Evolutionary Learning Algorithms For Neural Adaptive Control

Author : Dimitris C. Dracopoulos
Publisher : Springer
ISBN 13 : 1447109031
Total Pages : 214 pages
Book Rating : 4.37/5 ( download)

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Download or read book Evolutionary Learning Algorithms for Neural Adaptive Control written by Dimitris C. Dracopoulos and published by Springer. This book was released on 2013-12-21 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: Evolutionary Learning Algorithms for Neural Adaptive Control is an advanced textbook, which investigates how neural networks and genetic algorithms can be applied to difficult adaptive control problems which conventional results are either unable to solve , or for which they can not provide satisfactory results. It focuses on the principles involved, rather than on the modelling of the applications themselves, and therefore provides the reader with a good introduction to the fundamental issues involved.

Author : Dimitris Dracopoulos
Publisher :
ISBN 13 : 9781447109044
Total Pages : 224 pages
Book Rating : 4.4X/5 ( download)

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Download or read book Evolutionary Learning Algorithms for Neural Adaptive Control written by Dimitris Dracopoulos and published by . This book was released on 2014-09-01 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Author : P. Mars
Publisher : CRC Press
ISBN 13 : 1351090879
Total Pages : 231 pages
Book Rating : 4.72/5 ( download)

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Download or read book Learning Algorithms written by P. Mars and published by CRC Press. This book was released on 2018-01-18 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past decade, interest in computational or non-symbolic artificial intelligence has grown. The algorithms involved have the ability to learn from past experience, and therefore have significant potential in the adaptive control of signals and systems. This book focuses on the theory and applications of learning algorithms-stochastic learning automata; artificial neural networks; and genetic algorithms, evolutionary strategies, and evolutionary programming. Hybrid combinations of various algorithms are also discussed.Chapter 1 provides a brief overview of the topics discussed and organization of the text. The first half of the book (Chapters 2 through 4) discusses the basic theory of the learning algorithms, with one chapter devoted to each type. In the second half (Chapters 5 through 7), the emphasis is on a wide range of applications drawn from adaptive signal processing, system identification, and adaptive control problems in telecommunication networks.Learning Algorithms: Theory and Applications in Signal Processing, Control and Communications is an excellent text for final year undergraduate and first year graduate students in engineering, computer science, and related areas. Professional engineers and everyone involved in the application of learning techniques in adaptive signal processing, control, and communications will find this text a valuable synthesis of theory and practical application of the most useful algorithms.

Author : Lakhmi C. Jain
Publisher : CRC Press
ISBN 13 : 9780849398056
Total Pages : 440 pages
Book Rating : 4.53/5 ( download)

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Download or read book Intelligent Adaptive Control written by Lakhmi C. Jain and published by CRC Press. This book was released on 1998-12-29 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book describes important techniques, developments, and applications of computational intelligence in system control. Chapters present: an introduction to the fundamentals of neural networks, fuzzy logic, and evolutionary computing a rigorous treatment of intelligent control industrial applications of intelligent control and soft computing, including transportation, petroleum, motor drive, industrial automation, and fish processing other knowledge-based techniques, including vehicle driving aid and air traffic management Intelligent Adaptive Control provides a state-of-the-art treatment of practical applications of computational intelligence in system control. The book cohesively covers introductory and advanced theory, design, implementation, and industrial use - serving as a singular resource for the theory and application of intelligent control, particularly employing fuzzy logic, neural networks, and evolutionary computing.

Author : Fouad Sabry
Publisher : One Billion Knowledgeable
ISBN 13 :
Total Pages : 164 pages
Book Rating : 4.53/5 ( download)

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Download or read book Intelligent Control written by Fouad Sabry and published by One Billion Knowledgeable. This book was released on 2023-07-03 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: What Is Intelligent Control The term "intelligent control" refers to a category of control methods that make use of a number of different artificial intelligence computing methodologies, including neural networks, Bayesian probability, fuzzy logic, machine learning, reinforcement learning, evolutionary computation, and genetic algorithms. How You Will Benefit (I) Insights, and validations about the following topics: Chapter 1: Intelligent Control Chapter 2: Artificial Intelligence Chapter 3: Machine Learning Chapter 4: Reinforcement Learning Chapter 5: Neural Network Chapter 6: Adaptive Control Chapter 7: Computational Intelligence Chapter 8: Outline of Artificial Intelligence Chapter 9: Machine Learning Control Chapter 10: Data-driven Model (II) Answering the public top questions about intelligent control. (III) Real world examples for the usage of intelligent control in many fields. (IV) 17 appendices to explain, briefly, 266 emerging technologies in each industry to have 360-degree full understanding of intelligent control' technologies. Who This Book Is For Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of intelligent control.

Author : Phil Mars
Publisher : CRC Press
ISBN 13 : 9780849378966
Total Pages : 240 pages
Book Rating : 4.66/5 ( download)

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Download or read book Learning Algorithms written by Phil Mars and published by CRC Press. This book was released on 1996-10-15 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the past decade, interest in computational or non-symbolic artificial intelligence has grown. The algorithms involved have the ability to learn from past experience, and therefore have significant potential in the adaptive control of signals and systems. This book focuses on the theory and applications of learning algorithms-stochastic learning automata; artificial neural networks; and genetic algorithms, evolutionary strategies, and evolutionary programming. Hybrid combinations of various algorithms are also discussed. Chapter 1 provides a brief overview of the topics discussed and organization of the text. The first half of the book (Chapters 2 through 4) discusses the basic theory of the learning algorithms, with one chapter devoted to each type. In the second half (Chapters 5 through 7), the emphasis is on a wide range of applications drawn from adaptive signal processing, system identification, and adaptive control problems in telecommunication networks. Learning Algorithms: Theory and Applications in Signal Processing, Control and Communications is an excellent text for final year undergraduate and first year graduate students in engineering, computer science, and related areas. Professional engineers and everyone involved in the application of learning techniques in adaptive signal processing, control, and communications will find this text a valuable synthesis of theory and practical application of the most useful algorithms.

Author : Gee Wah Ng
Publisher :
ISBN 13 : 9780863802140
Total Pages : 0 pages
Book Rating : 4.41/5 ( download)

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Download or read book Application of Neural Networks to Adaptive Control of Nonlinear Systems written by Gee Wah Ng and published by . This book was released on 1997 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book investigates the ability of a neural network (NN) to learn how to control an unknown (nonlinear, in general) system, using data acquired on-line, that is during the process of attempting to exert control. Two algorithms are developed to train the neural network for real-time control applications. The first algorithm is known as Learning by Recursive Least Squares (LRLS) algorithm and the second algorithm is known as Integrated Gradient and Least Squares (IGLS) algorithm. The ability of these algorithms to train the NN controller for real-time control is demonstrated on practical applications and the local convergence and stability requirements of these algorithms are analysed. In addition, network topology, learning algorithms (particularly supervised learning) and neural network control strategies are presented.

Author : Duc T. Pham
Publisher : Springer Science & Business Media
ISBN 13 : 1447132440
Total Pages : 243 pages
Book Rating : 4.48/5 ( download)

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Download or read book Neural Networks for Identification, Prediction and Control written by Duc T. Pham and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, there has been a growing interest in applying neural networks to dynamic systems identification (modelling), prediction and control. Neural networks are computing systems characterised by the ability to learn from examples rather than having to be programmed in a conventional sense. Their use enables the behaviour of complex systems to be modelled and predicted and accurate control to be achieved through training, without a priori information about the systems' structures or parameters. This book describes examples of applications of neural networks In modelling, prediction and control. The topics covered include identification of general linear and non-linear processes, forecasting of river levels, stock market prices and currency exchange rates, and control of a time-delayed plant and a two-joint robot. These applications employ the major types of neural networks and learning algorithms. The neural network types considered in detail are the muhilayer perceptron (MLP), the Elman and Jordan networks and the Group-Method-of-Data-Handling (GMDH) network. In addition, cerebellar-model-articulation-controller (CMAC) networks and neuromorphic fuzzy logic systems are also presented. The main learning algorithm adopted in the applications is the standard backpropagation (BP) algorithm. Widrow-Hoff learning, dynamic BP and evolutionary learning are also described.

Author : Bernadete Ribeiro
Publisher : Springer Science & Business Media
ISBN 13 : 9783211249345
Total Pages : 568 pages
Book Rating : 4.46/5 ( download)

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Download or read book Adaptive and Natural Computing Algorithms written by Bernadete Ribeiro and published by Springer Science & Business Media. This book was released on 2005-03-08 with total page 568 pages. Available in PDF, EPUB and Kindle. Book excerpt: The papers in this volume present theoretical insights and report practical applications both for neural networks, genetic algorithms and evolutionary computation. In the field of natural computing, swarm optimization, bioinformatics and computational biology contributions are no less compelling. A wide selection of contributions report applications of neural networks to process engineering, robotics and control. Contributions also abound in the field of evolutionary computation particularly in combinatorial and optimization problems. Many papers are dedicated to machine learning and heuristics, hybrid intelligent systems and soft computing applications. Some papers are devoted to quantum computation. In addition, kernel based algorithms, able to solve tasks other than classification, represent a revolution in pattern recognition bridging existing gaps. Further topics are intelligent signal processing and computer vision.

Author : Robert M. French
Publisher : Springer Science & Business Media
ISBN 13 : 1447102819
Total Pages : 327 pages
Book Rating : 4.16/5 ( download)

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Download or read book Connectionist Models of Learning, Development and Evolution written by Robert M. French and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Connectionist Models of Learning, Development and Evolution comprises a selection of papers presented at the Sixth Neural Computation and Psychology Workshop - the only international workshop devoted to connectionist models of psychological phenomena. With a main theme of neural network modelling in the areas of evolution, learning, and development, the papers are organized into six sections: The neural basis of cognition Development and category learning Implicit learning Social cognition Evolution Semantics Covering artificial intelligence, mathematics, psychology, neurobiology, and philosophy, it will be an invaluable reference work for researchers and students working on connectionist modelling in computer science and psychology, or in any area related to cognitive science.