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Functional Adaptive Control

Author: Simon G. Fabri

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 275

ISBN-13: 144710319X

Unique in its systematic approach to stochastic systems, this book presents a wide range of techniques that lead to novel strategies for effecting intelligent control of complex systems that are typically characterised by uncertainty, nonlinear dynamics, component failure, unpredictable disturbances, multi-modality and high dimensional spaces.

Intelligent Adaptive Control

Author: Lakhmi C. Jain

Publisher: CRC Press

Published: 1998-12-29

Total Pages: 440

ISBN-13: 9780849398056

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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.

Practical Applications of Computational Intelligence for Adaptive Control

Author: Charles Karr

Publisher: CRC Press

Published: 1999-04-12

Total Pages: 282

ISBN-13: 9780849320699

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Written as a result of a seven year research project using computational intelligence techniques for solving mineral processing problems at the U.S. Bureau of Mines, this book is about intelligent, adaptive process control. It brings together ideas from the field of computational intelligence , a part of the larger field of artificial intelligence, including fuzzy mathematics, genetic algorithms, and neural networks and uses these ideas to develop a generic architecture for accomplishing adaptive process control. In the development of this architecture, the requisite tools are described and then demonstrated on a number of problems. Moreover, most of the examples are of interest in industrial settings (although some simple examples are provided in the beginning so that the reader can focus on technique and not be overburdened with the complexity of the problems being solved.) The focus of Practical Applications of Computational Intelligence for Adaptive Control is on practical applications. It provides practicing engineers and scientists with the information they need to solve process control problems in industry and academia. If the reader is interested in solving difficult control problems or interested in the mechanics of basic computational intelligence techniques, then this book is an excellent place to start.

Stable Adaptive Control and Estimation for Nonlinear Systems

Author: Jeffrey T. Spooner

Publisher: John Wiley & Sons

Published: 2004-04-07

Total Pages: 564

ISBN-13: 0471460974

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Thema dieses Buches ist die Anwendung neuronaler Netze und Fuzzy-Logic-Methoden zur Identifikation und Steuerung nichtlinear-dynamischer Systeme. Dabei werden fortgeschrittene Konzepte der herkömmlichen Steuerungstheorie mit den intuitiven Eigenschaften intelligenter Systeme kombiniert, um praxisrelevante Steuerungsaufgaben zu lösen. Die Autoren bieten viel Hintergrundmaterial; ausgearbeitete Beispiele und Übungsaufgaben helfen Studenten und Praktikern beim Vertiefen des Stoffes. Lösungen zu den Aufgaben sowie MATLAB-Codebeispiele sind ebenfalls enthalten.

Intelligent Systems and Control: Principles and Applications

Author: Laxmidhar Behera

Publisher: OUP India

Published: 2009-12-24

Total Pages: 388

ISBN-13: 9780198063155

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Intelligent Systems and Control: Principles and Applications is a textbook for undergraduate level courses on intelligent control, intelligent systems, adaptive control, and non-linear control. The book covers primers in neural networks, fuzzy logic, and non-linear control so that readers can easily follow intelligent control techniques.

Adaptive Control Systems

Author: Gang Feng

Publisher: Elsevier

Published: 1999-05-10

Total Pages: 361

ISBN-13: 0080498604

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Adaptive control is no longer just an important theoretical field of study, but is also providing solutions to real-world problems. Adaptive techniques will transform the world of control. The leading world practitioners of adaptive control have contributed to this handbook which is the most important work yet in this field. Not only are techniques described in theory, but detailed control algorithms are given, making this a practical cookbook of adaptive control for both control professionals and practising engineers.The book presents the most advanced techniques and algorithms of adaptive control. These include various robust techniques, performance enhancement techniques, techniques with less a-priori knowledge, nonlinear adaptive control techniques and intelligent adaptive techniques. Each technique described has been developed to provide a practical solution to a real-life problem. This volume will therefore not only advance the field of adaptive control as an area of study, but will also show how the potential of this technology can be realised and offer significant benefits. Practical cookbook of adaptive control Contains important research

Learning for Adaptive and Reactive Robot Control

Author: Aude Billard

Publisher: MIT Press

Published: 2022-02-08

Total Pages: 425

ISBN-13: 0262367017

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Methods by which robots can learn control laws that enable real-time reactivity using dynamical systems; with applications and exercises. This book presents a wealth of machine learning techniques to make the control of robots more flexible and safe when interacting with humans. It introduces a set of control laws that enable reactivity using dynamical systems, a widely used method for solving motion-planning problems in robotics. These control approaches can replan in milliseconds to adapt to new environmental constraints and offer safe and compliant control of forces in contact. The techniques offer theoretical advantages, including convergence to a goal, non-penetration of obstacles, and passivity. The coverage of learning begins with low-level control parameters and progresses to higher-level competencies composed of combinations of skills. Learning for Adaptive and Reactive Robot Control is designed for graduate-level courses in robotics, with chapters that proceed from fundamentals to more advanced content. Techniques covered include learning from demonstration, optimization, and reinforcement learning, and using dynamical systems in learning control laws, trajectory planning, and methods for compliant and force control . Features for teaching in each chapter: applications, which range from arm manipulators to whole-body control of humanoid robots; pencil-and-paper and programming exercises; lecture videos, slides, and MATLAB code examples available on the author’s website . an eTextbook platform website offering protected material[EPS2] for instructors including solutions.

Advances In Intelligent Control

Author: C J Harris

Publisher: CRC Press

Published: 1994-03-11

Total Pages: 384

ISBN-13: 9780748400669

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"Advances in intelligent Control" is a collection of essays covering the latest research in the field. Based on a special issue of "The International Journal of Control", the book is arranged in two parts. Part one contains recent contributions of artificial neural networks to modelling and control. Part two concerns itself primarily with aspects of fuzzy logic in intelligent control, guidance and estimation, although some of the contributions either make direct equivalence relationships to neural networks or use hybrid methods where a neural network is used to develop the fuzzy rule base.

Intelligent Optimal Adaptive Control for Mechatronic Systems

Author: Marcin Szuster

Publisher: Springer

Published: 2017-12-28

Total Pages: 382

ISBN-13: 331968826X

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The book deals with intelligent control of mobile robots, presenting the state-of-the-art in the field, and introducing new control algorithms developed and tested by the authors. It also discusses the use of artificial intelligent methods like neural networks and neuraldynamic programming, including globalised dual-heuristic dynamic programming, for controlling wheeled robots and robotic manipulators,and compares them to classical control methods.

System Identification and Adaptive Control

Author: Yiannis Boutalis

Publisher: Springer Science & Business

Published: 2014-04-23

Total Pages: 316

ISBN-13: 3319063642

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Presenting current trends in the development and applications of intelligent systems in engineering, this monograph focuses on recent research results in system identification and control. The recurrent neurofuzzy and the fuzzy cognitive network (FCN) models are presented. Both models are suitable for partially-known or unknown complex time-varying systems. Neurofuzzy Adaptive Control contains rigorous proofs of its statements which result in concrete conclusions for the selection of the design parameters of the algorithms presented. The neurofuzzy model combines concepts from fuzzy systems and recurrent high-order neural networks to produce powerful system approximations that are used for adaptive control. The FCN model stems from fuzzy cognitive maps and uses the notion of “concepts” and their causal relationships to capture the behavior of complex systems. The book shows how, with the benefit of proper training algorithms, these models are potent system emulators suitable for use in engineering systems. All chapters are supported by illustrative simulation experiments, while separate chapters are devoted to the potential industrial applications of each model including projects in: • contemporary power generation; • process control and • conventional benchmarking problems. Researchers and graduate students working in adaptive estimation and intelligent control will find Neurofuzzy Adaptive Control of interest both for the currency of its models and because it demonstrates their relevance for real systems. The monograph also shows industrial engineers how to test intelligent adaptive control easily using proven theoretical results.