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Fuzzy Neural Networks for Real Time Control Applications

Fuzzy Neural Networks for Real Time Control Applications
  • Author : Erdal Kayacan,Mojtaba Ahmadieh Khanesar
  • Publisher :Unknown
  • Release Date :2015-10-07
  • Total pages :264
  • ISBN : 9780128027035
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Summary : AN INDISPENSABLE RESOURCE FOR ALL THOSE WHO DESIGN AND IMPLEMENT TYPE-1 AND TYPE-2 FUZZY NEURAL NETWORKS IN REAL TIME SYSTEMS Delve into the type-2 fuzzy logic systems and become engrossed in the parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis with this book! Not only does this book stand apart from others in its focus but also in its application-based presentation style. Prepared in a way that can be easily understood by those who are experienced and inexperienced in this field. Readers can benefit from the computer source codes for both identification and control purposes which are given at the end of the book. A clear and an in-depth examination has been made of all the necessary mathematical foundations, type-1 and type-2 fuzzy neural network structures and their learning algorithms as well as their stability analysis. You will find that each chapter is devoted to a different learning algorithm for the tuning of type-1 and type-2 fuzzy neural networks; some of which are: • Gradient descent • Levenberg-Marquardt • Extended Kalman filter In addition to the aforementioned conventional learning methods above, number of novel sliding mode control theory-based learning algorithms, which are simpler and have closed forms, and their stability analysis have been proposed. Furthermore, hybrid methods consisting of particle swarm optimization and sliding mode control theory-based algorithms have also been introduced. The potential readers of this book are expected to be the undergraduate and graduate students, engineers, mathematicians and computer scientists. Not only can this book be used as a reference source for a scientist who is interested in fuzzy neural networks and their real-time implementations but also as a course book of fuzzy neural networks or artificial intelligence in master or doctorate university studies. We hope that this book will serve its main purpose successfully. Parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis Contains algorithms that are applicable to real time systems Introduces fast and simple adaptation rules for type-1 and type-2 fuzzy neural networks Number of case studies both in identification and control Provides MATLAB® codes for some algorithms in the book

Fuzzy Neural Networks for Real Time Control Applications

Fuzzy Neural Networks for Real Time Control Applications
  • Author : Erdal Kayacan,Mojtaba Ahmadieh Khanesar
  • Publisher :Unknown
  • Release Date :2015-09-17
  • Total pages :264
  • ISBN : 0128026871
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Summary : AN INDISPENSABLE RESOURCE FOR ALL THOSE WHO DESIGN AND IMPLEMENT TYPE-1 AND TYPE-2 FUZZY NEURAL NETWORKS IN REAL TIME SYSTEMS Delve into the type-2 fuzzy logic systems and become engrossed in the parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis with this book! Not only does this book stand apart from others in its focus but also in its application-based presentation style. Prepared in a way that can be easily understood by those who are experienced and inexperienced in this field. Readers can benefit from the computer source codes for both identification and control purposes which are given at the end of the book. A clear and an in-depth examination has been made of all the necessary mathematical foundations, type-1 and type-2 fuzzy neural network structures and their learning algorithms as well as their stability analysis. You will find that each chapter is devoted to a different learning algorithm for the tuning of type-1 and type-2 fuzzy neural networks; some of which are: . Gradient descent . Levenberg-Marquardt . Extended Kalman filter In addition to the aforementioned conventional learning methods above, number of novel sliding mode control theory-based learning algorithms, which are simpler and have closed forms, and their stability analysis have been proposed. Furthermore, hybrid methods consisting of particle swarm optimization and sliding mode control theory-based algorithms have also been introduced. The potential readers of this book are expected to be the undergraduate and graduate students, engineers, mathematicians and computer scientists. Not only can this book be used as a reference source for a scientist who is interested in fuzzy neural networks and their real-time implementations but also as a course book of fuzzy neural networks or artificial intelligence in master or doctorate university studies. We hope that this book will serve its main purpose successfully. Parameter update algorithms for type-1 and type-2 fuzzy neural networks and their stability analysis Contains algorithms that are applicable to real time systems Introduces fast and simple adaptation rules for type-1 and type-2 fuzzy neural networks Number of case studies both in identification and control Provides MATLAB® codes for some algorithms in the book

Neural Fuzzy Control Systems with Structure and Parameter Learning

Neural Fuzzy Control Systems with Structure and Parameter Learning
  • Author : C. T. Lin,Ching Tai Lin
  • Publisher :Unknown
  • Release Date :1994
  • Total pages :127
  • ISBN : 9810216130
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Summary : A general neural-network-based connectionist model, called Fuzzy Neural Network (FNN), is proposed in this book for the realization of a fuzzy logic control and decision system. The FNN is a feedforward multi-layered network which integrates the basic elements and functions of a traditional fuzzy logic controller into a connectionist structure which has distributed learning abilities.In order to set up this proposed FNN, the author recommends two complementary structure/parameter learning algorithms: a two-phase hybrid learning algorithm and an on-line supervised structure/parameter learning algorithm.Both of these learning algorithms require exact supervised training data for learning. In some real-time applications, exact training data may be expensive or even impossible to get. To solve this reinforcement learning problem for real-world applications, a Reinforcement Fuzzy Neural Network (RFNN) is further proposed. Computer simulation examples are presented to illustrate the performance and applicability of the proposed FNN, RFNN and their associated learning algorithms for various applications.

Neural Network Applications in Control

Neural Network Applications in Control
  • Author : Institution of Electrical Engineers
  • Publisher :Unknown
  • Release Date :1995
  • Total pages :295
  • ISBN : 0852968523
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Summary : Introducing a wide variety of network types, including Kohenen nets, n-tuple nets and radial basis function networks as well as the more useful multilayer perception back-propagation networks, this book aims to give a detailed appreciation of the use of neural nets in these applications.

Proceedings of the 4th International Conference on Electrical Engineering and Control Applications

Proceedings of the 4th International Conference on Electrical Engineering and Control Applications
  • Author : Sofiane Bououden
  • Publisher :Unknown
  • Release Date :2020
  • Total pages :1257
  • ISBN : 9789811564031
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Summary :

Fuzzy-neural Control

Fuzzy-neural Control
  • Author : Junhong Nie,D. A. Linkens
  • Publisher :Unknown
  • Release Date :1995
  • Total pages :243
  • ISBN : UOM:39015033961247
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Summary : Shows how Fuzzy Logic and Neural Networks can be intgrated into a Model Reference Control context for real-time control of multivariable systems. It provides a unified architecture which accommodates several popular learning/reasoning paradigms, including Counter Propagation Networks, Radial Basis Functions and CMAC a fuzzy context. Unified treatment of fuzzy-algorithm-based and neural network based control systems. Introduces new fuzzy-nueral controller structures. Demonstrates the feasibility of proposed approach by showing applications. Graduate students of Neural Networks, Intellegent Control and fuzzy matters in depts of Electrical Engineering, Computer Science and Maths.

Design of Interpretable Fuzzy Systems

Design of Interpretable Fuzzy Systems
  • Author : Krzysztof Cpałka
  • Publisher :Unknown
  • Release Date :2017-01-31
  • Total pages :196
  • ISBN : 9783319528816
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Summary : This book shows that the term “interpretability” goes far beyond the concept of readability of a fuzzy set and fuzzy rules. It focuses on novel and precise operators of aggregation, inference, and defuzzification leading to flexible Mamdani-type and logical-type systems that can achieve the required accuracy using a less complex rule base. The individual chapters describe various aspects of interpretability, including appropriate selection of the structure of a fuzzy system, focusing on improving the interpretability of fuzzy systems designed using both gradient-learning and evolutionary algorithms. It also demonstrates how to eliminate various system components, such as inputs, rules and fuzzy sets, whose reduction does not adversely affect system accuracy. It illustrates the performance of the developed algorithms and methods with commonly used benchmarks. The book provides valuable tools for possible applications in many fields including expert systems, automatic control and robotics.

Safety, Reliability, and Applications of Emerging Intelligent Control Technologies

Safety, Reliability, and Applications of Emerging Intelligent Control Technologies
  • Author : International Federation of Automatic Control
  • Publisher :Unknown
  • Release Date :1995
  • Total pages :231
  • ISBN : UOM:39015034437163
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Summary : Paperback. Increasingly, over the last few years, intelligent controllers have been incorporated into control systems. Presently, the numbers and types of intelligent controllers that contain variations of fuzzy logic, neural network, genetic algorithms or some other forms of knowledge based reasoning technology are dramatically rising. However, considering the stability of the system, when such controllers are included it is difficult to analyse and predict system behaviour under unexpected conditions. Leading researchers and industrial practitioners were able to discuss and evaluate current development and future research directions at the first IFAC International Workshop on safety, reliability and applications on emerging intelligent control technology. This publication contains the papers, covering a wide range of topics, presented at the workshop.

New Advances at the Intersection of Brain-Inspired Learning and Deep Learning in Autonomous Vehicles and Robotics

New Advances at the Intersection of Brain-Inspired Learning and Deep Learning in Autonomous Vehicles and Robotics
  • Author : Guang Chen,Pascual Campoy,Changhong Fu,Caixia Cai
  • Publisher :Unknown
  • Release Date :2020-09-02
  • Total pages :229
  • ISBN : 9782889639717
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Summary :

Biologically Inspired Cognitive Architectures 2018

Biologically Inspired Cognitive Architectures 2018
  • Author : Alexei V. Samsonovich
  • Publisher :Unknown
  • Release Date :2018-08-23
  • Total pages :362
  • ISBN : 9783319993164
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Summary : The book focuses on original approaches intended to support the development of biologically inspired cognitive architectures. It bridges together different disciplines, from classical artificial intelligence to linguistics, from neuro- and social sciences to design and creativity, among others. The chapters, based on contributions presented at the Ninth Annual Meeting of the BICA Society, held in on August 23-24, 2018, in Prague, Czech Republic, discuss emerging methods, theories and ideas towards the realization of general-purpose humanlike artificial intelligence or fostering a better understanding of the ways the human mind works. All in all, the book provides engineers, mathematicians, psychologists, computer scientists and other experts with a timely snapshot of recent research and a source of inspiration for future developments in the broadly intended areas of artificial intelligence and biological inspiration.

Fuzzy Neural Intelligent Systems

Fuzzy Neural Intelligent Systems
  • Author : Hongxing Li,C.L. Philip Chen,Han-Pang Huang
  • Publisher :Unknown
  • Release Date :2018-10-03
  • Total pages :392
  • ISBN : 9781351835152
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Summary : Although fuzzy systems and neural networks are central to the field of soft computing, most research work has focused on the development of the theories, algorithms, and designs of systems for specific applications. There has been little theoretical support for fuzzy neural systems, especially their mathematical foundations. Fuzzy Neural Intelligent Systems fills this gap. It develops a mathematical basis for fuzzy neural networks, offers a better way of combining fuzzy logic systems with neural networks, and explores some of their engineering applications. Dividing their focus into three main areas of interest, the authors give a systematic, comprehensive treatment of the relevant concepts and modern practical applications: Fundamental concepts and theories for fuzzy systems and neural networks. Foundation for fuzzy neural networks and important related topics Case examples for neuro-fuzzy systems, fuzzy systems, neural network systems, and fuzzy-neural systems Suitable for self-study, as a reference, and ideal as a textbook, Fuzzy Neural Intelligent Systems is accessible to students with a basic background in linear algebra and engineering mathematics. Mastering the material in this textbook will prepare students to better understand, design, and implement fuzzy neural systems, develop new applications, and further advance the field.

Intelligent Components and Instruments for Control Applications 2003 (SICICA 2003)

Intelligent Components and Instruments for Control Applications 2003 (SICICA 2003)
  • Author : L. Almeida,Luis B. Almeida,S. Boverie
  • Publisher :Unknown
  • Release Date :2003
  • Total pages :293
  • ISBN : 008044010X
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Summary : A Proceedings volume from the IFAC Symposium on Intelligent Components and Instruments for Control Applications, Portugal, 2003. Provides an overview of the theory and applications and presents an exchange of experiences on recent advances in this field.

Application of Artificial Intelligence in Process Control

Application of Artificial Intelligence in Process Control
  • Author : L. Boullart,A. Krijgsman,R. A. Vingerhoeds
  • Publisher :Unknown
  • Release Date :2013-10-22
  • Total pages :544
  • ISBN : 9780080912639
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Summary : 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.

Artificial Intelligence in Real-time Control 1997 (AIRTC'97)

Artificial Intelligence in Real-time Control 1997 (AIRTC'97)
  • Author : Herbert E. Rauch
  • Publisher :Unknown
  • Release Date :1998
  • Total pages :558
  • ISBN : CORNELL:31924084564065
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Summary : Paperback. The Symposium on Artificial Intelligence in Real-Time Control 97 (AIRTC '97) was the seventh in the series of symposia and workshops under the sponsorship of the International Federation of Automatic Control's (IFAC) Co-ordinating Committee in Computer Control and of the Technical Committee on Artificial Intelligence in Real-Time Control.Artificial Intelligence methods, including expert systems, artificial neural networks, fuzzy systems and genetic algorithms, are penetrating almost every field of engineering. These methods have shown their possible application in control, monitoring and supervising tasks which are difficult or impossible to solve when using conventional techniques. We have now come to a stage where there is a need to discuss and present these methods in a broader framework, not only showing their concepts and available algorithms, but also their relative benefits, advantages and disadvantages. This was the purpose of th

Artificial Intelligence in Real-time Control

Artificial Intelligence in Real-time Control
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :1994
  • Total pages :229
  • ISBN : UOM:39015035263915
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Summary :

Applications of Fuzzy Logic Technology

Applications of Fuzzy Logic Technology
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :1993
  • Total pages :229
  • ISBN : UOM:39015032908611
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Summary :

Fuzzy Control Systems

Fuzzy Control Systems
  • Author : Abraham Kandel,Gideon Langholz
  • Publisher :Unknown
  • Release Date :1993-09-27
  • Total pages :656
  • ISBN : 0849344964
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Summary : Fuzzy Control Systems explores one of the most active areas of research involving fuzzy set theory. The contributors address basic issues concerning the analysis, design, and application of fuzzy control systems. Divided into three parts, the book first devotes itself to the general theory of fuzzy control systems. The second part deals with a variety of methodologies and algorithms used in the analysis and design of fuzzy controllers. The various paradigms include fuzzy reasoning models, fuzzy neural networks, fuzzy expert systems, and genetic algorithms. The final part considers current applications of fuzzy control systems. This book should be required reading for researchers, practitioners, and students interested in fuzzy control systems, artificial intelligence, and fuzzy sets and systems.

1996 International Symposium/Workshop on Advanced Technologies

1996 International Symposium/Workshop on Advanced Technologies
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :1996
  • Total pages :260
  • ISBN : 0780333675
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Summary : This is a first conference describing advances in designing and using integrated circuits in control system. The application of neural networks on VLSI is explored. The Use of fuzzy logic in integrated circuit product controllers is explored.

Conference Report

Conference Report
  • Author : Anonim
  • Publisher :Unknown
  • Release Date :1996
  • Total pages :229
  • ISBN : UOM:39015035264566
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Summary :

Artificial Neural Networks for Engineering Applications

Artificial Neural Networks for Engineering Applications
  • Author : Alma Y. Alanis,Nancy Arana-Daniel,Carlos Lopez-Franco
  • Publisher :Unknown
  • Release Date :2019-03-15
  • Total pages :224
  • ISBN : 9780128182475
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Summary : Artificial Neural Networks for Engineering Applications presents current trends for the solution of complex engineering problems that cannot be solved through conventional methods. The proposed methodologies can be applied to modeling, pattern recognition, classification, forecasting, estimation, and more. Readers will find different methodologies to solve various problems, including complex nonlinear systems, cellular computational networks, waste water treatment, attack detection on cyber-physical systems, control of UAVs, biomechanical and biomedical systems, time series forecasting, biofuels, and more. Besides the real-time implementations, the book contains all the theory required to use the proposed methodologies for different applications. Presents the current trends for the solution of complex engineering problems that cannot be solved through conventional methods Includes real-life scenarios where a wide range of artificial neural network architectures can be used to solve the problems encountered in engineering Contains all the theory required to use the proposed methodologies for different applications

Artificial Intelligence in Real-Time Control 1989

Artificial Intelligence in Real-Time Control 1989
  • Author : Hua-Tian Li,Shi-Quan Su,M.G. Rodd
  • Publisher :Unknown
  • Release Date :2014-07-04
  • Total pages :123
  • ISBN : 9781483298337
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Summary : Papers presented at the workshop are representative of the state-of-the art of artificial intelligence in real-time control. The issues covered included the use of AI methods in the design, implementation, testing, maintenance and operation of real-time control systems. While the focus was on the fundamental aspects of the methodologies and technologies, there were some applications papers which helped to put emerging theories into perspective. The four main subjects were architectural issues; knowledge - acquisition and learning; techniques; and scheduling, monitoring and management.