategy for two-wheeled vehicles is described is this work. This system is designed to recover the maximum energy in braking processes while maintaining the vehicle’s stability. In order to develop the previously described regenerative control, tyre forces, vehicle speed and road adhesion are obtained by means of an estimation algorithm. A based-on-fuzzy-logic algorithm is programmed to carry out an optimized control with this information. This system recuperates maximum braking power without compromising the rear wheel slip and safety. Simulations show that the system optimizes energy regeneration on every surface compared to a constant regeneration strategy.

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

    Science.gov (United States)

    Straub, Jeremy; Huber, Justin

    2013-05-01

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

  15. A Review of Fuzzy Logic and Neural Network Based Intelligent Control Design for Discrete-Time Systems

    Directory of Open Access Journals (Sweden)

    Yiming Jiang

    2016-01-01

    Full Text Available Over the last few decades, the intelligent control methods such as fuzzy logic control (FLC and neural network (NN control have been successfully used in various applications. The rapid development of digital computer based control systems requires control signals to be calculated in a digital or discrete-time form. In this background, the intelligent control methods developed for discrete-time systems have drawn great attentions. This survey aims to present a summary of the state of the art of the design of FLC and NN-based intelligent control for discrete-time systems. For discrete-time FLC systems, numerous remarkable design approaches are introduced and a series of efficient methods to deal with the robustness, stability, and time delay of FLC discrete-time systems are recommended. Techniques for NN-based intelligent control for discrete-time systems, such as adaptive methods and adaptive dynamic programming approaches, are also reviewed. Overall, this paper is devoted to make a brief summary for recent progresses in FLC and NN-based intelligent control design for discrete-time systems as well as to present our thoughts and considerations of recent trends and potential research directions in this area.

  16. Robust intelligent sliding model control using recurrent cerebellar model articulation controller for uncertain nonlinear chaotic systems

    International Nuclear Information System (INIS)

    Peng Yafu

    2009-01-01

    In this paper, a robust intelligent sliding model control (RISMC) scheme using an adaptive recurrent cerebellar model articulation controller (RCMAC) is developed for a class of uncertain nonlinear chaotic systems. This RISMC system offers a design approach to drive the state trajectory to track a desired trajectory, and it is comprised of an adaptive RCMAC and a robust controller. The adaptive RCMAC is used to mimic an ideal sliding mode control (SMC) due to unknown system dynamics, and a robust controller is designed to recover the residual approximation error for guaranteeing the stable characteristic. Moreover, the Taylor linearization technique is employed to derive the linearized model of the RCMAC. The all adaptation laws of the RISMC system are derived based on the Lyapunov stability analysis and projection algorithm, so that the stability of the system can be guaranteed. Finally, the proposed RISMC system is applied to control a Van der Pol oscillator, a Genesio chaotic system and a Chua's chaotic circuit. The effectiveness of the proposed control scheme is verified by some simulation results with unknown system dynamics and existence of external disturbance. In addition, the advantages of the proposed RISMC are indicated in comparison with a SMC system

  17. Advanced intelligent systems

    CERN Document Server

    Ryoo, Young; Jang, Moon-soo; Bae, Young-Chul

    2014-01-01

    Intelligent systems have been initiated with the attempt to imitate the human brain. People wish to let machines perform intelligent works. Many techniques of intelligent systems are based on artificial intelligence. According to changing and novel requirements, the advanced intelligent systems cover a wide spectrum: big data processing, intelligent control, advanced robotics, artificial intelligence and machine learning. This book focuses on coordinating intelligent systems with highly integrated and foundationally functional components. The book consists of 19 contributions that features social network-based recommender systems, application of fuzzy enforcement, energy visualization, ultrasonic muscular thickness measurement, regional analysis and predictive modeling, analysis of 3D polygon data, blood pressure estimation system, fuzzy human model, fuzzy ultrasonic imaging method, ultrasonic mobile smart technology, pseudo-normal image synthesis, subspace classifier, mobile object tracking, standing-up moti...

  18. ATC enhancement using TCSC via artificial intelligent techniques

    International Nuclear Information System (INIS)

    Rashidinejad, M.; Gharaveisi, A.A.; Farahmand, H.; Fotuhi-Firuzabad, M.

    2008-01-01

    Procurement of optimum available transfer capability (ATC) in the restructured electricity industry is a crucial challenge with regards to open access to transmission network. This paper presents an approach to determine the optimum location and optimum capacity of TCSC in order to improve ATC as well as voltage profile. Real genetic algorithm (RGA) associated with analytical hierarchy process (AHP) and fuzzy sets are implemented as a hybrid heuristic technique in this paper to optimize such a complicated problem. The effectiveness of the proposed methodology is examined through different case studies. (author)

  19. Technique of nuclear reactors controls

    International Nuclear Information System (INIS)

    Weill, J.

    1953-12-01

    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) [fr

  20. An intelligent simulation environment for control system design

    International Nuclear Information System (INIS)

    Robinson, J.T.

    1989-01-01

    The Oak Ridge National Laboratory is currently assisting in the development of advanced control systems for the next generation of nuclear power plants. This paper presents a prototype interactive and intelligent simulation environment being developed to support this effort. The environment combines tools from the field of Artificial Intelligence; in particular object-oriented programming, a LISP programming environment, and a direct manipulation user interface; with traditional numerical methods for simulating combined continuous/discrete processes. The resulting environment is highly interactive and easy to use. Models may be created and modified quickly through a window oriented direct manipulation interface. Models may be modified at any time, even as the simulation is running, and the results observed immediately via real-time graphics. 8 refs., 3 figs

  1. Study of the intelligent control robustness with respect to radiations induced faults

    International Nuclear Information System (INIS)

    Cheynet, Ph.

    1999-01-01

    The so-called intelligent control techniques, such as Artificial Neural Networks and Fuzzy Logic, are considered as being potentially robust. Their digital implementation gives compact and powerful solutions to some problems difficult to be tackled by classical techniques. Such approaches might be used for applications working in harsh environment (nuclear and space). The aim of this thesis is to study the robustness of artificial neural networks and fuzzy logic against Single Event Upset faults, in order to evaluate their viability and their efficiency for onboard spacecraft processes. A set of experiments have been performed on a neural network and a fuzzy controller, both implementing real space applications: texture analysis from satellite images and wheel control of a martian rover. An original method, allowing to increase the recognition rate of any artificial neural network has been developed and used on the studied network. Digital architectures implementing the two studied techniques in this thesis, have been boarded on two scientific satellites. One is in flight since one year, the other will be launched in the end of 1999. Obtained results, both from software simulations, hardware fault injections or particle accelerator tests, show that intelligent control techniques have a significant robustness against Single Event Upset faults. Data issued from the flight experiment confirm these properties, showing that some onboard spacecraft processes can be reliably executed by digital artificial neural networks. (author)

  2. The Effectiveness of Yoga on Spiritual Intelligence in Air Traffic Controllers of Tehran Flight Control Center

    Science.gov (United States)

    Safara, Maryam; Ghasemi, Pejman

    2017-01-01

    The aim of this study was to evaluate the efficacy of yoga on spiritual intelligence in air traffic controllers in Tehran flight control center. This was a quasi-experimental research and the study population includes all air traffic controllers in Tehran flight control center. The sample consisted of 40 people of the study population that were…

  3. Advanced and intelligent computations in diagnosis and control

    CERN Document Server

    2016-01-01

    This book is devoted to the demands of research and industrial centers for diagnostics, monitoring and decision making systems that result from the increasing complexity of automation and systems, the need to ensure the highest level of reliability and safety, and continuing research and the development of innovative approaches to fault diagnosis. The contributions combine domains of engineering knowledge for diagnosis, including detection, isolation, localization, identification, reconfiguration and fault-tolerant control. The book is divided into six parts:  (I) Fault Detection and Isolation; (II) Estimation and Identification; (III) Robust and Fault Tolerant Control; (IV) Industrial and Medical Diagnostics; (V) Artificial Intelligence; (VI) Expert and Computer Systems.

  4. Intelligent Agent Based Traffic Signal Control on Isolated Intersections

    Directory of Open Access Journals (Sweden)

    Daniela Koltovska

    2014-08-01

    Full Text Available The purpose of this paper is to develop an adaptive signal control strategy on isolated urban intersections. An innovative approach to defining the set of states dependent on the actual and primarily observed parameters has been introduced. ?he Q–learning algorithm has been applied. The developed self-learning adaptive signal strategy has been tested on a re?l intersection. The intelligent agent results have been compared to those in cases of fixed-time and actuated control. Regarding the average total delay, the total number of stops and the total throughput, the best results have been obtained for unknown traffic demand and over-capacity.

  5. Intelligent control of a smart walker and its performance evaluation.

    Science.gov (United States)

    Grondin, Simon L; Li, Qingguo

    2013-06-01

    Recent technological advances have allowed the development of force-dependent, intelligently controlled smart walkers that are able to provide users with enhanced mobility, support and gait assistance. The purpose of this study was to develop an intelligent rule-based controller for a smart walker to achieve a smooth interaction between the user and the walker. This study developed a rule-based mapping between the interaction force, measured by a load cell attached to the walker handle, and the acceleration of the walker. Ten young, healthy subjects were used to evaluate the performance of the proposed controller compared to a well-known admittance-based control system. There were no significant differences between the two control systems concerning their user experience, velocity profiles or average cost of transportation. However, the admittance-based control system required a 1.2N lower average interaction force to maintain the 1m/s target speed (p = 0.002). Metabolic data also indicated that smart walker-assisted gait could considerably reduce the metabolic demand of walking with a four-legged walker.

  6. Artificial intelligence-based modeling and control of fluidized bed combustion

    Energy Technology Data Exchange (ETDEWEB)

    Ikonen, E.; Leppaekoski, K. (Univ. of Oulu, Dept. of Process and Environmental Engineering (Finland)). email: enso.ikonen@oulu.fi

    2009-07-01

    AI-inspired techniques have a lot to offer when developing methods for advanced identification, monitoring, control and optimization of industrial processes, such as power plants. Advanced control methods have been extensively examined in the research of the Power Plant Automation group at the Systems Engineering Laboratory, e.g., in fuel inventory modelling, combustion power control, modelling and control of flue gas oxygen, drum control, modelling and control of superheaters, or in optimization of flue-gas emissions. Most engineering approaches to artificial intelligence (AI) are characterized by two fundamental properties: the ability to learn from various sources and the ability to deal with plant complexity. Learning systems that are able to operate in uncertain environments based on incomplete information are commonly referred to as being intelligent. A number of other approaches exist, characterized by these properties, but not easily categorized as AI-systems. Advanced control methods (adaptive, predictive, multivariable, robust, etc.) are based on the availability of a model of the process to be controlled. Hence identification of processes becomes a key issue, leading to the use of adaptation and learning techniques. A typical learning control system concerns a selection of learning techniques applied for updating a process model, which in turn is used for the controller design. When design of learning control systems is complemented with concerns for dealing with uncertainties or vaguenesses in models, measurements, or even objectives, particularly close connections exist between advanced process control and methods of artificial intelligence and machine learning. Needs for advanced techniques are typically characterized by the desire to properly handle plant non-linearities, the multivariable nature of the dynamic problems, and the necessity to adapt to changing plant conditions. In the field of fluidized bed combustion (FBC) control, the many promising

  7. Intelligent failure-proof control system for structural vibration

    Energy Technology Data Exchange (ETDEWEB)

    Yoshida, Kazuo [Keio Univ., Yokohama (Japan). Faculty of Science and Technology; Oba, Takahiro [Keio Univ., Tokyo (Japan)

    2000-11-01

    With progress of technology in recent years, gigantism and complication such as high-rise buildings, nuclear reactors and so on have brought about new problems. Particularly, the safety and the reliability for damages in abnormal situations have become more important. Intelligent control systems which can judge whether the situation is normal or abnormal at real time and cope with these situations suitably are demanded. In this study, Cubic Neural Network (CNN) is adopted, which consists of the controllers possessing cubically some levels of information abstracting. In addition to the usual quantitative control, the qualitative control is used for the abnormal situations. And, by selecting a suitable controller, CNN can cope with the abnormal situation. In order to confirm the effectiveness of this system, the structural vibration control problems with sensory failure and elasto-plastic response are dealt with. As a result of simulations, it was demonstrated that CNN can cope with unexpected abnormal situations which are not considered in learning. (author)

  8. Intelligent failure-proof control system for structural vibration

    International Nuclear Information System (INIS)

    Yoshida, Kazuo

    2000-01-01

    With progress of technology in recent years, gigantism and complication such as high-rise buildings, nuclear reactors and so on have brought about new problems. Particularly, the safety and the reliability for damages in abnormal situations have become more important. Intelligent control systems which can judge whether the situation is normal or abnormal at real time and cope with these situations suitably are demanded. In this study, Cubic Neural Network (CNN) is adopted, which consists of the controllers possessing cubically some levels of information abstracting. In addition to the usual quantitative control, the qualitative control is used for the abnormal situations. And, by selecting a suitable controller, CNN can cope with the abnormal situation. In order to confirm the effectiveness of this system, the structural vibration control problems with sensory failure and elasto-plastic response are dealt with. As a result of simulations, it was demonstrated that CNN can cope with unexpected abnormal situations which are not considered in learning. (author)

  9. Design on intelligent gateway technique in home network

    Science.gov (United States)

    Hu, Zhonggong; Feng, Xiancheng

    2008-12-01

    Based on digitization, multimedia, mobility, wide band, real-time interaction and so on,family networks, because can provide diverse and personalized synthesis service in information, correspondence work, entertainment, education and health care and so on, are more and more paid attention by the market. The family network product development has become the focus of the related industry. In this paper,the concept of the family network and the overall reference model of the family network are introduced firstly.Then the core techniques and the correspondence standard related with the family network are proposed.The key analysis is made for the function of family gateway, the function module of the software,the key technologies to client side software architecture and the trend of development of the family network entertainment seeing and hearing service and so on. Product present situation of the family gateway and the future trend of development, application solution of the digital family service are introduced. The development of the family network product bringing about the digital family network industry is introduced finally.It causes the development of software industries,such as communication industry,electrical appliances industry, computer and game and so on.It also causes the development of estate industry.

  10. Distributed stability control using intelligent voltage-margin relay

    Energy Technology Data Exchange (ETDEWEB)

    Wiszniewski, A.; Rebizant, W. [Wroclaw Univ. of Technology (Poland); Klimek, A. [Powertech Labs Inc., Surrey, BC (Canada)

    2010-07-01

    This paper presented an intelligent relay that operates if the load to source impedance ratio decreases to a level that is dangerously close to the stability limit, which leads to power system blackouts. The intelligent voltage-margin/difference relay installed at receiving substations automatically initiates action if the voltage stability margin drops to a dangerously low level. The relay decides if the tap changing devices are to be blocked and if under-voltage load shedding should be initiated, thereby mitigating an evolving instability. The intelligent relay has two levels of operation. At the first stage, which corresponds to the higher load to source impedance ratio, the relay initiates blocking of the tap changer. At the second stage, corresponding to the lower source to load impedance ratio, load shedding is initiated. The relay operates when the load to source impedance ratio reaches a certain predetermined level, but it does not depend either on the level of the source voltage or on the difference of source and load impedance phase angles. The algorithm for the relay is relatively simple and uses only locally available signals. Consequently, the transformer is well controlled to eliminate the cases of voltage instability. 6 refs., 7 figs.

  11. Sensorless speed control of switched reluctance motor using brain emotional learning based intelligent controller

    International Nuclear Information System (INIS)

    Dehkordi, Behzad Mirzaeian; Parsapoor, Amir; Moallem, Mehdi; Lucas, Caro

    2011-01-01

    In this paper, a brain emotional learning based intelligent controller (BELBIC) is developed to control the switched reluctance motor (SRM) speed. Like other intelligent controllers, BELBIC is model free and is suitable to control nonlinear systems. Motor parameter changes, operating point changes, measurement noise, open circuit fault in one phase and asymmetric phases in SRM are also simulated to show the robustness and superior performance of BELBIC. To compare the BELBIC performance with other intelligent controllers, Fuzzy Logic Controller (FLC) is developed. System responses with BELBIC and FLC are compared. Furthermore, by eliminating the position sensor, a method is introduced to estimate the rotor position. This method is based on Adaptive Neuro Fuzzy Inference System (ANFIS). The estimator inputs are four phase flux linkages. Suggested rotor position estimator is simulated in different conditions. Simulation results confirm the accurate rotor position estimation in different loads and speeds.

  12. Sensorless speed control of switched reluctance motor using brain emotional learning based intelligent controller

    Energy Technology Data Exchange (ETDEWEB)

    Dehkordi, Behzad Mirzaeian, E-mail: mirzaeian@eng.ui.ac.i [Department of Electrical Engineering, Faculty of Engineering, University of Isfahan, Hezar-Jerib St., Postal code 8174673441, Isfahan (Iran, Islamic Republic of); Parsapoor, Amir, E-mail: amirparsapoor@yahoo.co [Department of Electrical Engineering, Faculty of Engineering, University of Isfahan, Hezar-Jerib St., Postal code 8174673441, Isfahan (Iran, Islamic Republic of); Moallem, Mehdi, E-mail: moallem@cc.iut.ac.i [Department of Electrical Engineering, Isfahan University of Technology, Isfahan (Iran, Islamic Republic of); Lucas, Caro, E-mail: lucas@ut.ac.i [Centre of Excellence for Control and Intelligent Processing, Electrical and Computer Engineering Faculty, College of Engineering, University of Tehran, Tehran (Iran, Islamic Republic of)

    2011-01-15

    In this paper, a brain emotional learning based intelligent controller (BELBIC) is developed to control the switched reluctance motor (SRM) speed. Like other intelligent controllers, BELBIC is model free and is suitable to control nonlinear systems. Motor parameter changes, operating point changes, measurement noise, open circuit fault in one phase and asymmetric phases in SRM are also simulated to show the robustness and superior performance of BELBIC. To compare the BELBIC performance with other intelligent controllers, Fuzzy Logic Controller (FLC) is developed. System responses with BELBIC and FLC are compared. Furthermore, by eliminating the position sensor, a method is introduced to estimate the rotor position. This method is based on Adaptive Neuro Fuzzy Inference System (ANFIS). The estimator inputs are four phase flux linkages. Suggested rotor position estimator is simulated in different conditions. Simulation results confirm the accurate rotor position estimation in different loads and speeds.

  13. Auto-correlation based intelligent technique for complex waveform presentation and measurement

    International Nuclear Information System (INIS)

    Rana, K P S; Singh, R; Sayann, K S

    2009-01-01

    Waveform acquisition and presentation forms the heart of many measurement systems. Particularly, data acquisition and presentation of repeating complex signals like sine sweep and frequency-modulated signals introduces the challenge of waveform time period estimation and live waveform presentation. This paper presents an intelligent technique, for waveform period estimation of both the complex and simple waveforms, based on the normalized auto-correlation method. The proposed technique is demonstrated using LabVIEW based intensive simulations on several simple and complex waveforms. Implementation of the technique is successfully demonstrated using LabVIEW based virtual instrumentation. Sine sweep vibration waveforms are successfully presented and measured for electrodynamic shaker system generated vibrations. The proposed method is also suitable for digital storage oscilloscope (DSO) triggering, for complex signals acquisition and presentation. This intelligence can be embodied into the DSO, making it an intelligent measurement system, catering wide varieties of the waveforms. The proposed technique, simulation results, robustness study and implementation results are presented in this paper.

  14. Advanced and intelligent control in power electronics and drives

    CERN Document Server

    Blaabjerg, Frede; Rodríguez, José

    2014-01-01

    Power electronics and variable frequency drives are continuously developing multidisciplinary fields in electrical engineering, and it is practically not possible to write a book covering the entire area by one individual specialist. Especially by taking account the recent fast development in the neighboring fields like control theory, computational intelligence and signal processing, which all strongly influence new solutions in control of power electronics and drives. Therefore, this book is written by individual key specialist working on the area of modern advanced control methods which penetrates current implementation of power converters and drives. Although some of the presented methods are still not adopted by industry, they create new solutions with high further research and application potential. The material of the book is presented in the following three parts: Part I: Advanced Power Electronic Control in Renewable Energy Sources (Chapters 1-4), Part II: Predictive Control of Power Converters and D...

  15. Heat input control in coke ovens battery using artificial intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Kumar, R.; Kannan, C.; Sistla, S.; Kumar, D. [Tata Steel, Jamshedpur (India)

    2005-07-01

    Controlled heating is very essential for producing coke with certain desired properties. Controlled heating involves controlling the heat input into the battery dynamically depending on the various process parameters like current battery temperature, the set point of battery temperature, moisture in coal, ambient temperature, coal fineness, cake breakage etc. An artificial intelligence (AI) based heat input control has been developed in which currently some of the above mentioned process parameters are considered and used for calculating the pause time which is applied between reversal during the heating process. The AI based model currently considers 3 input variables, temperature deviation history, current deviation of the battery temperature from the target temperature and the actual heat input into the battery. Work is in progress to control the standard deviation of coke end temperature using this model. The new system which has been developed in-house has replaced Hoogovens supplied model. 7 figs.

  16. The NASA F-15 Intelligent Flight Control Systems: Generation II

    Science.gov (United States)

    Buschbacher, Mark; Bosworth, John

    2006-01-01

    The Second Generation (Gen II) control system for the F-15 Intelligent Flight Control System (IFCS) program implements direct adaptive neural networks to demonstrate robust tolerance to faults and failures. The direct adaptive tracking controller integrates learning neural networks (NNs) with a dynamic inversion control law. The term direct adaptive is used because the error between the reference model and the aircraft response is being compensated or directly adapted to minimize error without regard to knowing the cause of the error. No parameter estimation is needed for this direct adaptive control system. In the Gen II design, the feedback errors are regulated with a proportional-plus-integral (PI) compensator. This basic compensator is augmented with an online NN that changes the system gains via an error-based adaptation law to improve aircraft performance at all times, including normal flight, system failures, mispredicted behavior, or changes in behavior resulting from damage.

  17. Intelligent Home Control System Based on Single Chip Microcomputer

    Science.gov (United States)

    Yang, Libo

    2017-12-01

    Intelligent home as a way to achieve the realization of the family information has become an important part of the development of social information, Internet of Things because of its huge application prospects, will be smart home industry in the development process of a more realistic breakthrough in the smart home industry development has great significance. This article is based on easy to implement, easy to operate, close to the use of the design concept, the use of STC89C52 microcontroller as the control core for the control terminal, and including infrared remote control, buttons, Web interface, including multiple control sources to control household appliances. The second chapter of this paper describes the design of the hardware and software part of the specific implementation, the fifth chapter is based on the design of a good function to build a specific example of the environment.

  18. New Intelligent Transmission Concept for Hybrid Mobile Robot Speed Control

    Directory of Open Access Journals (Sweden)

    Nazim Mir-Nasiri

    2008-11-01

    Full Text Available This paper presents a new concept of a mobile robot speed control by using two degree of freedom gear transmission. The developed intelligent speed controller utilizes a gear box which comprises of epicyclic gear train with two inputs, one coupled with the engine shaft and another with the shaft of a variable speed dc motor. The net output speed is a combination of the two input speeds and is governed by the transmission ratio of the planetary gear train. This new approach eliminates the use of a torque converter which is otherwise an indispensable part of all available automatic transmissions, thereby reducing the power loss that occurs in the box during the fluid coupling. By gradually varying the speed of the dc motor a stepless transmission has been achieved. The other advantages of the developed controller are pulling over and reversing the vehicle, implemented by intelligent mixing of the dc motor and engine speeds. This approach eliminates traditional braking system in entire vehicle design. The use of two power sources, IC engine and battery driven DC motor, utilizes the modern idea of hybrid vehicles. The new mobile robot speed controller is capable of driving the vehicle even in extreme case of IC engine failure, for example, due to gas depletion..

  19. New Intelligent Transmission Concept for Hybrid Mobile Robot Speed Control

    Directory of Open Access Journals (Sweden)

    Nazim Mir-Nasiri

    2005-09-01

    Full Text Available This paper presents a new concept of a mobile robot speed control by using two degree of freedom gear transmission. The developed intelligent speed controller utilizes a gear box which comprises of epicyclic gear train with two inputs, one coupled with the engine shaft and another with the shaft of a variable speed dc motor. The net output speed is a combination of the two input speeds and is governed by the transmission ratio of the planetary gear train. This new approach eliminates the use of a torque converter which is otherwise an indispensable part of all available automatic transmissions, thereby reducing the power loss that occurs in the box during the fluid coupling. By gradually varying the speed of the dc motor a stepless transmission has been achieved. The other advantages of the developed controller are pulling over and reversing the vehicle, implemented by intelligent mixing of the dc motor and engine speeds. This approach eliminates traditional braking system in entire vehicle design. The use of two power sources, IC engine and battery driven DC motor, utilizes the modern idea of hybrid vehicles. The new mobile robot speed controller is capable of driving the vehicle even in extreme case of IC engine failure, for example, due to gas depletion.

  20. Finite-element-model updating using computational intelligence techniques applications to structural dynamics

    CERN Document Server

    Marwala, Tshilidzi

    2010-01-01

    Finite element models (FEMs) are widely used to understand the dynamic behaviour of various systems. FEM updating allows FEMs to be tuned better to reflect measured data and may be conducted using two different statistical frameworks: the maximum likelihood approach and Bayesian approaches. Finite Element Model Updating Using Computational Intelligence Techniques applies both strategies to the field of structural mechanics, an area vital for aerospace, civil and mechanical engineering. Vibration data is used for the updating process. Following an introduction a number of computational intelligence techniques to facilitate the updating process are proposed; they include: • multi-layer perceptron neural networks for real-time FEM updating; • particle swarm and genetic-algorithm-based optimization methods to accommodate the demands of global versus local optimization models; • simulated annealing to put the methodologies into a sound statistical basis; and • response surface methods and expectation m...

  1. 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.

  2. 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...

  3. 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…

  4. Increasing the Intelligence of Virtual Sales Assistants through Knowledge Modeling Techniques

    OpenAIRE

    Molina, Martin

    2001-01-01

    Shopping agents are web-based applications that help consumers to find appropriate products in the context of e-commerce. In this paper we argue about the utility of advanced model-based techniques that recently have been proposed in the fields of Artificial Intelligence and Knowledge Engineering, in order to increase the level of support provided by this type of applications. We illustrate this approach with a virtual sales assistant that dynamically configures a product according to the nee...

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

    Science.gov (United States)

    Wroblewski, David [Mentor, OH; Katrompas, Alexander M [Concord, OH; Parikh, Neel J [Richmond Heights, OH

    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.

  6. 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.

  7. Dynamic Intelligent Feedback Scheduling in Networked Control Systems

    Directory of Open Access Journals (Sweden)

    Hui-ying Chen

    2013-01-01

    Full Text Available For the networked control system with limited bandwidth and flexible workload, a dynamic intelligent feedback scheduling strategy is proposed. Firstly, a monitor is used to acquire the current available network bandwidth. Then, the new available bandwidth in the next interval is predicted by using LS_SVM approach. At the same time, the dynamic performance indices of all control loops are obtained with a two-dimensional fuzzy logic modulator. Finally, the predicted network bandwidth is dynamically allocated by the bandwidth manager and the priority allocator in terms of the loops' dynamic performance indices. Simulation results show that the sampling periods and priorities of control loops are adjusted timely according to the network workload condition and the dynamic performance of control loops, which make the system running in the optimal state all the time.

  8. Advances in Intelligent Control Systems and Computer Science

    CERN Document Server

    2013-01-01

    The conception of real-time control networks taking into account, as an integrating approach, both the specific aspects of information and knowledge processing and the dynamic and energetic particularities of physical processes and of communication networks is representing one of the newest scientific and technological challenges. The new paradigm of Cyber-Physical Systems (CPS) reflects this tendency and will certainly change the evolution of the technology, with major social and economic impact. This book presents significant results in the field of process control and advanced information and knowledge processing, with applications in the fields of robotics, biotechnology, environment, energy, transportation, et al.. It introduces intelligent control concepts and strategies as well as real-time implementation aspects for complex control approaches. One of the sections is dedicated to the complex problem of designing software systems for distributed information processing networks. Problems as complexity an...

  9. Intelligent control of diesel generators using gain-scheduling

    DEFF Research Database (Denmark)

    Mai, Christian; Jepsen, Kasper; Yang, Zhenyu

    2014-01-01

    The development of an intelligent control solution for a wide range of diesel generators is discussed. Compared with most existing solutions, the advantages of the proposed solution lie in two folds: (i) The proposed control has the plug-and-play capability which is reflected by an automatic...... recognition procedure when it is plugged into a specific diesel generator, such that some extensive manual-tuning of the installed controller can be significantly reduced; (ii) The proposed control has an real-time adaptability by using the online external load estimation, such that the integrated system can...... keep a consistent performance for a wide range of operating conditions. Technically, a general nonlinear dynamic model is firstly developed based on fundamental principles of diesel generators. Then, the system parameters of this model can be identified experimentally or partially retrieved from...

  10. Intelligent Integration between Human Simulated Intelligence and Expert Control Technology for the Combustion Process of Gas Heating Furnace

    Directory of Open Access Journals (Sweden)

    Yucheng Liu

    2014-01-01

    Full Text Available Due to being poor in control quality of the combustion process of gas heating furnace, this paper explored a sort of strong robust control algorithm in order to improve the control quality of the combustion process of gas heating furnace. The paper analyzed the control puzzle in the complex combustion process of gas heating furnace, summarized the cybernetics characteristic of the complex combustion process, researched into control strategy of the uncertainty complex control process, discussed the control model of the complex process, presented a sort of intelligent integration between human-simulated intelligence and expert control technology, and constructed the control algorithm for the combustion process controlling of gas heating furnace. The simulation results showed that the control algorithm proposed in the paper is not only better in dynamic and steady quality of the combustion process, but also obvious in energy saving effect, feasible, and effective in control strategy.

  11. 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.

  12. Trading Control Intelligence for Physical Intelligence: Muscle Drives in Evolved Virtual Creatures

    DEFF Research Database (Denmark)

    Lessin, Dan; Fussell, Don; Miikkulainen, Risto

    2014-01-01

    Traditional evolved virtual creatures [12] are actuated using unevolved, uniform, invisible drives at joints between rigid segments. In contrast, this paper shows how such conven- tional actuators can be replaced by evolvable muscle drives that are a part of the creature’s physical structure....... This design is important for two reasons: First, the con- trol intelligence is made visible in the purposeful develop- ment of muscle density, orientation, attachment points, and size. Second, the complexity that needs to be evolved for the brain to control the actuators is reduced, and in some cases can...... be essentially eliminated, thus freeing brain power for higher-level functions. Such designs may thus make it pos- sible to create more complex behavior than would otherwise be achievable....

  13. Fuzzy gain scheduling of velocity PI controller with intelligent learning algorithm for reactor control

    International Nuclear Information System (INIS)

    Dong Yun Kim; Poong Hyun Seong; .

    1997-01-01

    In this research, we propose a fuzzy gain scheduler (FGS) with an intelligent learning algorithm for a reactor control. In the proposed algorithm, the gradient descent method is used in order to generate the rule bases of a fuzzy algorithm by learning. These rule bases are obtained by minimizing an objective function, which is called a performance cost function. The objective of the FGS with an intelligent learning algorithm is to generate gains, which minimize the error of system. The proposed algorithm can reduce the time and effort required for obtaining the fuzzy rules through the intelligent learning function. It is applied to reactor control of nuclear power plant (NPP), and the results are compared with those of a conventional PI controller with fixed gains. As a result, it is shown that the proposed algorithm is superior to the conventional PI controller. (author)

  14. HPT Clearance Control: Intelligent Engine Systems-Phase 1

    Science.gov (United States)

    2005-01-01

    The following work has been completed to satisfy the Phase I Deliverables for the "HPT Clearance Control" project under NASA GRC's "Intelligent Engine Systems" program: (1) Need for the development of an advanced HPT ACC system has been very clearly laid out, (2) Several existing and potential clearance control systems have been reviewed, (3) A scorecard has been developed to document the system, performance (fuel burn, range, payload, etc.), thermal, and mechanical characteristics of the existing clearance control systems, (4) Engine size and flight cycle selection for the advanced HPT ACC system has been reviewed with "large engine"/"long range mission" combination showing the most benefit, (5) A scoring criteria has been developed to tie together performance parameters for an objective, data driven comparison of competing systems, and (6) The existing HPT ACC systems have been scored based on this scoring system.

  15. Toolchain for User-Centered Intelligent Floor Heating Control

    DEFF Research Database (Denmark)

    Agesen, Mads Kronborg; Larsen, Kim Guldstrand; Mikučionis, Marius

    2016-01-01

    temperature is below the user defined target temperature, otherwise it closes for the heating in the room. The disadvantage is that the heat exchange among the rooms, outside weather conditions, weather forecast and other factors are not considered. We propose a novel model-driven approach for intelligent...... floor heating control based on a chain of tools that allow us to gather the sensor readings from the actual hardware and use the state-of-the-art controller synthesis tool UPPAAL Stratego in order to synthesise abstract control strategies that are then executed on the real hardware platform provided...... by the company Seluxit. We have built a scaled demonstrator of the system and the experimental results document a 38% to 52 % increase in user satisfaction, moreover with additional energy savings between 2% to 12%....

  16. ASSESSMENT OF A WIND TURBINE INTELLIGENT CONTROLLER FOR ENHANCED ENERGY PRODUCTION AND POLLUTION REDUCTION

    Science.gov (United States)

    This study assessed the enhanced energy production which is possible when variable-speed wind turbines are electronically controlled by an intelligent controller for efficiency optimization and performance improvement. The control system consists of three fuzzy- logic controllers...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-06-15

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

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

    International Nuclear Information System (INIS)

    Ferreira, F.J.O.; Crispim, V.R.; Silva, A.X.

    2010-01-01

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

  19. Remote Control of an Inverted Pendulum System for Intelligent Control Education

    Directory of Open Access Journals (Sweden)

    Seul Jung

    2011-08-01

    Full Text Available This paper presents a remote control task of an inverted pendulum system for intelligent control education. The inverted pendulum moving on the guided rail is required to maintain balancing while it follows the desired trajectory commanded remotely by a joystick operated by a user. Position commands for the inverted pendulum system are given by a joystick through the network. The inverted pendulum system is controlled by a neural network control method. The corresponding control results are confirmed through experimental studies.

  20. DEVELOPING A HUMAN CONTROLLED MODEL FOR SAFE ARTIFICIAL INTELLIGENCE SYSTEMS

    OpenAIRE

    KÖSE, Utku

    2018-01-01

    Artificial Intelligence is known as one of the most effective research field of nowadays and the future. But rapid rise of Artificial Intelligence and its potential to solve all real world problems autonomously, it has caused also several anxieties. Some scientists think that intelligent systems can reach to a level, which is dangerous for the humankind so because of that some precautions should be taken. So, many sub-research fields like Machine Ethics or Artificial Intelligence Safety have ...

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

    Science.gov (United States)

    Taylan, Osman

    2017-02-01

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

  2. Short-term Local Forecasting by Artificial Intelligence Techniques and Assess Related Social Effects from Heterogeneous Data

    OpenAIRE

    Gong, Bing

    2017-01-01

    This work aims to use the sophisticated artificial intelligence and statistic techniques to forecast pollution and assess its social impact. To achieve the target of the research, this study is divided into several research sub-objectives as follows: First research sub-objective: propose a framework for relocating and reconfiguring the existing pollution monitoring networks by using feature selection, artificial intelligence techniques, and information theory. Second research sub-objective: c...

  3. Univariate and multivariate forecasting of hourly solar radiation with artificial intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Sfetsos, A. [7 Pirsou Str., Athens (Greece); Coonick, A.H. [Imperial Coll. of Science Technology and Medicine, Dept. of Electrical and Electronic Engineering, London (United Kingdom)

    2000-07-01

    This paper introduces a new approach for the forecasting of mean hourly global solar radiation received by a horizontal surface. In addition to the traditional linear methods, several artificial-intelligence-based techniques are studied. These include linear, feed-forward, recurrent Elman and Radial Basis neural networks alongside the adaptive neuro-fuzzy inference scheme. The problem is examined initially for the univariate case, and is extended to include additional meteorological parameters in the process of estimating the optimum model. The results indicate that the developed artificial intelligence models predict the solar radiation time series more effectively compared to the conventional procedures based on the clearness index. The forecasting ability of some models can be further enhanced with the use of additional meteorological parameters. (Author)

  4. 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.

  5. A Real-Time Temperature Data Transmission Approach for Intelligent Cooling Control of Mass Concrete

    Directory of Open Access Journals (Sweden)

    Peng Lin

    2014-01-01

    Full Text Available The primary aim of the study presented in this paper is to propose a real-time temperature data transmission approach for intelligent cooling control of mass concrete. A mathematical description of a digital temperature control model is introduced in detail. Based on pipe mounted and electrically linked temperature sensors, together with postdata handling hardware and software, a stable, real-time, highly effective temperature data transmission solution technique is developed and utilized within the intelligent mass concrete cooling control system. Once the user has issued the relevant command, the proposed programmable logic controllers (PLC code performs all necessary steps without further interaction. The code can control the hardware, obtain, read, and perform calculations, and display the data accurately. Hardening concrete is an aggregate of complex physicochemical processes including the liberation of heat. The proposed control system prevented unwanted structural change within the massive concrete blocks caused by these exothermic processes based on an application case study analysis. In conclusion, the proposed temperature data transmission approach has proved very useful for the temperature monitoring of a high arch dam and is able to control thermal stresses in mass concrete for similar projects involving mass concrete.

  6. 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.

  7. Embedded intelligent adaptive PI controller for an electromechanical system.

    Science.gov (United States)

    El-Nagar, Ahmad M

    2016-09-01

    In this study, an intelligent adaptive controller approach using the interval type-2 fuzzy neural network (IT2FNN) is presented. The proposed controller consists of a lower level proportional - integral (PI) controller, which is the main controller and an upper level IT2FNN which tuning on-line the parameters of a PI controller. The proposed adaptive PI controller based on IT2FNN (API-IT2FNN) is implemented practically using the Arduino DUE kit for controlling the speed of a nonlinear DC motor-generator system. The parameters of the IT2FNN are tuned on-line using back-propagation algorithm. The Lyapunov theorem is used to derive the stability and convergence of the IT2FNN. The obtained experimental results, which are compared with other controllers, demonstrate that the proposed API-IT2FNN is able to improve the system response over a wide range of system uncertainties. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

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

    International Nuclear Information System (INIS)

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

    2011-01-01

    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.

  9. The implementation of artificial intelligence in control systems

    International Nuclear Information System (INIS)

    Koul, R.; Weygand, D.P.

    1987-01-01

    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

  10. Robust Bio-Signal Based Control of an Intelligent Wheelchair

    Directory of Open Access Journals (Sweden)

    Dongyi Chen

    2013-09-01

    Full Text Available In this paper, an adaptive human-machine interaction (HMI method that is based on surface electromyography (sEMG signals is proposed for the hands-free control of an intelligent wheelchair. sEMG signals generated by the facial movements are obtained by a convenient dry electrodes sensing device. After the signals features are extracted from the autoregressive model, control data samples are updated and trained by an incremental online learning algorithm in real-time. Experimental results show that the proposed method can significantly improve the classification accuracy and training speed. Moreover, this method can effectively reduce the influence of muscle fatigue during a long time operation of sEMG-based HMI.

  11. Intelligent Hybrid Control Strategy for Trajectory Tracking of Robot Manipulators

    Directory of Open Access Journals (Sweden)

    Yi Zuo

    2008-01-01

    Full Text Available We address the problem of robust tracking control using a PD-plus-feedforward controller and an intelligent adaptive robust compensator for a rigid robotic manipulator with uncertain dynamics and external disturbances. A key feature of this scheme is that soft computer methods are used to learn the upper bound of system uncertainties and adjust the width of the boundary layer base. In this way, the prior knowledge of the upper bound of the system uncertainties does need not to be required. Moreover, chattering can be effectively eliminated, and asymptotic error convergence can be guaranteed. Numerical simulations and experiments of two-DOF rigid robots are presented to show effectiveness of the proposed scheme.

  12. Intelligent distributed voltage control system for smart grid application

    Energy Technology Data Exchange (ETDEWEB)

    Sajadi, Amirhossein [Warsaw Univ. of Technology (Poland); Ariatabar, Mitra [RWTH Aachen Univ. (Germany)

    2012-07-01

    Increasing penetration of the renewable energy source (RES) units in distribution networks particularly due to nonlinear and unpredictable nature of renewable units brings up new challenges in different aspects of electricity network, which leads to more complex power systems. Multi-agent system is consisting of agents which are capable to perceive environment that they are located in and to reacts with each other by communication infrastructure in order to achieve overall goals. In this paper an approach to control the voltage based on in the power distribution system is proposed and discussed. Therefore, a multi-agent system has been integrated with artificial intelligence to come up with fuzzy multi-agent based system. The proposed control scheme is deployed to a smart distribution system consisting distribution generation units, modelled in MATLAB/Simulink, to evaluate its effectiveness. The simulation results show how proposed system can regulate voltage in smart distribution feeders. (orig.)

  13. An intelligent readout controller for Fastbus, the Fermilab FSCC

    International Nuclear Information System (INIS)

    Bowden, M.; Kwarciany, R.; Urish, J.

    1990-01-01

    This paper reports on the Fermilab FASTBUS Smart Crate Controller which is intended as a fast, versatile, and cost effective solution for the readout of FASTBUS crates. The on-board 68020 provides intelligence and a programmable microsequencer controls the main readout path. The FSCC supports communication via serial RS 232, Ethernet, and FASTBUS. The main readout path may be programmed for a variety of protocols. Currently, RS 422, VDAS, ECL line, and fiber-optic interfaces are being developed. Hardware interfacing is via the FASTBUS auxiliary connector using a personality card. Provision is made for some on-board formatting and processing of data. The 68020 may sample the data, also headers and word counts may be inserted into the data stream. Data is buffered by FIFOs to allow asynchronous readout

  14. Intelligent Heuristic Techniques for the Optimization of the Transshipment and Storage Operations at Maritime Container Terminals

    Directory of Open Access Journals (Sweden)

    Christopher Expósito-Izquierdo

    2017-02-01

    Full Text Available This paper summarizes the main contributions of the Ph.D. thesis of Christopher Exp\\'osito-Izquierdo. This thesis seeks to develop a wide set of intelligent heuristic and meta-heuristic algorithms aimed at solving some of the most highlighted optimization problems associated with the transshipment and storage of containers at conventional maritime container terminals. Under the premise that no optimization technique can have a better performance than any other technique under all possible assumptions, the main point of interest in the domain of maritime logistics is to propose optimization techniques superior in terms of effectiveness and computational efficiency to previous proposals found in the scientific literature when solving individual optimization problems under realistic scenarios. Simultaneously, these optimization techniques should be enough competitive to be potentially implemented in practice. }}

  15. A Smart Sensor Data Transmission Technique for Logistics and Intelligent Transportation Systems

    OpenAIRE

    Kyunghee Sun; Intae Ryoo

    2018-01-01

    When it comes to Internet of Things systems that include both a logistics system and an intelligent transportation system, a smart sensor is one of the key elements to collect useful information whenever and wherever necessary. This study proposes the Smart Sensor Node Group Management Medium Access Control Scheme designed to group smart sensor devices and collect data from them efficiently. The proposed scheme performs grouping of portable sensor devices connected to a system depending on th...

  16. Microgrid central controller development and hierarchical control implemetation in the intelligent microgrid lab of Aalborg University

    OpenAIRE

    Meng, Lexuan; Savaghebi, Mehdi; Andrade, Fabio; Vasquez Quintero, Juan Carlos; Guerrero, Josep M.; Graells Sobré, Moisès

    2015-01-01

    This paper presents the development of a microgrid central controller in an inverter-based intelligent microgrid (iMG) lab in Aalborg University, Denmark. The iMG lab aims to provide a flexible experimental platform for comprehensive studies of microgrids. The complete control system applied in this lab is based on the hierarchical control scheme for microgrids and includes primary, secondary and tertiary control. The structure of the lab, including the lab facilities, configurations and comm...

  17. Intelligent control schemes applied to Automatic Generation Control

    Directory of Open Access Journals (Sweden)

    Dingguo Chen

    2016-04-01

    Full Text Available Integrating ever increasing amount of renewable generating resources to interconnected power systems has created new challenges to the safety and reliability of today‟s power grids and posed new questions to be answered in the power system modeling, analysis and control. Automatic Generation Control (AGC must be extended to be able to accommodate the control of renewable generating assets. In addition, AGC is mandated to operate in accordance with the NERC‟s Control Performance Standard (CPS criteria, which represent a greater flexibility in relaxing the control of generating resources and yet assuring the stability and reliability of interconnected power systems when each balancing authority operates in full compliance. Enhancements in several aspects to the traditional AGC must be made in order to meet the aforementioned challenges. It is the intention of this paper to provide a systematic, mathematical formulation for AGC as a first attempt in the context of meeting the NERC CPS requirements and integrating renewable generating assets, which has not been seen reported in the literature to the best knowledge of the authors. Furthermore, this paper proposes neural network based predictive control schemes for AGC. The proposed controller is capable of handling complicated nonlinear dynamics in comparison with the conventional Proportional Integral (PI controller which is typically most effective to handle linear dynamics. The neural controller is designed in such a way that it has the capability of controlling the system generation in the relaxed manner so the ACE is controlled to a desired range instead of driving it to zero which would otherwise increase the control effort and cost; and most importantly the resulting system control performance meets the NERC CPS requirements and/or the NERC Balancing Authority’s ACE Limit (BAAL compliance requirements whichever are applicable.

  18. Genetic Fuzzy Trees for Intelligent Control of Unmanned Combat Aerial Vehicles

    Science.gov (United States)

    Ernest, Nicholas D.

    Fuzzy Logic Control is a powerful tool that has found great success in a variety of applications. This technique relies less on complex mathematics and more "expert knowledge" of a system to bring about high-performance, resilient, and efficient control through linguistic classification of inputs and outputs and if-then rules. Genetic Fuzzy Systems (GFSs) remove the need of this expert knowledge and instead rely on a Genetic Algorithm (GA) and have similarly found great success. However, the combination of these methods suffer severely from scalability; the number of rules required to control the system increases exponentially with the number of states the inputs and outputs can take. Therefor GFSs have thus far not been applicable to complex, artificial intelligence type problems. The novel Genetic Fuzzy Tree (GFT) method breaks down complex problems hierarchically, makes sub-decisions when possible, and thus greatly reduces the burden on the GA. This development significantly changes the field of possible applications for GFSs. Within this study, this is demonstrated through applying this technique to a difficult air combat problem. Looking forward to an autonomous Unmanned Combat Aerial Vehicle (UCAV) in the 2030 time-frame, it becomes apparent that the mission, flight, and ground controls will utilize the emerging paradigm of Intelligent Systems (IS); namely, the ability to learn, adapt, exhibit robustness in uncertain situations, make sense of the data collected in real-time and extrapolate when faced with scenarios significantly different from those used in training. LETHA (Learning Enhanced Tactical Handling Algorithm) was created to develop intelligent controllers for these advanced unmanned craft as the first GFT. A simulation space referred to as HADES (Hoplological Autonomous Defend and Engage Simulation) was created in which LETHA can train the UCAVs. Equipped with advanced sensors, a limited supply of Self-Defense Missiles (SDMs), and a recharging

  19. Applicability of statistical process control techniques

    NARCIS (Netherlands)

    Schippers, W.A.J.

    1998-01-01

    This paper concerns the application of Process Control Techniques (PCTs) for the improvement of the technical performance of discrete production processes. Successful applications of these techniques, such as Statistical Process Control Techniques (SPC), can be found in the literature. However, some

  20. A novel intelligent control of HVAC system in smart microgrid

    Directory of Open Access Journals (Sweden)

    Seyed Mehdi Hakimi

    2017-09-01

    Full Text Available Heating systems have played an important role in building energy and comfort management. This paper set forth a novel intelligent residential heating system controller that has smart grid functionality. In smart grid, demand response systems now have the ability to not only engage commercial and industrial customers, but also the individual residential customers. Additionally, the ability exists to have automated control systems which operate on an availability of renewable energy and welfare of customers. In this paper one possible implementation of an active controller will be examined. An active controller operates by responding to a combination of internal set points and external signal from local control entity. The optimization objective of the heating systems management was to minimize the cost of smart microgrid, minimize the size of smart microgrid units, minimize import energy from distribution grid and maximize reliability of smart microgrid. This means that, smart heating system and renewable energy can work well together and their individual benefits can be added together when used in combination. Simulation studies are used to demonstrate the capability on the proposed heating system controller on the planning of a smart microgrid system.

  1. The Case for Intelligent Propulsion Control for Fast Engine Response

    Science.gov (United States)

    Litt, Jonathan S.; Frederick, Dean K.; Guo, Ten-Huei

    2009-01-01

    Damaged aircraft have occasionally had to rely solely on thrust to maneuver as a consequence of losing hydraulic power needed to operate flight control surfaces. The lack of successful landings in these cases inspired research into more effective methods of utilizing propulsion-only control. That research demonstrated that one of the major contributors to the difficulty in landing is the slow response of the engines as compared to using traditional flight control. To address this, research is being conducted into ways of making the engine more responsive under emergency conditions. This can be achieved by relaxing controller limits, adjusting schedules, and/or redesigning the regulators to increase bandwidth. Any of these methods can enable faster response at the potential expense of engine life and increased likelihood of stall. However, an example sensitivity analysis revealed a complex interaction of the limits and the difficulty in predicting the way to achieve the fastest response. The sensitivity analysis was performed on a realistic engine model, and demonstrated that significantly faster engine response can be achieved compared to standard Bill of Material control. However, the example indicates the need for an intelligent approach to controller limit adjustment in order for the potential to be fulfilled.

  2. Dealing with distributed intelligence in monitoring and control systems

    International Nuclear Information System (INIS)

    McLaren, R.A.

    1981-01-01

    The Euorpean Hybrid Spectrometer is built up of many individual detectors, each having widely varying monitoring and control requirements. With the advent of cheap microprocessor systems a shift from the concept of a single monitoring and control computer of that of distributed intelligent controllers has been economically feasible. A detector designer can now thoroughly test and debug a complete monitoring and control system on a local, dedicated micro-computer, while during operation, the central computer can be relieved of many simple repetitive tasks. Rapidly, however, it has become obvious that the designers of these systems have to take into account the final operational environment and build into both the hardware and software, features allowing easy integration into a central monitoring and control chain. In addition, the problems of maintenance and enventual modification have to be taken into consideration early in the development. Examples of currently operational systems will be briefly described to demonstrate how a set of basic guidelines plus standardisation of hardware/software can minimise the problems of integration and maintenance. Based on practical experience gained in the European Hybrid Spectrometer, investigations are proceeding on various possible alternatives for future micro-computer based monitoring and control systems. (orig.)

  3. Evolutionary Computing for Intelligent Power System Optimization and Control

    DEFF Research Database (Denmark)

    This new book focuses on how evolutionary computing techniques benefit engineering research and development tasks by converting practical problems of growing complexities into simple formulations, thus largely reducing development efforts. This book begins with an overview of the optimization the...... theory and modern evolutionary computing techniques, and goes on to cover specific applications of evolutionary computing to power system optimization and control problems....

  4. High Flux Commercial Illumination Solution with Intelligent Controls

    Energy Technology Data Exchange (ETDEWEB)

    Camil Ghiu

    2012-04-30

    This report summarizes the work performed at OSRAM SYLVANIA under US Department of Energy contract DE-EE0003241 for developing a high efficiency LED-based luminaire. A novel light engine module (two versions: standard and super), power supply and luminaire mechanical parts were designed and tested. At steady-state, the luminaire luminous flux is 3156 lumens (lm), luminous efficacy 97.4 LPW and CRI (Ra) 88 at a correlated color temperature (CCT) of 3507K. When the luminaire is fitted with the super version of the light engine the efficacy reaches 130 LPW. In addition, the luminaire is provided with an intelligent control network capable of additional energy savings. The technology developed during the course of this project has been incorporated into a family of products. Recently, the first product in the family has been launched.

  5. Intelligent control system for continuous technological process of alkylation

    Science.gov (United States)

    Gebel, E. S.; Hakimov, R. A.

    2018-01-01

    Relevance of intelligent control for complex dynamic objects and processes are shown in this paper. The model of a virtual analyzer based on a neural network is proposed. Comparative analysis of mathematical models implemented in MathLab software showed that the most effective from the point of view of the reproducibility of the result is the model with seven neurons in the hidden layer, the training of which was performed using the method of scaled coupled gradients. Comparison of the data from the laboratory analysis and the theoretical model are showed that the root-mean-square error does not exceed 3.5, and the calculated value of the correlation coefficient corresponds to a "strong" connection between the values.

  6. Intelligent perception control based on a blackboard architecture

    International Nuclear Information System (INIS)

    Taibi, I.; Koenig, A.; Vacherand, F.

    1991-01-01

    In this paper, is described the intelligent perception control system GESPER which is presently equipped with a set of three cameras, a telemeter and a camera associated with a structured strip light. This system is of great interest for all our robotic applications as it is capable of autonomously planning, triggering acquisitions, integrating and interpreting multisensory data. The GESPER architecture, based on the blackboard model, provides a generic development method for indoor and outdoor perception. The modularity and the independence of the knowledge sources make the software evolving easily without breaking down the architecture. New sensors and/or new data processing can be integrated by the addition of new knowledge sources that modelize them. At present, first results are obtained in our testbed hall which simulates the nuclear plant as gives similar experimental conditions. Our ongoing research concerns the improvement of fusion algorithms and the embedding of the whole system (hardware and software) on target robots and distributed architecture

  7. Behind the Meter Grid Services: Intelligent Load Control

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Woohyun [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Katipamula, Srinivas [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lutes, Robert G. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Underhill, Ronald M. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2016-11-15

    This report describes how the intelligent load control (ILC) algorithm can be implemented to achieve peak demand reduction while minimizing impacts on occupant comfort. The algorithm was designed to minimize the additional sensors and minimum configuration requirements to enable a scalable and cost-effective implementation for both large and small-/medium-sized commercial buildings. The ILC algorithm uses an analytic hierarchy process (AHP) to dynamically prioritize the available curtailable loads based on both quantitative (deviation of zone conditions from set point) and qualitative rules (types of zone). Although the ILC algorithm described in this report was highly tailored to work with rooftop units, it can be generalized for application to other building loads such as variable-air-volume (VAV) boxes and lighting systems.

  8. Complex Formation Control of Large-Scale Intelligent Autonomous Vehicles

    Directory of Open Access Journals (Sweden)

    Ming Lei

    2012-01-01

    Full Text Available A new formation framework of large-scale intelligent autonomous vehicles is developed, which can realize complex formations while reducing data exchange. Using the proposed hierarchy formation method and the automatic dividing algorithm, vehicles are automatically divided into leaders and followers by exchanging information via wireless network at initial time. Then, leaders form formation geometric shape by global formation information and followers track their own virtual leaders to form line formation by local information. The formation control laws of leaders and followers are designed based on consensus algorithms. Moreover, collision-avoiding problems are considered and solved using artificial potential functions. Finally, a simulation example that consists of 25 vehicles shows the effectiveness of theory.

  9. Application of artificial intelligence to radiation control, (1)

    International Nuclear Information System (INIS)

    Kimura, Yoshitaka; Hasegawa, Keisuke; Ikezawa, Yoshio

    1990-01-01

    Recently artificial intelligence (AI) which has functions of our interpretations and judgments has been applied to various fields of science. In the first application of AI to the transport procedure of the radioactive material, a prototype of expert system was developed with UTI-LISP programming language to appropriately classify mainly the packages and packagings according to regulations for the safe transport of radioactive material. Classification of the packages and packagings for the consignment is mainly determined from input informations such as radionuclides, its activities, states and conveyances through a forward reasoning method of the expert system. The rationalization of practice on our interpretations and judgments for transport of radioactive material including uniformity and reliability of our decision were confirmed as the result of an application to radiation control. (author)

  10. Nonlinear Analysis and Intelligent Control of Integrated Vehicle Dynamics

    Directory of Open Access Journals (Sweden)

    C. Huang

    2014-01-01

    Full Text Available With increasing and more stringent requirements for advanced vehicle integration, including vehicle dynamics and control, traditional control and optimization strategies may not qualify for many applications. This is because, among other factors, they do not consider the nonlinear characteristics of practical systems. Moreover, the vehicle wheel model has some inadequacies regarding the sideslip angle, road adhesion coefficient, vertical load, and velocity. In this paper, an adaptive neural wheel network is introduced, and the interaction between the lateral and vertical dynamics of the vehicle is analyzed. By means of nonlinear analyses such as the use of a bifurcation diagram and the Lyapunov exponent, the vehicle is shown to exhibit complicated motions with increasing forward speed. Furthermore, electric power steering (EPS and active suspension system (ASS, which are based on intelligent control, are used to reduce the nonlinear effect, and a negotiation algorithm is designed to manage the interdependences and conflicts among handling stability, driving smoothness, and safety. Further, a rapid control prototype was built using the hardware-in-the-loop simulation platform dSPACE and used to conduct a real vehicle test. The results of the test were consistent with those of the simulation, thereby validating the proposed control.

  11. Development of an intelligent controller for power generators

    International Nuclear Information System (INIS)

    Maxted, Clive; Waller, Winston

    2005-01-01

    This paper is a description of the development of an embedded controller for high power industrial diesel generators. The aim of the project was to replace the existing discrete logic design by an intelligent versatile and user configurable control system. A prototype embedded PC controlled system was developed, capable of fully replacing the existing system, with a colour TFT display and keypad. Features include fully automatic generator control as before with status and alarm display and monitoring of engine parameters, along with data logging, remote communications and a means of analysing data. The unit was tested on the bench and on diesel generators for the core controlling functionality to prove compliance with the specifications. The results of the testing proved the unit's suitability as a replacement for the existing system in its intended environment. The significance of this study is that a low cost replacement solution has been found for an industrial application by transferring modern technological knowledge to a small business. The company are now able to build on the design and take it into production, reducing servicing and production costs

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

    Science.gov (United States)

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

    2017-01-01

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

  13. Solving Multi-Pollutant Emission Dispatch Problem Using Computational Intelligence Technique

    Directory of Open Access Journals (Sweden)

    Nur Azzammudin Rahmat

    2016-06-01

    Full Text Available Economic dispatch is a crucial process conducted by the utilities to correctly determine the satisfying amount of power to be generated and distributed to the consumers. During the process, the utilities also consider pollutant emission as the consequences of fossil-fuel consumption. Fossil-fuel includes petroleum, coal, and natural gas; each has its unique chemical composition of pollutants i.e. sulphur oxides (SOX, nitrogen oxides (NOX and carbon oxides (COX. This paper presents multi-pollutant emission dispatch problem using computational intelligence technique. In this study, a novel emission dispatch technique is formulated to determine the amount of the pollutant level. It utilizes a pre-developed optimization technique termed as differential evolution immunized ant colony optimization (DEIANT for the emission dispatch problem. The optimization results indicated high level of COX level, regardless of any type of fossil fuel consumed.

  14. An Intelligent Harmonic Synthesis Technique for Air-Gap Eccentricity Fault Diagnosis in Induction Motors

    Science.gov (United States)

    Li, De Z.; Wang, Wilson; Ismail, Fathy

    2017-11-01

    Induction motors (IMs) are commonly used in various industrial applications. To improve energy consumption efficiency, a reliable IM health condition monitoring system is very useful to detect IM fault at its earliest stage to prevent operation degradation, and malfunction of IMs. An intelligent harmonic synthesis technique is proposed in this work to conduct incipient air-gap eccentricity fault detection in IMs. The fault harmonic series are synthesized to enhance fault features. Fault related local spectra are processed to derive fault indicators for IM air-gap eccentricity diagnosis. The effectiveness of the proposed harmonic synthesis technique is examined experimentally by IMs with static air-gap eccentricity and dynamic air-gap eccentricity states under different load conditions. Test results show that the developed harmonic synthesis technique can extract fault features effectively for initial IM air-gap eccentricity fault detection.

  15. Artificial Intelligence (AI techniques to analyze the determinants attributes in housing prices

    Directory of Open Access Journals (Sweden)

    Julia M. Núñez Tabale

    2016-12-01

    Full Text Available The econometric approach to obtain the value of a property began with hedonic modelling, which were based on a set of property attributes, internal or external, associated to each particular dwelling. The final sale value can be estimated, and also the marginal prices of each exogenous explanatory variable. A good alternative to the hedonic approach is based on several Artificial Intelligence (AI techniques, such as artificial neural networks (ANN, these tend to be more precise. Both methodologies are compared, and a case study is developed using data from Seville, the larger town in the South of Spain.

  16. fuzzy control technique fuzzy control technique applied to modified

    African Journals Online (AJOL)

    eobe

    epidemiological parameters) to the malaria model simulated by 9 fully ... The Mamdani controllers use a standard max-min inference process and a fast centre of min inference process and a ... Numerical results obtained using Matlab 2008a software software .... simulation environment using the 9 ODE Simulators. The test ...

  17. Design And Implementation of Dsp-Based Intelligent Controller For Automobile Braking System

    OpenAIRE

    S.N. Sidek and M.J.E. Salami

    2012-01-01

    An intelligent braking system has great potential applications especially, in developed countries where research on smart vehicle and intelligent highways are receiving ample attention. The system when integrated with other subsystems like automatic traction control, intelligent throttle, and auto cruise systems, etc will result in smart vehicle maneuver. The driver at the end of the day will become the passenger, safety accorded the highest priority and the journey optimized in term of time ...

  18. Modern control techniques for accelerators

    International Nuclear Information System (INIS)

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

    1984-01-01

    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: the microprocessor and 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

  19. Sensor guided control and navigation with intelligent machines. Final technical report

    Energy Technology Data Exchange (ETDEWEB)

    Ghosh, Bijoy K.

    2001-03-26

    This item constitutes the final report on ''Visionics: An integrated approach to analysis and design of intelligent machines.'' The report discusses dynamical systems approach to problems in robust control of possibly time-varying linear systems, problems in vision and visually guided control, and, finally, applications of these control techniques to intelligent navigation with a mobile platform. Robust design of a controller for a time-varying system essentially deals with the problem of synthesizing a controller that can adapt to sudden changes in the parameters of the plant and can maintain stability. The approach presented is to design a compensator that simultaneously stabilizes each and every possible mode of the plant as the parameters undergo sudden and unexpected changes. Such changes can in fact be detected by a visual sensor and, hence, visually guided control problems are studied as a natural consequence. The problem here is to detect parameters of the plant and maintain st ability in the closed loop using a ccd camera as a sensor. The main result discussed in the report is the role of perspective systems theory that was developed in order to analyze such a detection and control problem. The robust control algorithms and the visually guided control algorithms are applied in the context of a PUMA 560 robot arm control where the goal is to visually locate a moving part on a mobile turntable. Such problems are of paramount importance in manufacturing with a certain lack of structure. Sensor guided control problems are extended to problems in robot navigation using a NOMADIC mobile platform with a ccd and a laser range finder as sensors. The localization and map building problems are studied with the objective of navigation in an unstructured terrain.

  20. Modern control techniques for accelerators

    International Nuclear Information System (INIS)

    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

  1. Intelligent control and automation technology for nuclear application

    International Nuclear Information System (INIS)

    Kim, Jae Hee; Eom, Heung Sub; Kim, Ko Ryu; Lee, Jae Cheol; Choi, You Rak; Lee, Soo Cheol

    1996-06-01

    Using recent technologies on a mobile robot and computer science, we developed an automatic inspection system for weld lines of the reactor pressure vessel. The ultrasonic inspection of the reactor pressure vessel is currently performed by commercialized robot manipulators. Since, however, the conventional fixed type robot manipulator is very huge, heavy and expensive, it needs long inspection time and is hard to handle and maintain. In order to resolve these problems, we developed a new inspection automation system using a small mobile robot crawling on the vertical wall. According to the conceptual design studied in the first year, we developed the inspection automation system including an underwater inspection robot, a laser position control subsystem and a main control subsystem. And we carried out underwater experiments on the reactor vessel mockup. After finishing this project successfully, we have a plan to commercialize our inspection system. Using this system, we can expect much reduction of the inspection time, performance enhancement, automatic management of inspection history, etc. In the economic point of view, we can also expect import substitution more than 5 million dollars. The established essential technologies for intelligent control and automation are expected to be synthetically applied to the automation of similar systems in nuclear power plants. 4 tabs., 37 figs., 6 refs. (Author)

  2. Intelligent automated control of robotic systems for environmental restoration

    International Nuclear Information System (INIS)

    Harrigan, R.W.

    1992-01-01

    Remote systems are needed to accomplish many tasks, such as the cleanup of waste sites in which the exposure of personnel to radiation, chemical, explosive, and other hazardous constituents is unacceptable. In addition, hazardous operations, which in the past have been completed by technicians, are under scrutiny because of the high costs and low productivity associated with providing protective clothing and environments. Traditional remote operations have, unfortunately, proven to also have very low productivity when compared with unencumbered human operators. However, recent advances in the integration of sensors and computing into the control of remotely operated equipment has shown great promise for reducing the cost of remote systems by providing faster and safer remote systems. The US Department of Energy's Office of Technology Development (OTD) has sponsored the development of the generic intelligent system controller (GISC) for application to remote system control. The GISC employs a highly modular architecture employing distributed real-time computing resources for speed and efficiency of computation. Currently, the graphics interface of GISC has been implemented on a Unix-based Silicon Graphics computer using commercial animation graphics software modified for real-time updating from sensory systems. A first implementation of GISC has been completed and is currently in use at Hanford, Washington, as part of the underground storage tank robotics technology development program

  3. An intelligent active force control algorithm to control an upper extremity exoskeleton for motor recovery

    Science.gov (United States)

    Hasbullah Mohd Isa, Wan; Taha, Zahari; Mohd Khairuddin, Ismail; Majeed, Anwar P. P. Abdul; Fikri Muhammad, Khairul; Abdo Hashem, Mohammed; Mahmud, Jamaluddin; Mohamed, Zulkifli

    2016-02-01

    This paper presents the modelling and control of a two degree of freedom upper extremity exoskeleton by means of an intelligent active force control (AFC) mechanism. The Newton-Euler formulation was used in deriving the dynamic modelling of both the anthropometry based human upper extremity as well as the exoskeleton that consists of the upper arm and the forearm. A proportional-derivative (PD) architecture is employed in this study to investigate its efficacy performing joint-space control objectives. An intelligent AFC algorithm is also incorporated into the PD to investigate the effectiveness of this hybrid system in compensating disturbances. The Mamdani Fuzzy based rule is employed to approximate the estimated inertial properties of the system to ensure the AFC loop responds efficiently. It is found that the IAFC-PD performed well against the disturbances introduced into the system as compared to the conventional PD control architecture in performing the desired trajectory tracking.

  4. Radiation curing of intelligent coating for controlled release and permeation

    International Nuclear Information System (INIS)

    Nakayama, Hiroshi; Kaetsu, Isao; Uchida, Kumao; Sakata, Shoei; Tougou, Kazuhide; Hara, Takamichi; Matsubara, Yoshio

    2002-01-01

    Intelligent membranes for pH and temperature-responsive drug releases were developed by coating and curing of polymer-drug composite film with electrolyte or N-isopropyl acrylamide curable mixture. It was proved that those intelligent membranes showed the stimule-sensitive and responsive release functions and could be produced efficiently by radiation curing processing with a conveyer system

  5. Intelligent viewing control for robotic and automation systems

    Science.gov (United States)

    Schenker, Paul S.; Peters, Stephen F.; Paljug, Eric D.; Kim, Won S.

    1994-10-01

    We present a new system for supervisory automated control of multiple remote cameras. Our primary purpose in developing this system has been to provide capability for knowledge- based, `hands-off' viewing during execution of teleoperation/telerobotic tasks. The reported technology has broader applicability to remote surveillance, telescience observation, automated manufacturing workcells, etc. We refer to this new capability as `Intelligent Viewing Control (IVC),' distinguishing it from a simple programmed camera motion control. In the IVC system, camera viewing assignment, sequencing, positioning, panning, and parameter adjustment (zoom, focus, aperture, etc.) are invoked and interactively executed by real-time by a knowledge-based controller, drawing on a priori known task models and constraints, including operator preferences. This multi-camera control is integrated with a real-time, high-fidelity 3D graphics simulation, which is correctly calibrated in perspective to the actual cameras and their platform kinematics (translation/pan-tilt). Such merged graphics- with-video design allows the system user to preview and modify the planned (`choreographed') viewing sequences. Further, during actual task execution, the system operator has available both the resulting optimized video sequence, as well as supplementary graphics views from arbitrary perspectives. IVC, including operator-interactive designation of robot task actions, is presented to the user as a well-integrated video-graphic single screen user interface allowing easy access to all relevant telerobot communication/command/control resources. We describe and show pictorial results of a preliminary IVC system implementation for telerobotic servicing of a satellite.

  6. Intelligent control a hybrid approach based on fuzzy logic, neural networks and genetic algorithms

    CERN Document Server

    Siddique, Nazmul

    2014-01-01

    Intelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller.  The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of t...

  7. REVIEW OF HEART DISEASE PREDICTION SYSTEM USING DATA MINING AND HYBRID INTELLIGENT TECHNIQUES

    Directory of Open Access Journals (Sweden)

    R. Chitra

    2013-07-01

    Full Text Available The Healthcare industry generally clinical diagnosis is done mostly by doctor’s expertise and experience. Computer Aided Decision Support System plays a major role in medical field. With the growing research on heart disease predicting system, it has become important to categories the research outcomes and provides readers with an overview of the existing heart disease prediction techniques in each category. Neural Networks are one of many data mining analytical tools that can be utilized to make predictions for medical data. From the study it is observed that Hybrid Intelligent Algorithm improves the accuracy of the heart disease prediction system. The commonly used techniques for Heart Disease Prediction and their complexities are summarized in this paper.

  8. Techniques of Ultrasound Cavitation Control

    Directory of Open Access Journals (Sweden)

    S. P. Skvortsov

    2015-01-01

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

  9. Software tool for resolution of inverse problems using artificial intelligence techniques: an application in neutron spectrometry

    International Nuclear Information System (INIS)

    Castaneda M, V. H.; Martinez B, M. R.; Solis S, L. O.; Castaneda M, R.; Leon P, A. A.; Hernandez P, C. F.; Espinoza G, J. G.; Ortiz R, J. M.; Vega C, H. R.; Mendez, R.; Gallego, E.; Sousa L, M. A.

    2016-10-01

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

  10. Development of An Intelligent Flight Propulsion Control System

    Science.gov (United States)

    Calise, A. J.; Rysdyk, R. T.; Leonhardt, B. K.

    1999-01-01

    The initial design and demonstration of an Intelligent Flight Propulsion and Control System (IFPCS) is documented. The design is based on the implementation of a nonlinear adaptive flight control architecture. This initial design of the IFPCS enhances flight safety by using propulsion sources to provide redundancy in flight control. The IFPCS enhances the conventional gain scheduled approach in significant ways: (1) The IFPCS provides a back up flight control system that results in consistent responses over a wide range of unanticipated failures. (2) The IFPCS is applicable to a variety of aircraft models without redesign and,(3) significantly reduces the laborious research and design necessary in a gain scheduled approach. The control augmentation is detailed within an approximate Input-Output Linearization setting. The availability of propulsion only provides two control inputs, symmetric and differential thrust. Earlier Propulsion Control Augmentation (PCA) work performed by NASA provided for a trajectory controller with pilot command input of glidepath and heading. This work is aimed at demonstrating the flexibility of the IFPCS in providing consistency in flying qualities under a variety of failure scenarios. This report documents the initial design phase where propulsion only is used. Results confirm that the engine dynamics and associated hard nonlineaaities result in poor handling qualities at best. However, as demonstrated in simulation, the IFPCS is capable of results similar to the gain scheduled designs of the NASA PCA work. The IFPCS design uses crude estimates of aircraft behaviour. The adaptive control architecture demonstrates robust stability and provides robust performance. In this work, robust stability means that all states, errors, and adaptive parameters remain bounded under a wide class of uncertainties and input and output disturbances. Robust performance is measured in the quality of the tracking. The results demonstrate the flexibility of

  11. Interated Intelligent Industrial Process Sensing and Control: Applied to and Demonstrated on Cupola Furnaces

    Energy Technology Data Exchange (ETDEWEB)

    Mohamed Abdelrahman; roger Haggard; Wagdy Mahmoud; Kevin Moore; Denis Clark; Eric Larsen; Paul King

    2003-02-12

    The final goal of this project was the development of a system that is capable of controlling an industrial process effectively through the integration of information obtained through intelligent sensor fusion and intelligent control technologies. The industry of interest in this project was the metal casting industry as represented by cupola iron-melting furnaces. However, the developed technology is of generic type and hence applicable to several other industries. The system was divided into the following four major interacting components: 1. An object oriented generic architecture to integrate the developed software and hardware components @. Generic algorithms for intelligent signal analysis and sensor and model fusion 3. Development of supervisory structure for integration of intelligent sensor fusion data into the controller 4. Hardware implementation of intelligent signal analysis and fusion algorithms

  12. Attention and impulse control in children with borderline intelligence with or without conduct disorder.

    NARCIS (Netherlands)

    van der Meere, Jaap; van der Meer, Dirk-Jan; Borger, Norbert; Pirila, Silja

    2008-01-01

    This study was designed to investigate attention and impulse control in 21 boys with dual diagnoses of conduct disorder and borderline intelligence and in 19 boys with borderline intelligence only. Using the Continuous Performance Test A-not-X, it appeared that children with the dual diagnosis made

  13. Fire Play: ICCARUS--Intelligent Command and Control, Acquisition and Review Using Simulation

    Science.gov (United States)

    Powell, James; Wright, Theo; Newland, Paul; Creed, Chris; Logan, Brian

    2008-01-01

    Is it possible to educate a fire officer to deal intelligently with the command and control of a major fire event he will never have experienced? The authors of this paper believe there is, and present here just one solution to this training challenge. It involves the development of an intelligent simulation based upon computer managed interactive…

  14. Comparison of Intelligibility Measures for Adults with Parkinson's Disease, Adults with Multiple Sclerosis, and Healthy Controls

    Science.gov (United States)

    Stipancic, Kaila L.; Tjaden, Kris; Wilding, Gregory

    2016-01-01

    Purpose: This study obtained judgments of sentence intelligibility using orthographic transcription for comparison with previously reported intelligibility judgments obtained using a visual analog scale (VAS) for individuals with Parkinson's disease and multiple sclerosis and healthy controls (K. Tjaden, J. E. Sussman, & G. E. Wilding, 2014).…

  15. Laser rangefinders for autonomous intelligent cruise control systems

    Science.gov (United States)

    Journet, Bernard A.; Bazin, Gaelle

    1998-01-01

    THe purpose of this paper is to show to what kind of application laser range-finders can be used inside Autonomous Intelligent Cruise Control systems. Even if laser systems present good performances the safety and technical considerations are very restrictive. As the system is used in the outside, the emitted average output power must respect the rather low level of 1A class. Obstacle detection or collision avoidance require a 200 meters range. Moreover bad weather conditions, like rain or fog, ar disastrous. We have conducted measurements on laser rangefinder using different targets and at different distances. We can infer that except for cooperative targets low power laser rangefinder are not powerful enough for long distance measurement. Radars, like 77 GHz systems, are better adapted to such cases. But in case of short distances measurement, range around 10 meters, with a minimum distance around twenty centimeters, laser rangefinders are really useful with good resolution and rather low cost. Applications can have the following of white lines on the road, the target being easily cooperative, detection of vehicles in the vicinity, that means car convoy traffic control or parking assistance, the target surface being indifferent at short distances.

  16. An intelligent control scheme for precise tip-motion control in atomic force microscopy.

    Science.gov (United States)

    Wang, Yanyan; Hu, Xiaodong; Xu, Linyan

    2016-01-01

    The paper proposes a new intelligent control method to precisely control the tip motion of the atomic force microscopy (AFM). The tip moves up and down at a high rate along the z direction during scanning, requiring the utilization of a rapid feedback controller. The standard proportional-integral (PI) feedback controller is commonly used in commercial AFMs to enable topography measurements. The controller's response performance is determined by the set of the proportional (P) parameter and the integral (I) parameter. However, the two parameters cannot be automatically altered simultaneously according to the scanning speed and the surface topography during continuors scanning, leading to an inaccurate measurement. Thus a new intelligent controller combining the fuzzy controller and the PI controller is put forward in the paper. The new controller automatically selects the most appropriate PI parameters to achieve a fast response rate on basis of the tracking errors. In the experimental setup, the new controller is realized with a digital signal process (DSP) system, implemented in a conventional AFM system. Experiments are carried out by comparing the new method with the standard PI controller. The results demonstrate that the new method is more robust and effective for the precise tip motion control, corresponding to the achievement of a highly qualified image by shortening the response time of the controller. © Wiley Periodicals, Inc.

  17. Robust control technique for nuclear power plants

    International Nuclear Information System (INIS)

    Murphy, G.V.; Bailey, J.M.

    1989-03-01

    This report summarizes the linear quadratic Guassian (LQG) design technique with loop transfer recovery (LQG/LTR) for design of control systems. The concepts of return ratio, return difference, inverse return difference, and singular values are summarized. The LQG/LTR design technique allows the synthesis of a robust control system. To illustrate the LQG/LTR technique, a linearized model of a simple process has been chosen. The process has three state variables, one input, and one output. Three control system design methods are compared: LQG, LQG/LTR, and a proportional plus integral controller (PI). 7 refs., 20 figs., 6 tabs

  18. Theoretical analysis and real time implementation of a classical controller with intelligent properties

    Directory of Open Access Journals (Sweden)

    Essam Hendawi

    2018-05-01

    Full Text Available This paper presents theoretical analysis and experimental implementation of a classical controller with intelligent properties. The controller has constant parameters, but it performs as an intelligent controller. The controller design mimics the fuzzy logic controller in a classical form and combines the advantages of classical controllers and properties of intelligent controllers. The designed controller parameters force the controlled variable to behave such as a first order system with a desired time constant. DC motor practical system is used to demonstrate the effectiveness of the presented controller. Root locus and frequency response using Bode diagram are used to help the design of the controller parameters. Simulation and experimental results verify the high performance of the presented controller. Keywords: Classical controller, DC motor, Root locus, Frequency response, Arduino microcontroller

  19. 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.

  20. Results from an in-plant demonstration of intelligent control

    International Nuclear Information System (INIS)

    Edwards, R.M.; Garcia, H.E.; Messick, N.

    1993-01-01

    A learning systems-based reconfigurable controller was demonstrated on the deaerating feedwater heater at the Experimental Breeder Reactor II (EBR-II) on April 1, 1993. Failures of the normal pressure regulating process were introduced by reducing the steam flow to the heater by as much as 10%. The controller maintained pressure in the heater at acceptable levels for several minutes, whereas operator intervention would have otherwise been required within a few seconds. This experiment demonstrates the potential of advanced control techniques for improving safety, reliability, and performance of power plant operations as well as the utility of EBR-II as an experimental power plant controls facility

  1. A Wavelet Neural Network Optimal Control Model for Traffic-Flow Prediction in Intelligent Transport Systems

    Science.gov (United States)

    Huang, Darong; Bai, Xing-Rong

    Based on wavelet transform and neural network theory, a traffic-flow prediction model, which was used in optimal control of Intelligent Traffic system, is constructed. First of all, we have extracted the scale coefficient and wavelet coefficient from the online measured raw data of traffic flow via wavelet transform; Secondly, an Artificial Neural Network model of Traffic-flow Prediction was constructed and trained using the coefficient sequences as inputs and raw data as outputs; Simultaneous, we have designed the running principium of the optimal control system of traffic-flow Forecasting model, the network topological structure and the data transmitted model; Finally, a simulated example has shown that the technique is effectively and exactly. The theoretical results indicated that the wavelet neural network prediction model and algorithms have a broad prospect for practical application.

  2. Charting a Path to Location Intelligence for STD Control

    OpenAIRE

    Gerber, Todd M.; Du, Ping; Armstrong-Brown, Janelle; McNutt, Louise-Anne; Coles, F. Bruce

    2009-01-01

    This article describes the New York State Department of Health's GeoDatabase project, which developed new methods and techniques for designing and building a geocoding and mapping data repository for sexually transmitted disease (STD) control. The GeoDatabase development was supported through the Centers for Disease Control and Prevention's Outcome Assessment through Systems of Integrated Surveillance workgroup. The design and operation of the GeoDatabase relied upon commercial-off-the-shelf ...

  3. Composite Intelligent Learning Control of Strict-Feedback Systems With Disturbance.

    Science.gov (United States)

    Xu, Bin; Sun, Fuchun

    2018-02-01

    This paper addresses the dynamic surface control of uncertain nonlinear systems on the basis of composite intelligent learning and disturbance observer in presence of unknown system nonlinearity and time-varying disturbance. The serial-parallel estimation model with intelligent approximation and disturbance estimation is built to obtain the prediction error and in this way the composite law for weights updating is constructed. The nonlinear disturbance observer is developed using intelligent approximation information while the disturbance estimation is guaranteed to converge to a bounded compact set. The highlight is that different from previous work directly toward asymptotic stability, the transparency of the intelligent approximation and disturbance estimation is included in the control scheme. The uniformly ultimate boundedness stability is analyzed via Lyapunov method. Through simulation verification, the composite intelligent learning with disturbance observer can efficiently estimate the effect caused by system nonlinearity and disturbance while the proposed approach obtains better performance with higher accuracy.

  4. Fatigue distribution optimization for offshore wind farms using intelligent agent control

    DEFF Research Database (Denmark)

    Zhao, Rongyong; Shen, Wen Zhong; Knudsen, Torben

    2012-01-01

    with its neighbouring downwind turbines and organizes them adaptively into a wind delivery group along the wind direction. The agent attributes and the event structure are designed on the basis of the intelligent agent theory by using the unified modelling language. The control strategy of the intelligent......A novel control approach is proposed to optimize the fatigue distribution of wind turbines in a large‐scale offshore wind farm on the basis of an intelligent agent theory. In this approach, each wind turbine is considered to be an intelligent agent. The turbine at the farm boundary communicates...... coefficient for every wind turbine. The optimization is constrained such that the average fatigue for every turbine is smaller than what would be achieved by conventional dispatch and such that the total power loss of the wind farm is restricted to a few percent of the total power. This intelligent agent...

  5. Fuzzy gain scheduling of velocity PI controller with intelligent learning algorithm for reactor control

    International Nuclear Information System (INIS)

    Kim, Dong Yun

    1997-02-01

    In this research, we propose a fuzzy gain scheduler (FGS) with an intelligent learning algorithm for a reactor control. In the proposed algorithm, the gradient descent method is used in order to generate the rule bases of a fuzzy algorithm by learning. These rule bases are obtained by minimizing an objective function, which is called a performance cost function. The objective of the FGS with an intelligent learning algorithm is to generate adequate gains, which minimize the error of system. The proposed algorithm can reduce the time and efforts required for obtaining the fuzzy rules through the intelligent learning function. The evolutionary programming algorithm is modified and adopted as the method in order to find the optimal gains which are used as the initial gains of FGS with learning function. It is applied to reactor control of nuclear power plant (NPP), and the results are compared with those of a conventional PI controller with fixed gains. As a result, it is shown that the proposed algorithm is superior to the conventional PI controller

  6. Early detection and identification of anomalies in chemical regime based on computational intelligence techniques

    International Nuclear Information System (INIS)

    Figedy, Stefan; Smiesko, Ivan

    2012-01-01

    This article provides brief information about the fundamental features of a newly-developed diagnostic system for early detection and identification of anomalies being generated in water chemistry regime of the primary and secondary circuit of the VVER-440 reactor. This system, which is called SACHER (System of Analysis of CHEmical Regime), was installed within the major modernization project at the NPP-V2 Bohunice in the Slovak Republic. The SACHER system has been fully developed on MATLAB environment. It is based on computational intelligence techniques and inserts various elements of intelligent data processing modules for clustering, diagnosing, future prediction, signal validation, etc, into the overall chemical information system. The application of SACHER would essentially assist chemists to identify the current situation regarding anomalies being generated in the primary and secondary circuit water chemistry. This system is to be used for diagnostics and data handling, however it is not intended to fully replace the presence of experienced chemists to decide upon corrective actions. (author)

  7. Emotional intelligence in patients with posttraumatic stress disorder, borderline personality disorder and healthy controls.

    Science.gov (United States)

    Janke, Katrin; Driessen, Martin; Behnia, Behnoush; Wingenfeld, Katja; Roepke, Stefan

    2018-06-01

    Emotional intelligence as a part of social cognition has, to our knowledge, never been investigated in patients with Posttraumatic Stress Disorder (PTSD), though the disorder is characterized by aspects of emotional dysfunctioning. PTSD often occurs with Borderline Personality Disorder (BPD) as a common comorbidity. Studies about social cognition and emotional intelligence in patients with BPD propose aberrant social cognition, but produced inconsistent results regarding emotional intelligence. The present study aims to assess emotional intelligence in patients with PTSD without comorbid BPD, PTSD with comorbid BPD, and BPD patients without comorbid PTSD, as well as in healthy controls. 71 patients with PTSD (41 patients with PTSD without comorbid BPD, 30 patients with PTSD with comorbid BPD), 56 patients with BPD without PTSD, and 63 healthy controls filled in the Test of Emotional Intelligence (TEMINT). Patients with PTSD without comorbid BPD showed impairments in emotional intelligence compared to patients with BPD without PTSD, and compared to healthy controls. These impairments were not restricted to specific emotions. Patients with BPD did not differ significantly from healthy controls. This study provides evidence for an impaired emotional intelligence in PTSD without comorbid BPD compared to BPD and healthy controls, affecting a wide range of emotions. Copyright © 2018 Elsevier B.V. All rights reserved.

  8. New development thoughts on the bio-inspired intelligence based control for unmanned combat aerial vehicle

    Institute of Scientific and Technical Information of China (English)

    2010-01-01

    Bio-inspired intelligence is in the spotlight in the field of international artificial intelligence,and unmanned combat aerial vehicle(UCAV),owing to its potential to perform dangerous,repetitive tasks in remote and hazardous,is very promising for the technological leadership of the nation and essential for improving the security of society.On the basis of introduction of bioinspired intelligence and UCAV,a series of new development thoughts on UCAV control are proposed,including artificial brain based high-level autonomous control for UCAV,swarm intelligence based cooperative control for multiple UCAVs,hy-brid swarm intelligence and Bayesian network based situation assessment under complicated combating environments, bio-inspired hardware based high-level autonomous control for UCAV,and meta-heuristic intelligence based heterogeneous cooperative control for multiple UCAVs and unmanned combat ground vehicles(UCGVs).The exact realization of the proposed new development thoughts can enhance the effectiveness of combat,while provide a series of novel breakthroughs for the intelligence,integration and advancement of future UCAV systems.

  9. Intelligent Technique for Signal Processing to Identify the Brain Disorder for Epilepsy Captures Using Fuzzy Systems

    Directory of Open Access Journals (Sweden)

    Gurumurthy Sasikumar

    2016-01-01

    Full Text Available The new direction of understand the signal that is created from the brain organization is one of the main chores in the brain signal processing. Amid all the neurological disorders the human brain epilepsy is measured as one of the extreme prevalent and then programmed artificial intelligence detection technique is an essential due to the crooked and unpredictable nature of happening of epileptic seizures. We proposed an Improved Fuzzy firefly algorithm, which would enhance the classification of the brain signal efficiently with minimum iteration. An important bunching technique created on fuzzy logic is the Fuzzy C means. Together in the feature domain with the spatial domain the features gained after multichannel EEG signals remained combined by means of fuzzy algorithms. And for better precision segmentation process the firefly algorithm is applied to optimize the Fuzzy C-means membership function. Simultaneously for the efficient clustering method the convergence criteria are set. On the whole the proposed technique yields more accurate results and that gives an edge over other techniques. This proposed algorithm result compared with other algorithms like fuzzy c means algorithm and PSO algorithm.

  10. Experimental Study on Intelligent Control Scheme for Fan Coil Air-Conditioning System

    Directory of Open Access Journals (Sweden)

    Yanfeng Li

    2013-01-01

    Full Text Available An intelligent control scheme for fan coil air-conditioning systems has been put forward in order to overcome the shortcomings of the traditional proportion-integral-derivative (PID control scheme. These shortcomings include the inability of anti-interference and large inertia. An intelligent control test rig of fan coil air-conditioning system has been built, and MATLAB/Simulink dynamics simulation software has been adopted to implement the intelligent control scheme. A software for data exchange has been developed to combine the intelligence control system and the building automation (BA system. Experimental tests have been conducted to investigate the effectiveness of different control schemes including the traditional PID control, fuzzy control, and fuzzy-PID control for fan coil air-conditioning system. The effects of control schemes have been compared and analyzed in robustness, static and dynamic character, and economy. The results have shown that the developed data exchange interface software can induce the intelligent control scheme of the BA system more effectively. Among the proposed control strategies, fuzzy-PID control scheme which has the advantages of both traditional PID and fuzzy schemes is the optimal control scheme for the fan coil air-conditioning system.

  11. Distributed sensor architecture for intelligent control that supports quality of control and quality of service.

    Science.gov (United States)

    Poza-Lujan, Jose-Luis; Posadas-Yagüe, Juan-Luis; Simó-Ten, José-Enrique; Simarro, Raúl; Benet, Ginés

    2015-02-25

    This paper is part of a study of intelligent architectures for distributed control and communications systems. The study focuses on optimizing control systems by evaluating the performance of middleware through quality of service (QoS) parameters and the optimization of control using Quality of Control (QoC) parameters. The main aim of this work is to study, design, develop, and evaluate a distributed control architecture based on the Data-Distribution Service for Real-Time Systems (DDS) communication standard as proposed by the Object Management Group (OMG). As a result of the study, an architecture called Frame-Sensor-Adapter to Control (FSACtrl) has been developed. FSACtrl provides a model to implement an intelligent distributed Event-Based Control (EBC) system with support to measure QoS and QoC parameters. The novelty consists of using, simultaneously, the measured QoS and QoC parameters to make decisions about the control action with a new method called Event Based Quality Integral Cycle. To validate the architecture, the first five Braitenberg vehicles have been implemented using the FSACtrl architecture. The experimental outcomes, demonstrate the convenience of using jointly QoS and QoC parameters in distributed control systems.

  12. Distributed Sensor Architecture for Intelligent Control that Supports Quality of Control and Quality of Service

    Directory of Open Access Journals (Sweden)

    Jose-Luis Poza-Lujan

    2015-02-01

    Full Text Available This paper is part of a study of intelligent architectures for distributed control and communications systems. The study focuses on optimizing control systems by evaluating the performance of middleware through quality of service (QoS parameters and the optimization of control using Quality of Control (QoC parameters. The main aim of this work is to study, design, develop, and evaluate a distributed control architecture based on the Data-Distribution Service for Real-Time Systems (DDS communication standard as proposed by the Object Management Group (OMG. As a result of the study, an architecture called Frame-Sensor-Adapter to Control (FSACtrl has been developed. FSACtrl provides a model to implement an intelligent distributed Event-Based Control (EBC system with support to measure QoS and QoC parameters. The novelty consists of using, simultaneously, the measured QoS and QoC parameters to make decisions about the control action with a new method called Event Based Quality Integral Cycle. To validate the architecture, the first five Braitenberg vehicles have been implemented using the FSACtrl architecture. The experimental outcomes, demonstrate the convenience of using jointly QoS and QoC parameters in distributed control systems.

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

    International Nuclear Information System (INIS)

    Azmy, Y.Y.

    1988-01-01

    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

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

    International Nuclear Information System (INIS)

    Azmy, Y.Y.

    1988-01-01

    Most optimization studies of cold neutron sources have concentrated on the numerical prediction or experimental measurement of the cold moderator optimum thickness that produces the largest cold neutron leakage for a given thermal neutron source. Optimizing the geometric 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. An analogy is drawn between this problem and a state space search, then a simple artificial intelligence (AI) search technique is used to determine the optimum cold source shape based on a two-group, r-z diffusion model. This AI design concept was implemented 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

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

    International Nuclear Information System (INIS)

    Tong, S.S.; Powell, D.; Goel, S.

    1992-02-01

    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

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

    International Nuclear Information System (INIS)

    Pallas, Christophe

    1987-01-01

    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) [fr

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

    International Nuclear Information System (INIS)

    Yoshikawa, S.; Saiki, A.; Ugolini, D.; Ozawa, K.

    1996-01-01

    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 (NN ds ) 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)

  18. Competitive Intelligence.

    Science.gov (United States)

    Bergeron, Pierrette; Hiller, Christine A.

    2002-01-01

    Reviews the evolution of competitive intelligence since 1994, including terminology and definitions and analytical techniques. Addresses the issue of ethics; explores how information technology supports the competitive intelligence process; and discusses education and training opportunities for competitive intelligence, including core competencies…

  19. Intelligent control system for nuclear power plant mobile robot

    International Nuclear Information System (INIS)

    Koenig, A.; Lecoeur-Taibi, I.; Crochon, E.; Vacherand, F.

    1991-01-01

    In order to fully optimize the efficiency of the perception and navigation components available on a mobile robot, the upper level of a mobile robot control requires intelligence support to unload the work of the teleoperator. This knowledge-based system has to manage a priori data such as the map of the workspace, the mission, the characteristics of sensors and robot, but also, the current environment state and the running mission. It has to issue a plan to drive the sensors to focus on relevant objects or to scan the environment and to select the best algorithms depending on the current situation. The environment workspace is a nuclear power plant building. The teleoperated robot is a mobile wheeled or legged vehicle that moves inside the different floors of the building. There are three types of mission: radio-activity survey, inspection and intervention. To perform these goals the robot must avoid obstacles, pass through doors, possibly climb stairs and recognize valves and pipes. The perception control system has to provide the operator with a synthetic view of the surroundings. It manages background tasks such as obstacle detection and free space map building, and specific tasks such as beacon recognition for odometry relocalization and valve detection for maintenance. To do this, the system solves perception resources conflicts, taking into account the current states of the sensors and the current conditions such as lightness or darkness, cluttered scenes, sensor failure. A perception plan is issued from the mission goals, planned path, relocalization requirements and available perception resources. Basically, the knowledge-based system is implemented on a blackboard architecture which includes two parts: a top-down planning part and a bottom-up perception part. The results of the perception are continuously sent to the operator who can trigger new perception actions. (author)

  20. A comparative analysis among computational intelligence techniques for dissolved oxygen prediction in Delaware River

    Directory of Open Access Journals (Sweden)

    Ehsan Olyaie

    2017-05-01

    Full Text Available Most of the water quality models previously developed and used in dissolved oxygen (DO prediction are complex. Moreover, reliable data available to develop/calibrate new DO models is scarce. Therefore, there is a need to study and develop models that can handle easily measurable parameters of a particular site, even with short length. In recent decades, computational intelligence techniques, as effective approaches for predicting complicated and significant indicator of the state of aquatic ecosystems such as DO, have created a great change in predictions. In this study, three different AI methods comprising: (1 two types of artificial neural networks (ANN namely multi linear perceptron (MLP and radial based function (RBF; (2 an advancement of genetic programming namely linear genetic programming (LGP; and (3 a support vector machine (SVM technique were used for DO prediction in Delaware River located at Trenton, USA. For evaluating the performance of the proposed models, root mean square error (RMSE, Nash–Sutcliffe efficiency coefficient (NS, mean absolute relative error (MARE and, correlation coefficient statistics (R were used to choose the best predictive model. The comparison of estimation accuracies of various intelligence models illustrated that the SVM was able to develop the most accurate model in DO estimation in comparison to other models. Also, it was found that the LGP model performs better than the both ANNs models. For example, the determination coefficient was 0.99 for the best SVM model, while it was 0.96, 0.91 and 0.81 for the best LGP, MLP and RBF models, respectively. In general, the results indicated that an SVM model could be employed satisfactorily in DO estimation.

  1. Intelligent plasma operation and control system for HL-2M

    International Nuclear Information System (INIS)

    Xia, F.; Chen, L.Y.; Wang, C.; Zhang, G.; Song, X.M.; Song, X.; Pan, L.; Zhao, L.; Pan, W.; Lan, J.T.

    2015-01-01

    Full text of publication follows. The Intelligent Plasma Operation and Control System (IPOCS) for HL-2M is under construction based on the current actual situation of HL-2A control system in SWIP. The purpose of IPOCS is to replace the routine processes before, during and post discharge with the automatic process algorithms and give various information, for example, status, warning, reason, instruction, suggestion, physics phenomenon etc. to staff who can access the intranet. In this case, the core research objectives can be focused on and the related operations can be carried out referring to the information. The ultimate goal of IPOCS is to improve the efficiency of plant operation and control and physics research for HL-2M and for the fusion reactor in the future. There are three layers in IPOCS, which are named the information collection layer, the data processing layer and the presentation layer respectively. Information collection layer consists of data acquisition system, EPICS system, Audio and Video system, discharge scheduling system, data storage system etc. All raw data are collected and stored in this layer. The data processing layer is the core of IPOCS. Most algorithms are executed here. The basic computation platform is based on cluster (56 cores at present) and Parallel Computing Toolbox provided by Matlab. The physics database for SWIP based on HDF5 and offline EFIT also locate at this layer. All the operations can be finished during the time interval between two shots. The last layer is to present the information from the former two layers. The typical hardware including the large display screen system in the control room, the voice broadcasting system, personal monitors and smart phones, etc.. Several applications has being developed such as Control System Studio (CSS) in SWIP version, WebOPI, Automatic Alarm Display system and so on. IPOCS for HL-2M is at the very beginning phase at present. With more and more systems and algorithms got

  2. Intelligent, Semi-Automated Procedure Aid (ISAPA) for ISS Flight Control, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to develop the Intelligent, Semi-Automated Procedure Aid (ISAPA) intended for use by International Space Station (ISS) ground controllers to increase the...

  3. A Framework for a General Purpose Intelligent Control System for Particle Accelerators. Phase II Final Report

    International Nuclear Information System (INIS)

    Westervelt, Robert; Klein, William; Kroupa, Michael; Olsson, Eric; Rothrock, Rick

    1999-01-01

    Vista Control Systems, Inc. has developed a portable system for intelligent accelerator control. The design is general in scope and is thus configurable to a wide range of accelerator facilities and control problems. The control system employs a multi-layer organization in which knowledge-based decision making is used to dynamically configure lower level optimization and control algorithms

  4. An intelligent signal processing and pattern recognition technique for defect identification using an active sensor network

    Science.gov (United States)

    Su, Zhongqing; Ye, Lin

    2004-08-01

    The practical utilization of elastic waves, e.g. Rayleigh-Lamb waves, in high-performance structural health monitoring techniques is somewhat impeded due to the complicated wave dispersion phenomena, the existence of multiple wave modes, the high susceptibility to diverse interferences, the bulky sampled data and the difficulty in signal interpretation. An intelligent signal processing and pattern recognition (ISPPR) approach using the wavelet transform and artificial neural network algorithms was developed; this was actualized in a signal processing package (SPP). The ISPPR technique comprehensively functions as signal filtration, data compression, characteristic extraction, information mapping and pattern recognition, capable of extracting essential yet concise features from acquired raw wave signals and further assisting in structural health evaluation. For validation, the SPP was applied to the prediction of crack growth in an alloy structural beam and construction of a damage parameter database for defect identification in CF/EP composite structures. It was clearly apparent that the elastic wave propagation-based damage assessment could be dramatically streamlined by introduction of the ISPPR technique.

  5. 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.

  6. Intelligent Mechatronics Systems for Transport Climate Parameters Optimization Using Fuzzy Logic Control

    OpenAIRE

    Beinarts, I; Ļevčenkovs, A; Kuņicina, N

    2007-01-01

    In article interest is concentrated on the climate parameters optimization in passengers’ salon of public electric transportation vehicles. The article presents mathematical problem for using intelligent agents in mechatronics problems for climate parameters optimal control. Idea is to use fuzzy logic and intelligent algorithms to create coordination mechanism for climate parameters control to save electrical energy, and it increases the level of comfort for passengers. A special interest for...

  7. Design of intelligent comfort control system with human learning and minimum power control strategies

    International Nuclear Information System (INIS)

    Liang, J.; Du, R.

    2008-01-01

    This paper presents the design of an intelligent comfort control system by combining the human learning and minimum power control strategies for the heating, ventilating and air conditioning (HVAC) system. In the system, the predicted mean vote (PMV) is adopted as the control objective to improve indoor comfort level by considering six comfort related variables, whilst a direct neural network controller is designed to overcome the nonlinear feature of the PMV calculation for better performance. To achieve the highest comfort level for the specific user, a human learning strategy is designed to tune the user's comfort zone, and then, a VAV and minimum power control strategy is proposed to minimize the energy consumption further. In order to validate the system design, a series of computer simulations are performed based on a derived HVAC and thermal space model. The simulation results confirm the design of the intelligent comfort control system. In comparison to the conventional temperature controller, this system can provide a higher comfort level and better system performance, so it has great potential for HVAC applications in the future

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

    International Nuclear Information System (INIS)

    Gaafar, M.S.; Abdeen, Mostafa A.M.; Marzouk, S.Y.

    2011-01-01

    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 Nb 5+ 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 xNb 2 O 5 -(1 - x)TeO 2 , 0.1PbO-xNb 2 O 5 -(0.9 - x)TeO 2 , 0.2PbO-xNb 2 O 5 -(0.8 - x)TeO 2 and 0.05Bi 2 O 3 -xNb 2 O 5 -(0.95 - x)TeO 2 were prepared using melt quenching technique. The results of ultrasonic velocities and elastic moduli showed that the addition of Nb 2 O 5 as a network modifier provides oxygen ions to change [TeO 4 ] tbps into [TeO 3 ] tps.

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

    Energy Technology Data Exchange (ETDEWEB)

    Gaafar, M.S., E-mail: mohamed_s_gaafar@hotmail.com [Ultrasonic Department, National Institute for Standards, Giza (Egypt); Physics Department, Faculty of Science, Majmaah University, Zulfi (Saudi Arabia); Abdeen, Mostafa A.M., E-mail: mostafa_a_m_abdeen@hotmail.com [Dept. of Eng. Math. and Physics, Faculty of Eng., Cairo University, Giza (Egypt); Marzouk, S.Y., E-mail: samir_marzouk2001@yahoo.com [Arab Academy of Science and Technology, Al-Horria, Heliopolis, Cairo (Egypt)

    2011-02-24

    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 Nb{sup 5+} 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 xNb{sub 2}O{sub 5}-(1 - x)TeO{sub 2}, 0.1PbO-xNb{sub 2}O{sub 5}-(0.9 - x)TeO{sub 2}, 0.2PbO-xNb{sub 2}O{sub 5}-(0.8 - x)TeO{sub 2} and 0.05Bi{sub 2}O{sub 3}-xNb{sub 2}O{sub 5}-(0.95 - x)TeO{sub 2} were prepared using melt quenching technique. The results of ultrasonic velocities and elastic moduli showed that the addition of Nb{sub 2}O{sub 5} as a network modifier provides oxygen ions to change [TeO{sub 4}] tbps into [TeO{sub 3}] tps.

  10. Charting a Path to Location Intelligence for STD Control.

    Science.gov (United States)

    Gerber, Todd M; Du, Ping; Armstrong-Brown, Janelle; McNutt, Louise-Anne; Coles, F Bruce

    2009-01-01

    This article describes the New York State Department of Health's GeoDatabase project, which developed new methods and techniques for designing and building a geocoding and mapping data repository for sexually transmitted disease (STD) control. The GeoDatabase development was supported through the Centers for Disease Control and Prevention's Outcome Assessment through Systems of Integrated Surveillance workgroup. The design and operation of the GeoDatabase relied upon commercial-off-the-shelf tools that other public health programs may also use for disease-control systems. This article provides a blueprint of the structure and software used to build the GeoDatabase and integrate location data from multiple data sources into the everyday activities of STD control programs.

  11. Intelligent monitoring, control, and security of critical infrastructure systems

    CERN Document Server

    Polycarpou, Marios

    2015-01-01

    This book describes the challenges that critical infrastructure systems face, and presents state of the art solutions to address them. How can we design intelligent systems or intelligent agents that can make appropriate real-time decisions in the management of such large-scale, complex systems? What are the primary challenges for critical infrastructure systems? The book also provides readers with the relevant information to recognize how important infrastructures are, and their role in connection with a society’s economy, security and prosperity. It goes on to describe state-of-the-art solutions to address these points, including new methodologies and instrumentation tools (e.g. embedded software and intelligent algorithms) for transforming and optimizing target infrastructures. The book is the most comprehensive resource to date for professionals in both the private and public sectors, while also offering an essential guide for students and researchers in the areas of modeling and analysis of critical in...

  12. Tuberculosis control, and the where and why of artificial intelligence

    Directory of Open Access Journals (Sweden)

    Riddhi Doshi

    2017-06-01

    Full Text Available Countries aiming to reduce their tuberculosis (TB burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB.

  13. Tuberculosis control, and the where and why of artificial intelligence.

    Science.gov (United States)

    Doshi, Riddhi; Falzon, Dennis; Thomas, Bruce V; Temesgen, Zelalem; Sadasivan, Lal; Migliori, Giovanni Battista; Raviglione, Mario

    2017-04-01

    Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB.

  14. Tuberculosis control, and the where and why of artificial intelligence

    Science.gov (United States)

    Falzon, Dennis; Thomas, Bruce V.; Temesgen, Zelalem; Sadasivan, Lal; Raviglione, Mario

    2017-01-01

    Countries aiming to reduce their tuberculosis (TB) burden by 2035 to the levels envisaged by the World Health Organization End TB Strategy need to innovate, with approaches such as digital health (electronic and mobile health) in support of patient care, surveillance, programme management, training and communication. Alongside the large-scale roll-out required for such interventions to make a significant impact, products must stay abreast of advancing technology over time. The integration of artificial intelligence into new software promises to make processes more effective and efficient, endowing them with a potential hitherto unimaginable. Users can benefit from artificial intelligence-enabled pattern recognition software for tasks ranging from reading radiographs to adverse event monitoring, sifting through vast datasets to personalise a patient's care plan or to customise training materials. Many experts forecast the imminent transformation of the delivery of healthcare services. We discuss how artificial intelligence and machine learning could revolutionise the management of TB. PMID:28656130

  15. Economic Impact of Intelligent Dynamic Control in Urban Outdoor Lighting

    Directory of Open Access Journals (Sweden)

    Igor Wojnicki

    2016-04-01

    Full Text Available This paper presents and compares the possible energy savings in various approaches to outdoor lighting modernization. Several solutions implementable using currently-available systems are presented and discussed. An innovative approach using real-time sensor data is also presented in detail, along with its formal background, based on Artificial Intelligence methods (rule-based systems and graph transformations. The efficiency of all approaches has been estimated and compared using real-life data recorded at an urban setting. The article also presents other aspects which influence the efficiency and feasibility of intelligent lighting projects, including design quality, design workload and conformance to standards.

  16. Intelligent control of an IPMC actuated manipulator using emotional learning-based controller

    Science.gov (United States)

    Shariati, Azadeh; Meghdari, Ali; Shariati, Parham

    2008-08-01

    In this research an intelligent emotional learning controller, Takagi- Sugeno- Kang (TSK) is applied to govern the dynamics of a novel Ionic-Polymer Metal Composite (IPMC) actuated manipulator. Ionic-Polymer Metal Composites are active actuators that show very large deformation in existence of low applied voltage. In this research, a new IPMC actuator is considered and applied to a 2-dof miniature manipulator. This manipulator is designed for miniature tasks. The control system consists of a set of neurofuzzy controller whose parameters are adapted according to the emotional learning rules, and a critic with task to assess the present situation resulted from the applied control action in terms of satisfactory achievement of the control goals and provides the emotional signal (the stress). The controller modifies its characteristics so that the critic's stress decreased.

  17. A Smart Sensor Data Transmission Technique for Logistics and Intelligent Transportation Systems

    Directory of Open Access Journals (Sweden)

    Kyunghee Sun

    2018-03-01

    Full Text Available When it comes to Internet of Things systems that include both a logistics system and an intelligent transportation system, a smart sensor is one of the key elements to collect useful information whenever and wherever necessary. This study proposes the Smart Sensor Node Group Management Medium Access Control Scheme designed to group smart sensor devices and collect data from them efficiently. The proposed scheme performs grouping of portable sensor devices connected to a system depending on the distance from the sink node and transmits data by setting different buffer thresholds to each group. This method reduces energy consumption of sensor devices located near the sink node and enhances the IoT system’s general energy efficiency. When a sensor device is moved and, thus, becomes unable to transmit data, it is allocated to a new group so that it can continue transmitting data to the sink node.

  18. 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.

  19. Recent Advances on Hybrid Intelligent Systems

    CERN Document Server

    Melin, Patricia; Kacprzyk, Janusz

    2013-01-01

    This book presents recent advances on hybrid intelligent systems using soft computing techniques for intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and bio-inspired optimization algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in five main parts, which contain groups of papers around a similar subject. The first part consists of papers with the main theme of hybrid intelligent systems for control and robotics, which are basically state of the art papers that propose new models and concepts, which can be the basis for achieving intelligent control and mobile robotics. The second part contains papers with the main theme of hybrid intelligent systems for pattern recognition and time series prediction, which are basically papers using nature-inspired techniques, like evolutionary algo...

  20. Using intelligent clustering techniques to classify the energy performance of school buildings

    Energy Technology Data Exchange (ETDEWEB)

    Santamouris, M.; Sfakianaki, K.; Papaglastra, M.; Pavlou, C.; Doukas, P.; Geros, V.; Assimakopoulos, M.N.; Zerefos, S. [University of Athens, Department of Physics, Division of Applied Physics, Laboratory of Meteorology, Athens (Greece); Mihalakakou, G.; Gaitani, N. [University of Ioannina, Department of Environmental and Natural Resources Management, Agrinio (Greece); Patargias, P. [University of Peloponnesus, Faculty of Human Sciences and Cultural Studies, Department of History, Kalamata (Greece); Primikiri, E. [University of Patras, Department of Architecture, Patras (Greece); Mitoula, R. [Charokopion University of Athens, Athens (Greece)

    2007-07-01

    The present paper deals with the energy performance, energy classification and rating and the global environmental quality of school buildings. A new energy classification technique based on intelligent clustering methodologies is proposed. Energy rating of school buildings provides specific information on their energy consumption and efficiency relative to the other buildings of similar nature and permits a better planning of interventions to improve its energy performance. The overall work reported in the present paper, is carried out in three phases. During the first phase energy consumption data have been collected through energy surveys performed in 320 schools in Greece. In the second phase an innovative energy rating scheme based on fuzzy clustering techniques has been developed, while in the third phase, 10 schools have been selected and detailed measurements of their energy efficiency and performance as well as of the global environmental quality have been performed using a specific experimental protocol. The proposed energy rating method has been applied while the main environmental and energy problems have been identified. The potential for energy and environmental improvements has been assessed. (author)

  1. 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.

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

    International Nuclear Information System (INIS)

    Mesquita, Roberto N. de; Perillo, Sergio R.P.; Santos, Roberto C. dos

    2005-01-01

    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)

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

    Science.gov (United States)

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

    2016-10-01

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

  4. Use of artificial intelligence techniques for optimisation of co-combustion of coal with biomass

    Energy Technology Data Exchange (ETDEWEB)

    Tan, C.K.; Wilcox, S.J.; Ward, J. [University of Glamorgan, Pontypridd (United Kingdom). Division of Mechanical Engineering

    2006-03-15

    The optimisation of burner operation in conventional pulverised-coal-fired boilers for co-combustion applications represents a significant challenge This paper describes a strategic framework in which Artificial Intelligence (AI) techniques can be applied to solve such an optimisation problem. The effectiveness of the proposed system is demonstrated by a case study that simulates the co-combustion of coal with sewage sludge in a 500-kW pilot-scale combustion rig equipped with a swirl stabilised low-NOx burner. A series of Computational Fluid Dynamics (CFD) simulations were performed to generate data for different operating conditions, which were then used to train several Artificial Neural Networks (ANNs) to predict the co-combustion performance. Once trained, the ANNs were able to make estimations of unseen situations in a fraction of the time taken by the CFD simulation. Consequently, the networks were capable of representing the underlying physics of the CFD models and could be executed efficiently for a large number of iterations as required by optimisation techniques based on Evolutionary Algorithms (EAs). Four operating parameters of the burner, namely the swirl angles and flow rates of the secondary and tertiary combustion air were optimised with the objective of minimising the NOx and CO emissions as well as the unburned carbon at the furnace exit. The results suggest that ANNs combined with EAs provide a useful tool for optimising co-combustion processes.

  5. 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)

  6. Digital image analysis in breast pathology-from image processing techniques to artificial intelligence.

    Science.gov (United States)

    Robertson, Stephanie; Azizpour, Hossein; Smith, Kevin; Hartman, Johan

    2018-04-01

    Breast cancer is the most common malignant disease in women worldwide. In recent decades, earlier diagnosis and better adjuvant therapy have substantially improved patient outcome. Diagnosis by histopathology has proven to be instrumental to guide breast cancer treatment, but new challenges have emerged as our increasing understanding of cancer over the years has revealed its complex nature. As patient demand for personalized breast cancer therapy grows, we face an urgent need for more precise biomarker assessment and more accurate histopathologic breast cancer diagnosis to make better therapy decisions. The digitization of pathology data has opened the door to faster, more reproducible, and more precise diagnoses through computerized image analysis. Software to assist diagnostic breast pathology through image processing techniques have been around for years. But recent breakthroughs in artificial intelligence (AI) promise to fundamentally change the way we detect and treat breast cancer in the near future. Machine learning, a subfield of AI that applies statistical methods to learn from data, has seen an explosion of interest in recent years because of its ability to recognize patterns in data with less need for human instruction. One technique in particular, known as deep learning, has produced groundbreaking results in many important problems including image classification and speech recognition. In this review, we will cover the use of AI and deep learning in diagnostic breast pathology, and other recent developments in digital image analysis. Copyright © 2017 Elsevier Inc. All rights reserved.

  7. Intelligible Artificial Intelligence

    OpenAIRE

    Weld, Daniel S.; Bansal, Gagan

    2018-01-01

    Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...

  8. Data Mining for Business Intelligence Concepts, Techniques, and Applications in Microsoft Office Excel(r) with XLMiner(r)

    CERN Document Server

    Shmueli, Galit; Bruce, Peter C

    2011-01-01

    Data Mining for Business Intelligence, Second Edition uses real data and actual cases to illustrate the applicability of data mining (DM) intelligence in the development of successful business models. Featuring complimentary access to XLMiner, the Microsoft Office Excel add-in, this book allows readers to follow along and implement algorithms at their own speed, with a minimal learning curve. In addition, students and practitioners of DM techniques are presented with hands-on, business-oriented applications. An abundant amount of exercises and examples, now doubled in number in the second edit

  9. BST-PINK PANTHER. An intelligent CAMAC crate controller

    International Nuclear Information System (INIS)

    Troester, D.A.

    1984-01-01

    A technical and functional description of the PINK system for intelligent, distributed data acquisition, data formatting, and data reduction is presented. The system has been developed to bypass some of the constraints of CAMAC when collecting data with the high-resolution π 0 spectrometers of the Basel-Stockholm-Thessaloniki (BST) Collaboration at CERN. (orig.)

  10. Traffic control and intelligent vehicle highway systems: a survey

    NARCIS (Netherlands)

    Baskar, L.D.; Schutter, B. de; Hellendoorn, J.; Papp, Z.

    2011-01-01

    Traffic congestion in highway networks is one of the main issues to be addressed by today's traffic management schemes. Automation combined with the increasing market penetration of on-line communication, navigation and advanced driver assistance systems will ultimately result in intelligent vehicle

  11. Intelligent control of PV system on the basis of the fuzzy recurrent neuronet*

    Science.gov (United States)

    Engel, E. A.; Kovalev, I. V.; Engel, N. E.

    2016-04-01

    This paper presents the fuzzy recurrent neuronet for PV system’s control. Based on the PV system’s state, the fuzzy recurrent neural net tracks the maximum power point under random perturbations. The validity and advantages of the proposed intelligent control of PV system are demonstrated by numerical simulations. The simulation results show that the proposed intelligent control of PV system achieves real-time control speed and competitive performance, as compared to a classical control scheme on the basis of the perturbation & observation algorithm.

  12. Developments in operator assistance techniques for nuclear power plant control and operation

    International Nuclear Information System (INIS)

    Poujol, A.; Papin, B.; Beltranda, G.; Soldermann, R.

    1989-01-01

    This paper describes an approach which has been developed in order to improve nuclear power plants control and monitoring in normal and abnormal situations. These developments take full advantage of the trend towards the computerization of control rooms in industrial continuous processes. This research program consists in a thorough exploration of different information processing techniques, ranking from the rather simple visual synthetization of informations on graphic displays to sophisticated Artificial Intelligence (AI) techniques. These techniques are put into application for the solving of man-machine interface problems in the different domains of plant operation

  13. The Effect of Paternal Age on Offspring Intelligence and Personality when Controlling for Parental Trait Levels

    Science.gov (United States)

    Arslan, Ruben C.; Penke, Lars; Johnson, Wendy; Iacono, William G.; McGue, Matt

    2014-01-01

    Paternal age at conception has been found to predict the number of new genetic mutations. We examined the effect of father’s age at birth on offspring intelligence, head circumference and personality traits. Using the Minnesota Twin Family Study sample we tested paternal age effects while controlling for parents’ trait levels measured with the same precision as offspring’s. From evolutionary genetic considerations we predicted a negative effect of paternal age on offspring intelligence, but not on other traits. Controlling for parental intelligence (IQ) had the effect of turning an initially positive association non-significantly negative. We found paternal age effects on offspring IQ and Multidimensional Personality Questionnaire Absorption, but they were not robustly significant, nor replicable with additional covariates. No other noteworthy effects were found. Parents’ intelligence and personality correlated with their ages at twin birth, which may have obscured a small negative effect of advanced paternal age (birth order and the Flynn effect. PMID:24587224

  14. The effect of paternal age on offspring intelligence and personality when controlling for paternal trait level.

    Science.gov (United States)

    Arslan, Ruben C; Penke, Lars; Johnson, Wendy; Iacono, William G; McGue, Matt

    2014-01-01

    Paternal age at conception has been found to predict the number of new genetic mutations. We examined the effect of father's age at birth on offspring intelligence, head circumference and personality traits. Using the Minnesota Twin Family Study sample we tested paternal age effects while controlling for parents' trait levels measured with the same precision as offspring's. From evolutionary genetic considerations we predicted a negative effect of paternal age on offspring intelligence, but not on other traits. Controlling for parental intelligence (IQ) had the effect of turning an initially positive association non-significantly negative. We found paternal age effects on offspring IQ and Multidimensional Personality Questionnaire Absorption, but they were not robustly significant, nor replicable with additional covariates. No other noteworthy effects were found. Parents' intelligence and personality correlated with their ages at twin birth, which may have obscured a small negative effect of advanced paternal age (birth order and the Flynn effect.

  15. Ultrascalable Techniques Applied to the Global Intelligence Community Information Awareness Common Operating Picture (IA COP)

    National Research Council Canada - National Science Library

    Valdes, Alfonso; Kadte, Jim

    2005-01-01

    The focus of this research is to develop detection, correlation, and representation approaches to address the needs of the Intelligence Community Information Awareness Common Operating Picture (IA COP...

  16. Enhanced situation awareness and decision making for an intelligent reconfigurable reactor power controller

    International Nuclear Information System (INIS)

    Kenney, S.J.; Edwards, R.M.

    1996-01-01

    A Learning Automata based intelligent reconfigurable controller has been adapted for use as a reactor power controller to achieve improved reactor temperature performance. The intelligent reconfigurable controller is capable of enforcing either a classical or an optimal reactor power controller based on control performance feedback. Four control performance evaluation measures: dynamically estimated average quadratic temperature error, power, rod reactivity and rod reactivity rate were developed to provide feedback to the control decision component of the intelligent reconfigurable controller. Fuzzy Logic and Neural Network controllers have been studied for inclusion in the bank of controllers that form the intermediate level of an enhanced intelligent reconfigurable reactor power controller (IRRPC). The increased number of alternatives available to the supervisory level of the IRRPC requires enhanced situation awareness. Additional performance measures have been designed and a method for synthesizing them into a single indication of the overall performance of the currently enforced reactor power controller has been conceptualized. Modification of the reward/penalty scheme implemented in the existing IRRPC to increase the quality of the supervisory level decision process has been studied. The logogen model of human memory (Morton, 1969) and individual controller design information could be used to allocate reward to the most appropriate controller. Methods for allocating supervisory level attention were also studied with the goal of maximizing learning rate

  17. Fuzzy gain scheduling of velocity PI controller with intelligent learning algorithm for reactor control

    International Nuclear Information System (INIS)

    Kim, Dong Yun; Seong, Poong Hyun

    1996-01-01

    In this study, we proposed a fuzzy gain scheduler with intelligent learning algorithm for a reactor control. In the proposed algorithm, we used the gradient descent method to learn the rule bases of a fuzzy algorithm. These rule bases are learned toward minimizing an objective function, which is called a performance cost function. The objective of fuzzy gain scheduler with intelligent learning algorithm is the generation of adequate gains, which minimize the error of system. The condition of every plant is generally changed as time gose. That is, the initial gains obtained through the analysis of system are no longer suitable for the changed plant. And we need to set new gains, which minimize the error stemmed from changing the condition of a plant. In this paper, we applied this strategy for reactor control of nuclear power plant (NPP), and the results were compared with those of a simple PI controller, which has fixed gains. As a result, it was shown that the proposed algorithm was superior to the simple PI controller

  18. The effect of paternal age on offspring intelligence and personality when controlling for paternal trait level

    OpenAIRE

    Arslan, Ruben C.; Penke, Lars; Johnson, Wendy; Iacono, William G.; McGue, Matt

    2013-01-01

    Paternal age at conception has been found to predict the number of new genetic mutations. We examined the effect of father’s age at birth on offspring intelligence, head circumference and personality traits. Using the Minnesota Twin Family Study sample we tested paternal age effects while controlling for parents’ trait levels measured with the same precision as offspring’s. From evolutionary genetic considerations we predicted a negative effect of paternal age on offspring intelligence, but n...

  19. Personality disorder, emotional intelligence, and locus of control of patients with alcohol dependence.

    Science.gov (United States)

    Prakash, Om; Sharma, Neelu; Singh, Amool R; Sengar, K S; Chaudhury, Suprakash; Ranjan, Jay Kumar

    2015-01-01

    To assess personality disorder (PD), emotional intelligence (EI), and locus of control of alcohol dependent (AD) patients and its comparison with normal controls. Based on purposive sampling technique, 33 AD patients were selected from the De-Addiction Ward of Ranchi Institute of Neuro-Psychiatry and Allied Sciences (RINPAS) and 33 matched normal subjects were selected from Ranchi and nearby places. Both the groups were matched on various sociodemographic parameters, that is, age, gender, and socioeconomic level. All participants were assessed with Millon Clinical Multiaxial Inventory-III, Mangal EI Inventory, and Locus of Control scale. Obtained responses were scored by using standard scoring procedures and subsequently statistically analyzed by using Chi-square test. AD patients have more comorbid pathological personality traits and disorders in comparison to their normal counterparts. Depressive, narcissistic, and paranoid PDs were prominent among AD group; followed by schizotypal, antisocial, negativistic, dependent, schizoid, sadistic, masochistic, and borderline PD. In comparison to normal participants, AD patients were significantly deficient in almost all the areas of EI and their locus of control was externally oriented. Patients with AD have significantly higher PDs, low EI, and an external orientation on the locus of control. Identification and management of these comorbid conditions are likely to improve the management and outcome of AD.

  20. Personality disorder, emotional intelligence, and locus of control of patients with alcohol dependence

    Directory of Open Access Journals (Sweden)

    Om Prakash

    2015-01-01

    Full Text Available Aim: To assess personality disorder (PD, emotional intelligence (EI, and locus of control of alcohol dependent (AD patients and its comparison with normal controls. Materials and Methods: Based on purposive sampling technique, 33 AD patients were selected from the De-Addiction Ward of Ranchi Institute of Neuro-Psychiatry and Allied Sciences (RINPAS and 33 matched normal subjects were selected from Ranchi and nearby places. Both the groups were matched on various sociodemographic parameters, that is, age, gender, and socioeconomic level. All participants were assessed with Millon Clinical Multiaxial Inventory-III, Mangal EI Inventory, and Locus of Control scale. Obtained responses were scored by using standard scoring procedures and subsequently statistically analyzed by using Chi-square test. Results: AD patients have more comorbid pathological personality traits and disorders in comparison to their normal counterparts. Depressive, narcissistic, and paranoid PDs were prominent among AD group; followed by schizotypal, antisocial, negativistic, dependent, schizoid, sadistic, masochistic, and borderline PD. In comparison to normal participants, AD patients were significantly deficient in almost all the areas of EI and their locus of control was externally oriented. Conclusion: Patients with AD have significantly higher PDs, low EI, and an external orientation on the locus of control. Identification and management of these comorbid conditions are likely to improve the management and outcome of AD.

  1. The Intelligent Control System and Experiments for an Unmanned Wave Glider.

    Science.gov (United States)

    Liao, Yulei; Wang, Leifeng; Li, Yiming; Li, Ye; Jiang, Quanquan

    2016-01-01

    The control system designing of Unmanned Wave Glider (UWG) is challenging since the control system is weak maneuvering, large time-lag and large disturbance, which is difficult to establish accurate mathematical model. Meanwhile, to complete marine environment monitoring in long time scale and large spatial scale autonomously, UWG asks high requirements of intelligence and reliability. This paper focuses on the "Ocean Rambler" UWG. First, the intelligent control system architecture is designed based on the cerebrum basic function combination zone theory and hierarchic control method. The hardware and software designing of the embedded motion control system are mainly discussed. A motion control system based on rational behavior model of four layers is proposed. Then, combining with the line-of sight method(LOS), a self-adapting PID guidance law is proposed to compensate the steady state error in path following of UWG caused by marine environment disturbance especially current. Based on S-surface control method, an improved S-surface heading controller is proposed to solve the heading control problem of the weak maneuvering carrier under large disturbance. Finally, the simulation experiments were carried out and the UWG completed autonomous path following and marine environment monitoring in sea trials. The simulation experiments and sea trial results prove that the proposed intelligent control system, guidance law, controller have favorable control performance, and the feasibility and reliability of the designed intelligent control system of UWG are verified.

  2. The Intelligent Control System and Experiments for an Unmanned Wave Glider

    Science.gov (United States)

    Liao, Yulei; Wang, Leifeng; Li, Yiming; Li, Ye; Jiang, Quanquan

    2016-01-01

    The control system designing of Unmanned Wave Glider (UWG) is challenging since the control system is weak maneuvering, large time-lag and large disturbance, which is difficult to establish accurate mathematical model. Meanwhile, to complete marine environment monitoring in long time scale and large spatial scale autonomously, UWG asks high requirements of intelligence and reliability. This paper focuses on the “Ocean Rambler” UWG. First, the intelligent control system architecture is designed based on the cerebrum basic function combination zone theory and hierarchic control method. The hardware and software designing of the embedded motion control system are mainly discussed. A motion control system based on rational behavior model of four layers is proposed. Then, combining with the line-of sight method(LOS), a self-adapting PID guidance law is proposed to compensate the steady state error in path following of UWG caused by marine environment disturbance especially current. Based on S-surface control method, an improved S-surface heading controller is proposed to solve the heading control problem of the weak maneuvering carrier under large disturbance. Finally, the simulation experiments were carried out and the UWG completed autonomous path following and marine environment monitoring in sea trials. The simulation experiments and sea trial results prove that the proposed intelligent control system, guidance law, controller have favorable control performance, and the feasibility and reliability of the designed intelligent control system of UWG are verified. PMID:28005956

  3. The Use of Intelligent Relays for the Sewer Cleaning Vehicle Control and Automation

    Directory of Open Access Journals (Sweden)

    O. Chiver

    2012-06-01

    Full Text Available The paper presents the way in which the electrical control and automation system of the 5 mc combined sewer and gully cleaning vehicle equipped by a local company was designed, using the intelligent relay of the easy 700 type of Moeller (Eaton company. The control of all the equipments is performed locally from the control panel and some of them can also by remote controlled by means of the radio waves. The program required by the intelligent relay was created, tested and implemented with the help of the dedicated software easy-soft 6, developed by the manufacturing company.

  4. DEVELOPMENT OF A VIRTUAL INTELLIGENCE TECHNIQUE FOR THE UPSTREAM OIL INDUSTRY

    Energy Technology Data Exchange (ETDEWEB)

    Iraj A. Salehi; Shahab D. Mohaghegh; Samuel Ameri

    2004-09-01

    The objective of the research and development work reported in this document was to develop a Virtual Intelligence Technique for optimization of the Preferred Upstream Management Practices (PUMP) for the upstream oil industry. The work included the development of a software tool for identification and optimization of the most influential parameters in upstream common practices as well as geological, geophysical and reservoir engineering studies. The work was performed in cooperation with three independent producing companies--Newfield Exploration, Chesapeake Energy, and Triad Energy--operating in the Golden Trend, Oklahoma. In order to protect data confidentiality, these companies are referred to as Company One, Two, Three in a randomly selected order. These producing companies provided geological, completion, and production data on 320 wells and participated in frequent technical discussions throughout the project. Research and development work was performed by Gas Technology Institute (GTI), West Virginia University (WVU), and Intelligent Solutions Inc. (ISI). Oklahoma Independent Petroleum Association (OIPA) participated in technology transfer and data acquisition efforts. Deliverables from the project are the present final report and a user-friendly software package (Appendix D) with two distinct functions: a characterization tool that identifies the most influential parameters in the upstream operations, and an optimization tool that seeks optimization by varying a number of influential parameters and investigating the coupled effects of these variations. The electronic version of this report is also included in Appendix D. The Golden Trend data were used for the first cut optimization of completion procedures. In the subsequent step, results from soft computing runs were used as the guide for detailed geophysical and reservoir engineering studies that characterize the cause-and-effect relationships between various parameters. The general workflow and the main

  5. Selective weed control using laser techniques

    OpenAIRE

    Marx, Christian; Pastrana-Perez, Julio; Hustedt, Michael; Barcikowski, Stephan; Haferkamp, Heinz; Rath, Thomas

    2012-01-01

    This contribution discusses technical and growth relevant aspects of using laser techniques for weed control. The research on thermal weed control via laser first focused on the interaction of laser beams and weed plants. Due to preliminary studies, a CO2-laser was selected for further studies with regard to the process factors laser energy, laser spot area, coverage of the weeds meristem, weed species (Amaranthus retroflexus), and weed growth stage. Thereby, the laser damage was modeled in o...

  6. An 'intelligent' approach to radioimmunoassay sample counting employing a microprocessor-controlled sample counter

    International Nuclear Information System (INIS)

    Ekins, R.P.; Sufi, S.; Malan, P.G.

    1978-01-01

    The enormous impact on medical science in the last two decades of microanalytical techniques employing radioisotopic labels has, in turn, generated a large demand for automatic radioisotopic sample counters. Such instruments frequently comprise the most important item of capital equipment required in the use of radioimmunoassay and related techniques and often form a principle bottleneck in the flow of samples through a busy laboratory. It is therefore imperative that such instruments should be used 'intelligently' and in an optimal fashion to avoid both the very large capital expenditure involved in the unnecessary proliferation of instruments and the time delays arising from their sub-optimal use. Most of the current generation of radioactive sample counters nevertheless rely on primitive control mechanisms based on a simplistic statistical theory of radioactive sample counting which preclude their efficient and rational use. The fundamental principle upon which this approach is based is that it is useless to continue counting a radioactive sample for a time longer than that required to yield a significant increase in precision of the measurement. Thus, since substantial experimental errors occur during sample preparation, these errors should be assessed and must be related to the counting errors for that sample. The objective of the paper is to demonstrate that the combination of a realistic statistical assessment of radioactive sample measurement, together with the more sophisticated control mechanisms that modern microprocessor technology make possible, may often enable savings in counter usage of the order of 5- to 10-fold to be made. (author)

  7. 'Intelligent' approach to radioimmunoassay sample counting employing a microprocessor controlled sample counter

    International Nuclear Information System (INIS)

    Ekins, R.P.; Sufi, S.; Malan, P.G.

    1977-01-01

    The enormous impact on medical science in the last two decades of microanalytical techniques employing radioisotopic labels has, in turn, generated a large demand for automatic radioisotopic sample counters. Such instruments frequently comprise the most important item of capital equipment required in the use of radioimmunoassay and related techniques and often form a principle bottleneck in the flow of samples through a busy laboratory. It is therefore particularly imperitive that such instruments should be used 'intelligently' and in an optimal fashion to avoid both the very large capital expenditure involved in the unnecessary proliferation of instruments and the time delays arising from their sub-optimal use. The majority of the current generation of radioactive sample counters nevertheless rely on primitive control mechanisms based on a simplistic statistical theory of radioactive sample counting which preclude their efficient and rational use. The fundamental principle upon which this approach is based is that it is useless to continue counting a radioactive sample for a time longer than that required to yield a significant increase in precision of the measurement. Thus, since substantial experimental errors occur during sample preparation, these errors should be assessed and must be releted to the counting errors for that sample. It is the objective of this presentation to demonstrate that the combination of a realistic statistical assessment of radioactive sample measurement, together with the more sophisticated control mechanisms that modern microprocessor technology make possible, may often enable savings in counter usage of the order of 5-10 fold to be made. (orig.) [de

  8. The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network.

    Science.gov (United States)

    Han, Gaining; Fu, Weiping; Wang, Wen; Wu, Zongsheng

    2017-05-30

    The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function) is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average) model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS), the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative) controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control.

  9. The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network

    Directory of Open Access Journals (Sweden)

    Gaining Han

    2017-05-01

    Full Text Available The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS, the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control.

  10. Development and Experimental Evaluation of Machine-Learning Techniques for an Intelligent Hairy Scalp Detection System

    Directory of Open Access Journals (Sweden)

    Wei-Chien Wang

    2018-05-01

    Full Text Available Deep learning has become the most popular research subject in the fields of artificial intelligence (AI and machine learning. In October 2013, MIT Technology Review commented that deep learning was a breakthrough technology. Deep learning has made progress in voice and image recognition, image classification, and natural language processing. Prior to deep learning, decision tree, linear discriminant analysis (LDA, support vector machines (SVM, k-nearest neighbors algorithm (K-NN, and ensemble learning were popular in solving classification problems. In this paper, we applied the previously mentioned and deep learning techniques to hairy scalp images. Hairy scalp problems are usually diagnosed by non-professionals in hair salons, and people with such problems may be advised by these non-professionals. Additionally, several common scalp problems are similar; therefore, non-experts may provide incorrect diagnoses. Hence, scalp problems have worsened. In this work, we implemented and compared the deep-learning method, the ImageNet-VGG-f model Bag of Words (BOW, with machine-learning classifiers, and histogram of oriented gradients (HOG/pyramid histogram of oriented gradients (PHOG with machine-learning classifiers. The tools from the classification learner apps were used for hairy scalp image classification. The results indicated that deep learning can achieve an accuracy of 89.77% when the learning rate is 1 × 10−4, and this accuracy is far higher than those achieved by BOW with SVM (80.50% and PHOG with SVM (53.0%.

  11. Using Intelligent Techniques in Construction Project Cost Estimation: 10-Year Survey

    Directory of Open Access Journals (Sweden)

    Abdelrahman Osman Elfaki

    2014-01-01

    Full Text Available Cost estimation is the most important preliminary process in any construction project. Therefore, construction cost estimation has the lion’s share of the research effort in construction management. In this paper, we have analysed and studied proposals for construction cost estimation for the last 10 years. To implement this survey, we have proposed and applied a methodology that consists of two parts. The first part concerns data collection, for which we have chosen special journals as sources for the surveyed proposals. The second part concerns the analysis of the proposals. To analyse each proposal, the following four questions have been set. Which intelligent technique is used? How have data been collected? How are the results validated? And which construction cost estimation factors have been used? From the results of this survey, two main contributions have been produced. The first contribution is the defining of the research gap in this area, which has not been fully covered by previous proposals of construction cost estimation. The second contribution of this survey is the proposal and highlighting of future directions for forthcoming proposals, aimed ultimately at finding the optimal construction cost estimation. Moreover, we consider the second part of our methodology as one of our contributions in this paper. This methodology has been proposed as a standard benchmark for construction cost estimation proposals.

  12. Application of Artificial Intelligence (AI) Programming Techniques to Tactical Guidance for Fighter Aircraft

    Science.gov (United States)

    McManus, John W.; Goodrich, Kenneth H.

    1989-01-01

    A research program investigating the use of Artificial Intelligence (AI) techniques to aid in the development of a Tactical Decision Generator (TDG) for Within-Visual-Range (WVR) air combat engagements is discussed. The application of AI methods for development and implementation of the TDG is presented. The history of the Adaptive Maneuvering Logic (AML) program is traced and current versions of the AML program are compared and contrasted with the TDG system. The Knowledge-Based Systems (KBS) used by the TDG to aid in the decision-making process are outlined in detail and example rules are presented. The results of tests to evaluate the performance of the TDG versus a version of AML and versus human pilots in the Langley Differential Maneuvering Simulator (DMS) are presented. To date, these results have shown significant performance gains in one-versus-one air combat engagements, and the AI-based TDG software has proven to be much easier to modify than the updated FORTRAN AML programs.

  13. Identification of cataract and post-cataract surgery optical images using artificial intelligence techniques.

    Science.gov (United States)

    Acharya, Rajendra Udyavara; Yu, Wenwei; Zhu, Kuanyi; Nayak, Jagadish; Lim, Teik-Cheng; Chan, Joey Yiptong

    2010-08-01

    Human eyes are most sophisticated organ, with perfect and interrelated subsystems such as retina, pupil, iris, cornea, lens and optic nerve. The eye disorder such as cataract is a major health problem in the old age. Cataract is formed by clouding of lens, which is painless and developed slowly over a long period. Cataract will slowly diminish the vision leading to the blindness. At an average age of 65, it is most common and one third of the people of this age in world have cataract in one or both the eyes. A system for detection of the cataract and to test for the efficacy of the post-cataract surgery using optical images is proposed using artificial intelligence techniques. Images processing and Fuzzy K-means clustering algorithm is applied on the raw optical images to detect the features specific to three classes to be classified. Then the backpropagation algorithm (BPA) was used for the classification. In this work, we have used 140 optical image belonging to the three classes. The ANN classifier showed an average rate of 93.3% in detecting normal, cataract and post cataract optical images. The system proposed exhibited 98% sensitivity and 100% specificity, which indicates that the results are clinically significant. This system can also be used to test the efficacy of the cataract operation by testing the post-cataract surgery optical images.

  14. Epileptic seizure predictors based on computational intelligence techniques: a comparative study with 278 patients.

    Science.gov (United States)

    Alexandre Teixeira, César; Direito, Bruno; Bandarabadi, Mojtaba; Le Van Quyen, Michel; Valderrama, Mario; Schelter, Bjoern; Schulze-Bonhage, Andreas; Navarro, Vincent; Sales, Francisco; Dourado, António

    2014-05-01

    The ability of computational intelligence methods to predict epileptic seizures is evaluated in long-term EEG recordings of 278 patients suffering from pharmaco-resistant partial epilepsy, also known as refractory epilepsy. This extensive study in seizure prediction considers the 278 patients from the European Epilepsy Database, collected in three epilepsy centres: Hôpital Pitié-là-Salpêtrière, Paris, France; Universitätsklinikum Freiburg, Germany; Centro Hospitalar e Universitário de Coimbra, Portugal. For a considerable number of patients it was possible to find a patient specific predictor with an acceptable performance, as for example predictors that anticipate at least half of the seizures with a rate of false alarms of no more than 1 in 6 h (0.15 h⁻¹). We observed that the epileptic focus localization, data sampling frequency, testing duration, number of seizures in testing, type of machine learning, and preictal time influence significantly the prediction performance. The results allow to face optimistically the feasibility of a patient specific prospective alarming system, based on machine learning techniques by considering the combination of several univariate (single-channel) electroencephalogram features. We envisage that this work will serve as benchmark data that will be of valuable importance for future studies based on the European Epilepsy Database. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  15. New evaluation methods for conceptual design selection using computational intelligence techniques

    Energy Technology Data Exchange (ETDEWEB)

    Huang, Hong Zhong; Liu, Yu; Li, Yanfeng; Wang, Zhonglai [University of Electronic Science and Technology of China, Chengdu (China); Xue, Lihua [Higher Education Press, Beijing (China)

    2013-03-15

    The conceptual design selection, which aims at choosing the best or most desirable design scheme among several candidates for the subsequent detailed design stage, oftentimes requires a set of tools to conduct design evaluation. Using computational intelligence techniques, such as fuzzy logic, neural network, genetic algorithm, and physical programming, several design evaluation methods are put forth in this paper to realize the conceptual design selection under different scenarios. Depending on whether an evaluation criterion can be quantified or not, the linear physical programming (LPP) model and the RAOGA-based fuzzy neural network (FNN) model can be utilized to evaluate design alternatives in conceptual design stage. Furthermore, on the basis of Vanegas and Labib's work, a multi-level conceptual design evaluation model based on the new fuzzy weighted average (NFWA) and the fuzzy compromise decision-making method is developed to solve the design evaluation problem consisting of many hierarchical criteria. The effectiveness of the proposed methods is demonstrated via several illustrative examples.

  16. New evaluation methods for conceptual design selection using computational intelligence techniques

    International Nuclear Information System (INIS)

    Huang, Hong Zhong; Liu, Yu; Li, Yanfeng; Wang, Zhonglai; Xue, Lihua

    2013-01-01

    The conceptual design selection, which aims at choosing the best or most desirable design scheme among several candidates for the subsequent detailed design stage, oftentimes requires a set of tools to conduct design evaluation. Using computational intelligence techniques, such as fuzzy logic, neural network, genetic algorithm, and physical programming, several design evaluation methods are put forth in this paper to realize the conceptual design selection under different scenarios. Depending on whether an evaluation criterion can be quantified or not, the linear physical programming (LPP) model and the RAOGA-based fuzzy neural network (FNN) model can be utilized to evaluate design alternatives in conceptual design stage. Furthermore, on the basis of Vanegas and Labib's work, a multi-level conceptual design evaluation model based on the new fuzzy weighted average (NFWA) and the fuzzy compromise decision-making method is developed to solve the design evaluation problem consisting of many hierarchical criteria. The effectiveness of the proposed methods is demonstrated via several illustrative examples.

  17. Performance analysis of visible light communication using the STBC-OFDM technique for intelligent transportation systems

    Science.gov (United States)

    Li, Changping; Yi, Ying; Lee, Kyujin; Lee, Kyesan

    2014-08-01

    Visible light communication (VLC) applied in an intelligent transportation system (ITS) has attracted growing attentions, but it also faces challenges, for example deep path loss and optical multi-path dispersion. In this work, we modelled an actual outdoor optical channel as a Rician channel and further proposed space-time block coding (STBC) orthogonal frequency-division multiplexing (OFDM) technology to reduce the influence of severe optical multi-path dispersion associated with such a mock channel for achieving the effective BER of 10-6 even at a low signal-to-noise ratio (SNR). In this case, the optical signals transmission distance can be extended as long as possible. Through the simulation results of STBC-OFDM and single-input-single-output (SISO) counterparts in bit error rate (BER) performance comparison, we can distinctly observe that the VLC-ITS system using STBC-OFDM technique can obtain a strongly improved BER performance due to multi-path dispersion alleviation.

  18. Myoelectric Control Techniques for a Rehabilitation Robot

    Directory of Open Access Journals (Sweden)

    Alan Smith

    2011-01-01

    Full Text Available This work examines two different types of myoelectric control schemes for the purpose of rehabilitation robot applications. The first is a commonly used technique based on a Gaussian classifier. It is implemented in real time for healthy subjects in addition to a subject with Central Cord Syndrome (CCS. The myoelectric control scheme is used to control three degrees of freedom (DOF on a robot manipulator which corresponded to the robot's elbow joint, wrist joint, and gripper. The classes of motion controlled include elbow flexion and extension, wrist pronation and supination, hand grasping and releasing, and rest. Healthy subjects were able to achieve 90% accuracy. Single DOF controllers were first tested on the subject with CCS and he achieved 100%, 96%, and 85% accuracy for the elbow, gripper, and wrist controllers respectively. Secondly, he was able to control the three DOF controller at 68% accuracy. The potential applications for this scheme are rehabilitation and teleoperation. To overcome limitations in the pattern recognition based scheme, a second myoelectric control scheme is also presented which is trained using electromyographic (EMG data derived from natural reaching motions in the sagittal plane. This second scheme is based on a time delayed neural network (TDNN which has the ability to control multiple DOF at once. The controller tracked a subject's elbow and shoulder joints in the sagittal plane. Results showed an average error of 19° for the two joints. This myoelectric control scheme has the potential of being used in the development of exoskeleton and orthotic rehabilitation applications.

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

    Science.gov (United States)

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

    1993-06-01

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

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

    International Nuclear Information System (INIS)

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

    1993-01-01

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

  1. Comparison of intelligent fuzzy based AGC coordinated PID controlled and PSS controlled AVR system

    Energy Technology Data Exchange (ETDEWEB)

    Mukherjee, V. [Department of Electrical Engineering, Asansol Engineering College, Asansol, West Bengal (India); Ghoshal, S.P. [Department of Electrical Engineering, National Institute of Technology, Durgapur, West Bengal (India)

    2007-11-15

    This paper attempts to investigate the performance of intelligent fuzzy based coordinated control of the Automatic Generation Control (AGC) loop and the excitation loop equipped with Proportional Integral Derivative (PID) controlled Automatic Voltage Regulator (AVR) system and Power System Stabilizer (PSS) controlled AVR system. The work establishes that PSS controlled AVR system is much more robust in dynamic performance of the system over a wide range of system operating configurations. Thus, it is revealed that PSS equipped AVR is much more superior than PID equipped AVR in damping the oscillation resulting in improved transient response. The paper utilizes a novel class of Particle Swarm Optimization (PSO) termed as Craziness based Particle Swarm Optimization (CRPSO) as optimizing tool to get optimal tuning of PSS parameters as well as the gains of PID controllers. For on-line, off-nominal operating conditions Takagi Sugeno Fuzzy Logic (TSFL) has been applied to obtain the off-nominal optimal gains of PID controllers and parameters of PSS. Implementation of TSFL helps to achieve very fast dynamic response. Fourth order model of generator with AVR and high gain thyristor excitation system is considered for PSS controlled system while normal gain exciter is considered for PID controlled system. Simulation study also reveals that with high gain exciter, PID control is not at all effective. Transient responses are achieved by using modal analysis. (author)

  2. Use of nuclear techniques in biological control

    International Nuclear Information System (INIS)

    Greany, Patrick D.; Carpenter, James E.

    2000-01-01

    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

  3. Design and Research of Intelligent Remote Control Fan Based on Single Chip Microcomputer and Bluetooth Technology

    Directory of Open Access Journals (Sweden)

    Zhang Xue-Xia

    2017-01-01

    Full Text Available This paper is designed for intelligent remote control fans. The design of the microcontroller as the core, the sensor, Bluetooth and Andrews system applied to the design of intelligent remote control fan. According to the temperature sensor to achieve the indoor temperature collection, to achieve and set the temperature comparison, thus affecting the fan speed. At the same time, the system according to the infrared sensor components to detect external factors, in order to achieve the running or stopping of the fan, that is, to achieve intelligent control of the fan. In addition, the system achieve the Bluetooth and mobile phone Andrews system of effective combination, and through the software program to complete the fan remote operation and wind speed control.

  4. Multidisciplinary Techniques and Novel Aircraft Control Systems

    Science.gov (United States)

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

    2000-01-01

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

  5. Intelligent energy management control of vehicle air conditioning system coupled with engine

    International Nuclear Information System (INIS)

    Khayyam, Hamid; Abawajy, Jemal; Jazar, Reza N.

    2012-01-01

    Vehicle Air Conditioning (AC) systems consist of an engine powered compressor activated by an electrical clutch. The AC system imposes an extra load to the vehicle's engine increasing the vehicle fuel consumption and emissions. Energy management control of the vehicle air conditioning is a nonlinear dynamic system, influenced by uncertain disturbances. In addition, the vehicle energy management control system interacts with different complex systems, such as engine, air conditioning system, environment, and driver, to deliver fuel consumption improvements. In this paper, we describe the energy management control of vehicle AC system coupled with vehicle engine through an intelligent control design. The Intelligent Energy Management Control (IEMC) system presented in this paper includes an intelligent algorithm which uses five exterior units and three integrated fuzzy controllers to produce desirable internal temperature and air quality, improved fuel consumption, low emission, and smooth driving. The three fuzzy controllers include: (i) a fuzzy cruise controller to adapt vehicle cruise speed via prediction of the road ahead using a Look-Ahead system, (ii) a fuzzy air conditioning controller to produce desirable temperature and air quality inside vehicle cabin room via a road information system, and (iii) a fuzzy engine controller to generate the required engine torque to move the vehicle smoothly on the road. We optimised the integrated operation of the air conditioning and the engine under various driving patterns and performed three simulations. Results show that the proposed IEMC system developed based on Fuzzy Air Conditioning Controller with Look-Ahead (FAC-LA) method is a more efficient controller for vehicle air conditioning system than the previously developed Coordinated Energy Management Systems (CEMS). - Highlights: ► AC interacts: vehicle, environment, driver components, and the interrelationships between them. ► Intelligent AC algorithm which uses

  6. An intensive insulinotherapy mobile phone application built on artificial intelligence techniques.

    Science.gov (United States)

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

    2010-01-01

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

  7. Effect of emotional intelligence in glycemic control in patients with type II diabetes

    Directory of Open Access Journals (Sweden)

    Monireh Mehdizadeh

    2017-11-01

    Full Text Available Diabetes, in addition to adverse physical effects, is associated with many psychological problems. The correlation between physical health and emotional intelligence are acceptable. The aim of this study was to determine the effect of emotional intelligence training in glycemic control in patients with type II diabetes. The present study was a quasi-experimental research, which was conducted in Mashhad city, Iran. The participants included 20 patients referring to the diabetic centers. They were selected through convenience sampling and randomly divided into two groups of experiment (n=10 and control (n=10. To measure blood glucose, the level of HbA1c in patients was measured before and after training. The experimental group attended in a period of emotional intelligence training. The training sessions were held as group discussion during 8 weeks, one session of 120-min per week. The findings suggest that emotional intelligence training significantly reduced the level of blood glucose (HbA1c in the test group compared to the control group. Based on the results, emotional intelligence training, as a psychological intervention, by affecting understanding, interpretation, regulation and efficient use of excitement, is effective along with medication therapy in controlling blood glucose in type II diabetic patients.

  8. Intelligent voltage control in a DC micro-grid containing PV generation and energy storage

    OpenAIRE

    Rouzbehi, Kumars; Miranian, Arash; Candela García, José Ignacio; Luna Alloza, Álvaro; Rodríguez Cortés, Pedro

    2014-01-01

    This paper proposes an intelligent control scheme for DC voltage regulationin a DC micro-grid integrating photovoltaic (PV) generation, energy storage and electric loads. The maximum power generation of the PV panel is followed using the incremental conductance (IC) maximum power point tracking (MPPT) algorithm while a high-performance local linear controller (LLC)is developed for the DC voltage control in the micro-grid.The LLC, as a data-driven control strategy, controls the bidirectional c...

  9. Artificial Intelligence-based control for torque ripple minimization in switched reluctance motor drives - doi: 10.4025/actascitechnol.v36i1.18097

    Directory of Open Access Journals (Sweden)

    Kalaivani Lakshmanan

    2014-01-01

    Full Text Available In this paper, various intelligent controllers such as Fuzzy Logic Controller (FLC and Adaptive Neuro Fuzzy Inference System (ANFIS-based current compensating techniques are employed for minimizing the torque ripples in switched reluctance motor. FLC and ANFIS controllers are tuned using MATLAB Toolbox. For the purpose of comparison, the performance of conventional Proportional-Integral (PI controller is also considered. The statistical parameters like minimum, maximum, mean, standard deviation of total torque, torque ripple coefficient and the settling time of speed response for various controllers are reported. From the simulation results, it is found that both FLC and ANFIS controllers gives better performance than PI controller. Among the intelligent controllers, ANFIS gives outer performance than FLC due to its good learning and generalization capabilities thereby improves the dynamic performance of SRM drives.

  10. 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.

  11. Constraint, Intelligence, and Control Hierarchy in Virtual Environments. Chapter 1

    Science.gov (United States)

    Sheridan, Thomas B.

    2007-01-01

    This paper seeks to deal directly with the question of what makes virtual actors and objects that are experienced in virtual environments seem real. (The term virtual reality, while more common in public usage, is an oxymoron; therefore virtual environment is the preferred term in this paper). Reality is difficult topic, treated for centuries in those sub-fields of philosophy called ontology- "of or relating to being or existence" and epistemology- "the study of the method and grounds of knowledge, especially with reference to its limits and validity" (both from Webster s, 1965). Advances in recent decades in the technologies of computers, sensors and graphics software have permitted human users to feel present or experience immersion in computer-generated virtual environments. This has motivated a keen interest in probing this phenomenon of presence and immersion not only philosophically but also psychologically and physiologically in terms of the parameters of the senses and sensory stimulation that correlate with the experience (Ellis, 1991). The pages of the journal Presence: Teleoperators and Virtual Environments have seen much discussion of what makes virtual environments seem real (see, e.g., Slater, 1999; Slater et al. 1994; Sheridan, 1992, 2000). Stephen Ellis, when organizing the meeting that motivated this paper, suggested to invited authors that "We may adopt as an organizing principle for the meeting that the genesis of apparently intelligent interaction arises from an upwelling of constraints determined by a hierarchy of lower levels of behavioral interaction. "My first reaction was "huh?" and my second was "yeah, that seems to make sense." Accordingly the paper seeks to explain from the author s viewpoint, why Ellis s hypothesis makes sense. What is the connection of "presence" or "immersion" of an observer in a virtual environment, to "constraints" and what types of constraints. What of "intelligent interaction," and is it the intelligence of the

  12. ARGUMENTS ON USING COMPUTER-ASSISTED AUDIT TECHNIQUES (CAAT AND BUSINESS INTELLIGENCE TO IMPROVE THE WORK OF THE FINANCIAL AUDITOR

    Directory of Open Access Journals (Sweden)

    Ciprian-Costel, MUNTEANU

    2014-11-01

    Full Text Available In the 21st century, one of the most efficient ways to achieve an independent audit and quality opinion is by using information from the organization database, mainly documents in electronic format. With the help of Computer-Assisted Audit Techniques (CAAT, the financial auditor analyzes part or even all the data about a company in reference to other information within or outside the entity. The main purpose of this paper is to show the benefits of evolving from traditional audit techniques and tools to modern and , why not, visionary CAAT, which are supported by business intelligence systems. Given the opportunity to perform their work in IT environments, the auditors would start using the tools of business intelligence, a key factor which contributes to making successful business decisions . CAAT enable auditors to test large amount of data quickly and accurately and therefore increase the confidence they have in their opinion.

  13. 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.

  14. Intelligent control for braking-induced longitudinal vibration responses of floating-type railway bridges

    Science.gov (United States)

    Qu, Wei-Lian; Qin, Shun-Quan; Tu, Jian-Weia; Liu, Jia; Zhou, Qiang; Cheng, Haibin; Pi, Yong-Lin

    2009-12-01

    This paper presents an intelligent control method and its engineering application in the control of braking-induced longitudinal vibration of floating-type railway bridges. Equations of motion for the controlled floating-type railway bridges have been established based on the analysis of the longitudinal vibration responses of floating-type railway bridges to train braking and axle-loads of moving trains. For engineering applications of the developed theory, a full-scale 500 kN smart magnetorheologic (MR) damper has been designed, fabricated and used to carry out experiments on the intelligent control of braking-induced longitudinal vibration. The procedure for using the developed intelligent method in conjunction with the full-scale 500 kN MR dampers has been proposed and used to control the longitudinal vibration responses of the deck of floating-type railway bridges induced by train braking and axle-loads of moving trains. This procedure has been applied to the longitudinal vibration control of the Tian Xingzhou highway and railway cable-stayed bridge over the Yangtze River in China. The simulated results have shown that the intelligent control system using the smart MR dampers can effectively control the longitudinal response of the floating-type railway bridge under excitations of braking and axle-loads of moving trains.

  15. Intelligent control for braking-induced longitudinal vibration responses of floating-type railway bridges

    International Nuclear Information System (INIS)

    Qu, Wei-Lian; Tu, Jian-Weia; Liu, Jia; Zhou, Qiang; Qin, Shun-Quan; Cheng, Haibin; Pi, Yong-Lin

    2009-01-01

    This paper presents an intelligent control method and its engineering application in the control of braking-induced longitudinal vibration of floating-type railway bridges. Equations of motion for the controlled floating-type railway bridges have been established based on the analysis of the longitudinal vibration responses of floating-type railway bridges to train braking and axle-loads of moving trains. For engineering applications of the developed theory, a full-scale 500 kN smart magnetorheologic (MR) damper has been designed, fabricated and used to carry out experiments on the intelligent control of braking-induced longitudinal vibration. The procedure for using the developed intelligent method in conjunction with the full-scale 500 kN MR dampers has been proposed and used to control the longitudinal vibration responses of the deck of floating-type railway bridges induced by train braking and axle-loads of moving trains. This procedure has been applied to the longitudinal vibration control of the Tian Xingzhou highway and railway cable-stayed bridge over the Yangtze River in China. The simulated results have shown that the intelligent control system using the smart MR dampers can effectively control the longitudinal response of the floating-type railway bridge under excitations of braking and axle-loads of moving trains

  16. Research and development of intelligent controller for high-grade sanitary ware

    Science.gov (United States)

    Bao, Kongjun; Shen, Qingping

    2013-03-01

    With the social and economic development and people's living standards improve, more and more emphasis on modern society, people improve the quality of family life, the use of intelligent controller applications in high-grade sanitary ware physiotherapy students. Analysis of high-grade sanitary ware physiotherapy common functions pointed out in the production and use of the possible risks, proposed implementation of the system hardware and matching, given the system software implementation process. High-grade sanitary ware physiotherapy intelligent controller not only to achieve elegant and beautiful, simple, physical therapy, water power, deodorant, multi-function, intelligent control, to meet the consumers, the high-end sanitary ware market, strong demand, Accelerate the enterprise product Upgrade and improve the competitiveness of enterprises.

  17. Machine throughput improvement achieved using innovative control technique

    International Nuclear Information System (INIS)

    Sharma, V.; Acharya, S.; Mittal, K.C.

    2012-01-01

    In any type of fully or semi automatic machine the control systems plays an important role. The control system on the one hand has to consider the human psychology, intelligence requirement for an operator, and attention needed from him. On the other hand the complexity of the control has also to be understood well before designing a control system that can be handled comfortably and safely by the operator. As far as the user experience/comfort is concerned the design of control system GUI is vital. Considering these two aspects related to the user of the machine it is evident that the control system design is very important because it is has to accommodate the human behaviour and skill sets required/available as well as the capability of the machine under the control of the control system. An intelligently designed control system can enhance the productivity of the machine. (author)

  18. Intelligent battery energy management and control for vehicle-to-grid via cloud computing network

    International Nuclear Information System (INIS)

    Khayyam, Hamid; Abawajy, Jemal; Javadi, Bahman; Goscinski, Andrzej; Stojcevski, Alex; Bab-Hadiashar, Alireza

    2013-01-01

    Highlights: • The intelligent battery energy management substantially reduces the interactions of PEV with parking lots. • The intelligent battery energy management improves the energy efficiency. • The intelligent battery energy management predicts the road load demand for vehicles. - Abstract: Plug-in Electric Vehicles (PEVs) provide new opportunities to reduce fuel consumption and exhaust emission. PEVs need to draw and store energy from an electrical grid to supply propulsive energy for the vehicle. As a result, it is important to know when PEVs batteries are available for charging and discharging. Furthermore, battery energy management and control is imperative for PEVs as the vehicle operation and even the safety of passengers depend on the battery system. Thus, scheduling the grid power electricity with parking lots would be needed for efficient charging and discharging of PEV batteries. This paper aims to propose a new intelligent battery energy management and control scheduling service charging that utilize Cloud computing networks. The proposed intelligent vehicle-to-grid scheduling service offers the computational scalability required to make decisions necessary to allow PEVs battery energy management systems to operate efficiently when the number of PEVs and charging devices are large. Experimental analyses of the proposed scheduling service as compared to a traditional scheduling service are conducted through simulations. The results show that the proposed intelligent battery energy management scheduling service substantially reduces the required number of interactions of PEV with parking lots and grid as well as predicting the load demand calculated in advance with regards to their limitations. Also it shows that the intelligent scheduling service charging using Cloud computing network is more efficient than the traditional scheduling service network for battery energy management and control

  19. Optimization of fuel exchange machine operation for boiling water reactors using an artificial intelligence technique

    International Nuclear Information System (INIS)

    Sekimizu, K.; Araki, T.; Tatemichi, S.I.

    1987-01-01

    Optimization of fuel assembly exchange machine movements during periodic refueling outage is discussed. The fuel assembly movements during a fuel shuffling were examined, and it was found that the fuel assembly movements consist of two different movement sequences;one is the ''PATH,'' which begins at a discharged fuel assembly and terminates at a fresh fuel assembly, and the other is the ''LOOP,'' where fuel assemblies circulate in the core. It is also shown that fuel-loading patterns during the fuel shuffling can be expressed by the state of each PATH, which is the number of elements already accomplished in the PATH actions. Based on this fact, a scheme to determine a fuel assembly movement sequence within the constraint was formulated using the artificial intelligence language PROLOG. An additional merit to the scheme is that it can simultaneously evaluate fuel assembly movement, due to the control rods and local power range monitor exchange, in addition to normal fuel shuffling. Fuel assembly movements, for fuel shuffling in a 540-MW(electric) boiling water reactor power plant, were calculated by this scheme. It is also shown that the true optimization to minimize the fuel exchange machine movements would be costly to obtain due to the number of alternatives that would need to be evaluated. However, a method to obtain a quasi-optimum solution is suggested

  20. A Three Pronged Approach for Improved Data Understanding: 3-D Visualization, Use of Gaming Techniques, and Intelligent Advisory Agents

    Science.gov (United States)

    2006-10-01

    Pronged Approach for Improved Data Understanding: 3-D Visualization, Use of Gaming Techniques, and Intelligent Advisory Agents. In Visualising Network...University at the start of each fall semester, when numerous new students arrive on campus and begin downloading extensive amounts of audio and...SIGGRAPH ’92 • C. Cruz-Neira, D.J. Sandin, T.A. DeFanti, R.V. Kenyon and J.C. Hart, "The CAVE: Audio Visual Experience Automatic Virtual Environment

  1. 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.

  2. Overall intelligent hybrid control system for a fossil-fuel power unit

    Energy Technology Data Exchange (ETDEWEB)

    Garduno-Ramirez, Raul

    2000-08-01

    -level hierarchical intelligent hybrid multi-agent coordinated control system. Results show the feasibility of the proposed ICCS paradigm. An open purposeful self-governing overall unit control system for a FFPU can be systematically designed, built and upgrade to effectively satisfy arbitrary operation conditions. Remarkably, the ICCS paradigm provides a convenient conceptual framework such that the integration of applications can be carried out making use of best characteristics that either algorithmic or heuristic techniques have to offer, while keeping large system complexity manageable. [Spanish] Se presenta una metodologia para disenar un sistema unitario generalizado de control total para una unidad generadora de combustible fosil (FFPU) y se desarrolla un prototipo minimo para demostrar su factibilidad. Con miras a la meta mencionada, se emprendio el proyecto asociado de investigacion como un proceso de innovacion tecnologica con sus dos fines identificados como sigue. Primero, se reconoce que las estrategias de control combinado constituyen el mas alto nivel de control en las actuales FFPUs, y de esta manera son responsables de manejar el conjunto caldera-turbina-generador como una sola entidad. Segundo, una FFPU se visualiza como un proceso complejo, sujeto a muchas condiciones cambiantes de operacion, que debe de comportarse como un sistema inteligente, para lo cual se requiere un concepto de control integral avanzado. Por lo tanto, como un resultado del proceso de innovacion se propone un concepto de control integral de unidad generalizado que amplia el potencial de los esquemas actuales de control coordinado. Este concepto se presenta como el paradigma del Sistema de Control Coordinado Inteligente (ICCS), que establece un marco de referencia abierto para el desarrollo de esquemas de control unitario en conjunto. Las metas del sistema ICCS se identifican usando conceptos de ingenieria de procesos de centrales electricas y conceptos de ingenieria de sistemas inteligentes

  3. Modern insect control: Nuclear techniques and biotechnology

    International Nuclear Information System (INIS)

    1988-01-01

    The Symposium dealt primarily with genetic methods of insect control, including sterile insect technique (SIT), F 1 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 F 1 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

  4. 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.

  5. Wireless Intelligent Monitoring and Control System of Greenhouse Temperature Based on Fuzzy-PID

    Directory of Open Access Journals (Sweden)

    Mei ZHAN

    2014-03-01

    Full Text Available Control effect is not ideal for traditional control method and wired control system, since greenhouse temperature has such characteristics as nonlinear and longtime lag. Therefore, Fuzzy- PID control method was introduced and radio frequency chip CC1110 was applied to design greenhouse wireless intelligent monitoring and control system. The design of the system, the component of nodes and the developed intelligent management software system were explained in this paper. Then describe the design of the control algorithm Fuzzy-PID. By simulating the new method in Matlab software, the results showed that Fuzzy-PID method small overshoot and better dynamic performance compared with general PID control. It has shorter settling time and no steady-state error compared with fuzzy control. It can meet requirements in greenhouse production.

  6. Towards Realization of Intelligent Medical Treatment at Nanoscale by Artificial Microscopic Swarm Control Systems

    Directory of Open Access Journals (Sweden)

    Alireza Rowhanimanesh

    2017-07-01

    Full Text Available Background: In this paper, the novel concept of artificial microscopic swarm control systems is proposed as a promising approach towards realization of intelligent medical treatment at nanoscale. In this new paradigm, treatment is done autonomously at nanoscale within the patient’s body by the proposed swarm control systems.Methods: From control engineering perspective, medical treatment can be considered as a control problem, in which the ultimate goal is to find the best feasible way to change the state of diseased tissue from unhealthy to healthy in presence of uncertainty. Although a living tissue is a huge swarm of microscopic cells, nearly all of the common treatment methods are based on macroscopic centralized control paradigm. Inspired by natural microscopic swarm control systems such as nervous, endocrine and immune systems that work based on swarm control paradigm, medical treatment needs a paradigm shift from macroscopic centralized control to microscopic swarm control. An artificial microscopic swarm control system consists of a huge number of very simple autonomous microscopic agents that exploit swarm intelligence to realize sense, control (computing and actuation at nanoscale in local, distributed and decentralized manner. This control system can be designed based on mathematical analysis and computer simulation.Results: The proposed approach is used for treatment of atherosclerosis and cancer based on mathematical analysis and in-silico study.Conclusion: The notion of artificial microscopic swarm control systems opens new doors towards realization of autonomous and intelligent medical treatment at nanoscale within the patient’s body.

  7. Intelligent Photovoltaic Maximum Power Point Tracking Controller for Energy Enhancement in Renewable Energy System

    Directory of Open Access Journals (Sweden)

    Subiyanto

    2013-01-01

    Full Text Available Photovoltaic (PV system is one of the promising renewable energy technologies. Although the energy conversion efficiency of the system is still low, but it has the advantage that the operating cost is free, very low maintenance and pollution-free. Maximum power point tracking (MPPT is a significant part of PV systems. This paper presents a novel intelligent MPPT controller for PV systems. For the MPPT algorithm, an optimized fuzzy logic controller (FLC using the Hopfield neural network is proposed. It utilizes an automatically tuned FLC membership function instead of the trial-and-error approach. The MPPT algorithm is implemented in a new variant of coupled inductor soft switching boost converter with high voltage gain to increase the converter output from the PV panel. The applied switching technique, which includes passive and active regenerative snubber circuits, reduces the insulated gate bipolar transistor switching losses. The proposed MPPT algorithm is implemented using the dSPACE DS1104 platform software on a DS1104 board controller. The prototype MPPT controller is tested using an agilent solar array simulator together with a 3 kW real PV panel. Experimental test results show that the proposed boost converter produces higher output voltages and gives better efficiency (90% than the conventional boost converter with an RCD snubber, which gives 81% efficiency. The prototype MPPT controller is also found to be capable of tracking power from the 3 kW PV array about 2.4 times more than that without using the MPPT controller.

  8. New Concepts and Theories For Intelligent Control of Cellular Manufacturing Systems

    DEFF Research Database (Denmark)

    Langer, Gilad

    1996-01-01

    This paper will present some new theories such as biological manufacturing system, the fractal factory theory, holonic manufacturing systems, agile manufacturing, object orientation, multi-agent theory, artificial intelligence, and artificial life in the context of manufacturing systems....... The paper tries to encapsulate the main area of my Ph.D. thesis research which will evolve around the idea of integrating intelligent elements into the control systems of the manufacturing systems. Furthermore it intends to show how the curriculum and discussions of the IPS Ph.D. course will and have...... contributed to my research. The research will concentrate on integration of manufacturing units by use of intelligent control mechanisms, information technology and the material handling as the key integrators....

  9. Locus of control, hardiness, and emotional intelligence as predictors of waste prevention behaviours

    Directory of Open Access Journals (Sweden)

    Abdollahi, A.

    2015-07-01

    Full Text Available Given that waste generation is an economic and environmental problem for nations and governments, it is necessary that we advance our knowledge on the etiology of waste prevention behaviours. This study aimed to investigate about the relationships between the locus of control, hardiness, emotional intelligence, and waste prevention behaviours. Four hundred and forty participants (226 females and 214 males from Universiti Putra Malaysia completed a survey questionnaire. Structural Equation Modeling (SEM estimated that individuals who were high in emotional intelligence and hardiness showed better waste prevention behaviours as well as those individuals with internal locus of control. Also, the results showed that older students tend to have better waste prevention behaviours. These findings reinforce the importance of personality traits and emotional intelligence in waste prevention behaviours.

  10. Artificial intelligence utilization in power generation units control systems; Utilizacao de inteligencia artificial em sistemas de controle de unidades geradoras

    Energy Technology Data Exchange (ETDEWEB)

    Souza, G N [CEPEL, Rio de Janeiro, RJ (Brazil); Mendes, S B [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

    1992-12-31

    To the implementation of the logics of control in a hydroelectric power plant artificial languages or complexes formalisms are used which cause error introduction in the description process of such logic. This work suggests the use of an intelligent and interactive system with interface in natural language to the control description as a solution to this problem. 28 refs., 3 figs.

  11. Artificial intelligence utilization in power generation units control systems; Utilizacao de inteligencia artificial em sistemas de controle de unidades geradoras

    Energy Technology Data Exchange (ETDEWEB)

    Souza, G.N. [CEPEL, Rio de Janeiro, RJ (Brazil); Mendes, S.B. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

    1991-12-31

    To the implementation of the logics of control in a hydroelectric power plant artificial languages or complexes formalisms are used which cause error introduction in the description process of such logic. This work suggests the use of an intelligent and interactive system with interface in natural language to the control description as a solution to this problem. 28 refs., 3 figs.

  12. Integrated environmental control and monitoring in the intelligent workplace. Final report

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-12-31

    This project involved the design and engineering of the control and monitoring of environmental quality - visual, thermal, air - in the Intelligent Workplace. The research objectives were to study the performance of the individual systems, to study the integration issues related to each system, to develop a control plan, and to implement and test the integrated systems in a real setting. In this project, a control strategy with related algorithms for distributed sensors, actuators, and controllers for negotiating central and individual control of HVAC, lighting, and enclosure was developed in order to maximize user comfort, and energy and environmental effectiveness. The goal of the control system design in the Intelligent Workplace is the integration of building systems for optimization of occupant satisfaction, organizational flexibility, energy efficiency and environmental effectiveness. The task of designing this control system involves not only the research, development and demonstration of state-of-the-art mechanical and electrical systems, but also their integration. The ABSIC research team developed functional requirements for the environmental systems considering the needs of both facility manager and the user. There are three levels of control for the environmental systems: scheduled control, sensor control, and user control. The challenges are to achieve the highest possible levels of energy effectiveness simultaneously with the highest levels of user satisfaction. The report describes the components of each system, their implementation in the Intelligent Workplace and related control and monitoring issues.

  13. Investigation and study on each technique and example of intelligent planning; Intelligent planning no kakushu shuho to jirei ni kansuru chosa kenkyu

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1995-12-11

    Various problems on intelligent planning (IP) and the tendency of basic technology were investigated. For each technique of IP, a Petri net and mark graph have been widely used as the modeling and analysis methods of a discrete event system. Moreover, various planning problems were modeled by a traveling salesman problem, and the efficient solution of the traveling salesman problem has been studied simultaneously. The tendency of the basic technology and application system viewed from an example of intelligent plant planning was investigated as an applied field of planning technology, with importance attached to the production system and robot planning. In the scheduling technology of the production system, the activation of an AI study and a new theory (i.e., architecture study) based on natural science information was investigated with the transition in the world as a trigger. A robot system has been planned in a wide range such as the environmental information acquisition planning of a robot. 202 refs., 69 figs., 4 tabs.

  14. Assistance system 2000: Intelligent control system from DANOTEK; Assistanceordning 2000: Intelligent styresystem fra DANOTEK

    Energy Technology Data Exchange (ETDEWEB)

    Knudsen, S.

    2001-07-01

    This report describes performed investigations of a control system for a smart solar tank. The company Danotek has developed the control system. The smart solar tanks are characterised by having a flexble regulation by the consumer of the heat supply from the auxiliary energy supply system. The domestic water is only heated by the auxiliary energy supply system at times when the consumer needs hot water. Further, the water volume heated by the auxiliary energy supply system is fitted to the hot water demand. A solar domestic hot water (SDHW) system based on a smart solar tank is very suitable for both small, large, and variable hot water consumption due to the flexible control of the auxiliary energy supply system. The smart control system from Danotek has been investigated both experimentally and theoretically. The experimental investigations have been carried out in a test facility for solar heating systems at the Technical University of Denmark where the control system was installed in a SDHW system. The theoretical investigations were made with a computer simulation program, Kappesol, which is used for the calculation of annual thermal performance of low flow solar heating systems with mantle tanks. The test of the smart control system in the test facility proved that the smart control system is operating well and that it is able to meet the required hot water comfort. The thermal performance of the SDHW system with the smart control system was measured and compared with the thermal performance of a low flow SDHW system with a traditional control system. The measurements showed that the SDHW system with the smart control system had a thermal performance that was 25% higher than the thermal performance of the SDHW system with the traditional control system. The theoretical investigations with the above-mentioned computer simulation program showed that it is important for the thermal performance of the SDHW system with the smart control system that the consumers

  15. The effect of paternal age on offspring intelligence and personality when controlling for paternal trait level.

    Directory of Open Access Journals (Sweden)

    Ruben C Arslan

    Full Text Available Paternal age at conception has been found to predict the number of new genetic mutations. We examined the effect of father's age at birth on offspring intelligence, head circumference and personality traits. Using the Minnesota Twin Family Study sample we tested paternal age effects while controlling for parents' trait levels measured with the same precision as offspring's. From evolutionary genetic considerations we predicted a negative effect of paternal age on offspring intelligence, but not on other traits. Controlling for parental intelligence (IQ had the effect of turning an initially positive association non-significantly negative. We found paternal age effects on offspring IQ and Multidimensional Personality Questionnaire Absorption, but they were not robustly significant, nor replicable with additional covariates. No other noteworthy effects were found. Parents' intelligence and personality correlated with their ages at twin birth, which may have obscured a small negative effect of advanced paternal age (<1% of variance explained on intelligence. We discuss future avenues for studies of paternal age effects and suggest that stronger research designs are needed to rule out confounding factors involving birth order and the Flynn effect.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2003-07-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2003-07-01

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

  18. Research review: Indoor air quality control techniques

    International Nuclear Information System (INIS)

    Fisk, W.J.

    1986-10-01

    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

  19. The design schemes of database and intelligent local controller in the SRRC control system

    International Nuclear Information System (INIS)

    Wang, C.J.; Chen, Jenny; Chen, J.S.; Jan, G.J.

    1994-01-01

    The control system of the SRRC has been utilized to facilitate commisioning since the beginning, and it provides operators an easy to use environment. Hence, we would like to discuss the design schemes and relationships between the user's interface, the database and the ILC (Intelligent Local Controller) levels. The whole control system in SRRC is a two-level design connected by Ethernet. From operator's view, the upper level is the CONSOLE level and the lower one is the ILC level. Those signals from, or to, equipment are connected to ILCs through analog/digital interfaces, GPIB buses, RS232 serial links, etc.; the ILC is an IEEE 1014 bus (VMEbus) based system running PSOS+ real-time multi-tasking kernel and PNA+ (TCP/IP protocols) communication software. The control software of CONSOLE level is developed in the VMS operating system on DEC workstations, and The Graphic User Interfaces are built on the X-Window/Motif environment. The control system has fulfilled the expectations of the facility commissioning group. It has also proved to be a simple, stable, accurate, easily maintained system. ((orig.))

  20. Intelligent control of non-linear dynamical system based on the adaptive neurocontroller

    Science.gov (United States)

    Engel, E.; Kovalev, I. V.; Kobezhicov, V.

    2015-10-01

    This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the base of system's state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simulation results show that the proposed controller scheme achieves real-time control speed and the competitive performance, as compared to PID, fuzzy logic controllers.