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Learning Based Adaptive Control

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Learning Based Adaptive Control

Learning Based Adaptive Control Book
Author : Mouhacine Benosman
Publisher : Butterworth-Heinemann
Release : 2016-08-02
ISBN : 0128031514
Language : En, Es, Fr & De

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Book Description :

Adaptive control has been one of the main problems studied in control theory. The subject is well understood, yet it has a very active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control. As systems evolve during time or are exposed to unstructured environments, it is expected that some of their characteristics may change. This book offers a new perspective about how to deal with these variations. By merging together Model-Free and Model-Based learning algorithms, the author demonstrates, using a number of mechatronic examples, how the learning process can be shortened and optimal control performance can be reached and maintained. Includes a good number of Mechatronics Examples of the techniques. Compares and blends Model-free and Model-based learning algorithms. Covers fundamental concepts, state-of-the-art research, necessary tools for modeling, and control.

Learning based Adaptive Control

Learning based Adaptive Control Book
Author : Mouhacine Benosman
Publisher : Butterworth-Heinemann
Release : 2016-07-11
ISBN : 9780128031360
Language : En, Es, Fr & De

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Book Description :

Adaptive control has been one of the main problems studied in control theory. The subject is well understood, yet it has a very active research frontier. This book focuses on a specific subclass of adaptive control, namely, learning-based adaptive control. As systems evolve during time or are exposed to unstructured environments, it is expected that some of their characteristics may change. This book offers a new perspective about how to deal with these variations. By merging together Model-Free and Model-Based learning algorithms, the author demonstrates, using a number of mechatronic examples, how the learning process can be shortened and optimal control performance can be reached and maintained. Includes a good number of Mechatronics Examples of the techniques.Compares and blends Model-free and Model-based learning algorithms.Covers fundamental concepts, state-of-the-art research, necessary tools for modeling, and control.

Neural Network Based Adaptive Control of Uncertain Nonlinear Systems

Neural Network Based Adaptive Control of Uncertain Nonlinear Systems Book
Author : Kasra Esfandiari,Farzaneh Abdollahi,Heidar A. Talebi
Publisher : Springer Nature
Release : 2021-06-18
ISBN : 3030731367
Language : En, Es, Fr & De

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Book Description :

The focus of this book is the application of artificial neural networks in uncertain dynamical systems. It explains how to use neural networks in concert with adaptive techniques for system identification, state estimation, and control problems. The authors begin with a brief historical overview of adaptive control, followed by a review of mathematical preliminaries. In the subsequent chapters, they present several neural network-based control schemes. Each chapter starts with a concise introduction to the problem under study, and a neural network-based control strategy is designed for the simplest case scenario. After these designs are discussed, different practical limitations (i.e., saturation constraints and unavailability of all system states) are gradually added, and other control schemes are developed based on the primary scenario. Through these exercises, the authors present structures that not only provide mathematical tools for navigating control problems, but also supply solutions that are pertinent to real-life systems.

Adaptive Control for Robotic Manipulators

Adaptive Control for Robotic Manipulators Book
Author : Dan Zhang,Bin Wei
Publisher : CRC Press
Release : 2017-02-03
ISBN : 1351678922
Language : En, Es, Fr & De

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Book Description :

The robotic mechanism and its controller make a complete system. As the robotic mechanism is reconfigured, the control system has to be adapted accordingly. The need for the reconfiguration usually arises from the changing functional requirements. This book will focus on the adaptive control of robotic manipulators to address the changed conditions. The aim of the book is to summarise and introduce the state-of-the-art technologies in the field of adaptive control of robotic manipulators in order to improve the methodologies on the adaptive control of robotic manipulators. Advances made in the past decades are described in the book, including adaptive control theories and design, and application of adaptive control to robotic manipulators.

Maintaining the Utility of Learned Knowledge Using Model based Adaptive Control

Maintaining the Utility of Learned Knowledge Using Model based Adaptive Control Book
Author : Lawrence B. Holder,University of Illinois at Urbana-Champaign. Department of Computer Science
Publisher : Unknown
Release : 1991
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Maintaining the Utility of Learned Knowledge Using Model based Adaptive Control book written by Lawrence B. Holder,University of Illinois at Urbana-Champaign. Department of Computer Science, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Control Systems

Control Systems Book
Author : Jitendra R. Raol,Ramakalyan Ayyagari
Publisher : CRC Press
Release : 2019-07-12
ISBN : 1351170783
Language : En, Es, Fr & De

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Book Description :

Control Systems: Classical, Modern, and AI-Based Approaches provides a broad and comprehensive study of the principles, mathematics, and applications for those studying basic control in mechanical, electrical, aerospace, and other engineering disciplines. The text builds a strong mathematical foundation of control theory of linear, nonlinear, optimal, model predictive, robust, digital, and adaptive control systems, and it addresses applications in several emerging areas, such as aircraft, electro-mechanical, and some nonengineering systems: DC motor control, steel beam thickness control, drum boiler, motional control system, chemical reactor, head-disk assembly, pitch control of an aircraft, yaw-damper control, helicopter control, and tidal power control. Decentralized control, game-theoretic control, and control of hybrid systems are discussed. Also, control systems based on artificial neural networks, fuzzy logic, and genetic algorithms, termed as AI-based systems are studied and analyzed with applications such as auto-landing aircraft, industrial process control, active suspension system, fuzzy gain scheduling, PID control, and adaptive neuro control. Numerical coverage with MATLAB® is integrated, and numerous examples and exercises are included for each chapter. Associated MATLAB® code will be made available.

Informatics in Control Automation and Robotics

Informatics in Control  Automation and Robotics Book
Author : Oleg Gusikhin,Kurosh Madani,Janan Zaytoon
Publisher : Springer Nature
Release : 2022-01-01
ISBN : 3030924424
Language : En, Es, Fr & De

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Book Description :

The book focuses the latest endeavours relating researches and developments conducted in fields of Control, Robotics and Automation. Through more than ten revised and extended articles, the present book aims to provide the most up-to-date state-of-art of the aforementioned fields allowing researcher, PhD students and engineers not only updating their knowledge but also benefiting from the source of inspiration that represents the set of selected articles of the book. The deliberate intention of editors to cover as well theoretical facets of those fields as their practical accomplishments and implementations offers the benefit of gathering in a same volume a factual and well-balanced prospect of nowadays research in those topics. A special attention toward “Intelligent Robots and Control” may characterize another benefit of this book.

Machine Vision Inspection Systems Machine Learning Based Approaches

Machine Vision Inspection Systems  Machine Learning Based Approaches Book
Author : Muthukumaran Malarvel,Soumya Ranjan Nayak,Prasant Kumar Pattnaik,Surya Narayan Panda
Publisher : John Wiley & Sons
Release : 2021-01-14
ISBN : 111978610X
Language : En, Es, Fr & De

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Book Description :

Machine Vision Inspection Systems (MVIS) is a multidisciplinary research field that emphasizes image processing, machine vision and, pattern recognition for industrial applications. Inspection techniques are generally used in destructive and non-destructive evaluation industry. Now a day's the current research on machine inspection gained more popularity among various researchers, because the manual assessment of the inspection may fail and turn into false assessment due to a large number of examining while inspection process. This volume 2 covers machine learning-based approaches in MVIS applications and it can be employed to a wide diversity of problems particularly in Non-Destructive testing (NDT), presence/absence detection, defect/fault detection (weld, textile, tiles, wood, etc.), automated vision test & measurement, pattern matching, optical character recognition & verification (OCR/OCV), natural language processing, medical diagnosis, etc. This edited book is designed to address various aspects of recent methodologies, concepts, and research plan out to the readers for giving more depth insights for perusing research on machine vision using machine learning-based approaches.

Issues in Robotics and Automation 2013 Edition

Issues in Robotics and Automation  2013 Edition Book
Author : Anonim
Publisher : ScholarlyEditions
Release : 2013-05-01
ISBN : 1490110720
Language : En, Es, Fr & De

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Book Description :

Issues in Robotics and Automation / 2013 Edition is a ScholarlyEditions™ book that delivers timely, authoritative, and comprehensive information about Computing Information and Control. The editors have built Issues in Robotics and Automation: 2013 Edition on the vast information databases of ScholarlyNews.™ You can expect the information about Computing Information and Control in this book to be deeper than what you can access anywhere else, as well as consistently reliable, authoritative, informed, and relevant. The content of Issues in Robotics and Automation: 2013 Edition has been produced by the world’s leading scientists, engineers, analysts, research institutions, and companies. All of the content is from peer-reviewed sources, and all of it is written, assembled, and edited by the editors at ScholarlyEditions™ and available exclusively from us. You now have a source you can cite with authority, confidence, and credibility. More information is available at http://www.ScholarlyEditions.com/.

Maintaining the Utility of Learned Knowledge Using Model based Adaptive Control

Maintaining the Utility of Learned Knowledge Using Model based Adaptive Control Book
Author : Lawrence B. Holder
Publisher : Unknown
Release : 1991
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

Download Maintaining the Utility of Learned Knowledge Using Model based Adaptive Control book written by Lawrence B. Holder, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Applications of Neural Adaptive Control Technology

Applications of Neural Adaptive Control Technology Book
Author : Jens Kalkkuhl,Rafal Zbikowski
Publisher : World Scientific
Release : 1997
ISBN : 9789810231514
Language : En, Es, Fr & De

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Book Description :

This book presents the results of the second workshop on Neural Adaptive Control Technology, NACT II, held on September 9-10, 1996, in Berlin. The workshop was organised in connection with a three-year European-Union-funded Basic Research Project in the ESPRIT framework, called NACT, a collaboration between Daimler-Benz (Germany) and the University of Glasgow (Scotland).The NACT project, which began on 1 April 1994, is a study of the fundamental properties of neural-network-based adaptive control systems. Where possible, links with traditional adaptive control systems are exploited. A major aim is to develop a systematic engineering procedure for designing neural controllers for nonlinear dynamic systems. The techniques developed are being evaluated on concrete industrial problems from within the Daimler-Benz group of companies.The aim of the workshop was to bring together selected invited specialists in the fields of adaptive control, nonlinear systems and neural networks. The first workshop (NACT I) took place in Glasgow in May 1995 and was mainly devoted to theoretical issues of neural adaptive control. Besides monitoring further development of theory, the NACT II workshop was focused on industrial applications and software tools. This context dictated the focus of the book and guided the editors in the choice of the papers and their subsequent reshaping into substantive book chapters. Thus, with the project having progressed into its applications stage, emphasis is put on the transfer of theory of neural adaptive engineering into industrial practice. The contributors are therefore both renowned academics and practitioners from major industrial users of neurocontrol.

Evolutionary Learning Algorithms for Neural Adaptive Control

Evolutionary Learning Algorithms for Neural Adaptive Control Book
Author : Dimitris C. Dracopoulos
Publisher : Springer
Release : 2013-12-21
ISBN : 1447109031
Language : En, Es, Fr & De

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Book Description :

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.

Deep Reinforcement Learning with Guaranteed Performance

Deep Reinforcement Learning with Guaranteed Performance Book
Author : Yinyan Zhang,Shuai Li,Xuefeng Zhou
Publisher : Springer Nature
Release : 2019-11-09
ISBN : 3030333841
Language : En, Es, Fr & De

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Book Description :

This book discusses methods and algorithms for the near-optimal adaptive control of nonlinear systems, including the corresponding theoretical analysis and simulative examples, and presents two innovative methods for the redundancy resolution of redundant manipulators with consideration of parameter uncertainty and periodic disturbances. It also reports on a series of systematic investigations on a near-optimal adaptive control method based on the Taylor expansion, neural networks, estimator design approaches, and the idea of sliding mode control, focusing on the tracking control problem of nonlinear systems under different scenarios. The book culminates with a presentation of two new redundancy resolution methods; one addresses adaptive kinematic control of redundant manipulators, and the other centers on the effect of periodic input disturbance on redundancy resolution. Each self-contained chapter is clearly written, making the book accessible to graduate students as well as academic and industrial researchers in the fields of adaptive and optimal control, robotics, and dynamic neural networks.

Handbook of Reinforcement Learning and Control

Handbook of Reinforcement Learning and Control Book
Author : Kyriakos G. Vamvoudakis,Yan Wan,Frank L. Lewis,Derya Cansever
Publisher : Springer Nature
Release : 2021
ISBN : 3030609901
Language : En, Es, Fr & De

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Book Description :

This handbook presents state-of-the-art research in reinforcement learning, focusing on its applications in the control and game theory of dynamic systems and future directions for related research and technology. The contributions gathered in this book deal with challenges faced when using learning and adaptation methods to solve academic and industrial problems, such as optimization in dynamic environments with single and multiple agents, convergence and performance analysis, and online implementation. They explore means by which these difficulties can be solved, and cover a wide range of related topics including: deep learning; artificial intelligence; applications of game theory; mixed modality learning; and multi-agent reinforcement learning. Practicing engineers and scholars in the field of machine learning, game theory, and autonomous control will find the Handbook of Reinforcement Learning and Control to be thought-provoking, instructive and informative. .

Reinforcement Learning for Optimal Feedback Control

Reinforcement Learning for Optimal Feedback Control Book
Author : Rushikesh Kamalapurkar,Patrick Walters,Joel Rosenfeld,Warren Dixon
Publisher : Springer
Release : 2018-05-10
ISBN : 331978384X
Language : En, Es, Fr & De

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Book Description :

Reinforcement Learning for Optimal Feedback Control develops model-based and data-driven reinforcement learning methods for solving optimal control problems in nonlinear deterministic dynamical systems. In order to achieve learning under uncertainty, data-driven methods for identifying system models in real-time are also developed. The book illustrates the advantages gained from the use of a model and the use of previous experience in the form of recorded data through simulations and experiments. The book’s focus on deterministic systems allows for an in-depth Lyapunov-based analysis of the performance of the methods described during the learning phase and during execution. To yield an approximate optimal controller, the authors focus on theories and methods that fall under the umbrella of actor–critic methods for machine learning. They concentrate on establishing stability during the learning phase and the execution phase, and adaptive model-based and data-driven reinforcement learning, to assist readers in the learning process, which typically relies on instantaneous input-output measurements. This monograph provides academic researchers with backgrounds in diverse disciplines from aerospace engineering to computer science, who are interested in optimal reinforcement learning functional analysis and functional approximation theory, with a good introduction to the use of model-based methods. The thorough treatment of an advanced treatment to control will also interest practitioners working in the chemical-process and power-supply industry.

AI based Robot Safe Learning and Control

AI based Robot Safe Learning and Control Book
Author : Xuefeng Zhou,Zhihao Xu,Shuai Li,Hongmin Wu,Taobo Cheng,Xiaojing Lv
Publisher : Springer Nature
Release : 2020-06-02
ISBN : 9811555036
Language : En, Es, Fr & De

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Book Description :

This open access book mainly focuses on the safe control of robot manipulators. The control schemes are mainly developed based on dynamic neural network, which is an important theoretical branch of deep reinforcement learning. In order to enhance the safety performance of robot systems, the control strategies include adaptive tracking control for robots with model uncertainties, compliance control in uncertain environments, obstacle avoidance in dynamic workspace. The idea for this book on solving safe control of robot arms was conceived during the industrial applications and the research discussion in the laboratory. Most of the materials in this book are derived from the authors’ papers published in journals, such as IEEE Transactions on Industrial Electronics, neurocomputing, etc. This book can be used as a reference book for researcher and designer of the robotic systems and AI based controllers, and can also be used as a reference book for senior undergraduate and graduate students in colleges and universities.

Intelligent Adaptive Control

Intelligent Adaptive Control Book
Author : Lakhmi C. Jain,Clarence W. de Silva
Publisher : CRC Press
Release : 1998-12-29
ISBN : 9780849398056
Language : En, Es, Fr & De

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Book Description :

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.

Adaptive Control of Ill Defined Systems

Adaptive Control of Ill Defined Systems Book
Author : Oliver G. Selfridge,Edwina L. Rissland,Michael A. Arbib
Publisher : Springer Science & Business Media
Release : 2013-03-09
ISBN : 1468489410
Language : En, Es, Fr & De

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Book Description :

There are some types of complex systems that are built like clockwork, with well-defined parts that interact in well-defined ways, so that the action of the whole can be precisely analyzed and anticipated with accuracy and precision. Some systems are not themselves so well-defined, but they can be modeled in ways that are like trained pilots in well-built planes, or electrolyte balance in healthy humans. But there are many systems for which that is not true; and among them are many whose understanding and control we would value. For example, the model for the trained pilot above fails exactly where the pilot is being most human; that is, where he is exercising the highest levels of judgment, or where he is learning and adapting to new conditions. Again, sometimes the kinds of complexity do not lead to easily analyzable models at all; here we might include most economic systems, in all forms of societies. There are several factors that seem to contribute to systems being hard to model, understand, or control. The human participants may act in ways that are so variable or so rich or so interactive that the only adequate model of the system would be the entire system itself, so to speak. This is probably the case in true long term systems involving people learning and growing up in a changing society.

Cognitive Informatics Computer Modelling and Cognitive Science

Cognitive Informatics  Computer Modelling  and Cognitive Science Book
Author : G. R. Sinha,Jasjit S. Suri
Publisher : Academic Press
Release : 2020-04-07
ISBN : 0128194448
Language : En, Es, Fr & De

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Book Description :

Cognitive Informatics, Computer Modelling, and Cognitive Science: Theory, Case Studies, and Applications presents the theoretical background and history of cognitive science to help readers understand its foundations, philosophical and psychological aspects, and applications in a wide range of engineering and computer science case studies. Cognitive science, a cognitive model of the brain, knowledge representation, and information processing in the human brain are discussed, as is the theory of consciousness, neuroscience, intelligence, decision-making, mind and behavior analysis, and the various ways cognitive computing is used for information manipulation, processing and decision-making. Mathematical and computational models, structures and processes of the human brain are also covered, along with advances in machine learning, artificial intelligence, cognitive knowledge base, deep learning, cognitive image processing and suitable data analytics. Identifies how foundational theories and concepts in cognitive science are applicable in other fields Includes a comprehensive review of cognitive science applications in multiple domains, applying it to neural engineering, robotics, computer science and STEM Includes models of brain processing, consciousness, decision-making, and more Provides in-depth technical coverage of cognitive informatics and computing, including coverage of cognitive knowledge base, information theory, cognitive machine learning and intelligence

Aspects of Soft Computing Intelligent Robotics and Control

Aspects of Soft Computing  Intelligent Robotics and Control Book
Author : János Fodor
Publisher : Springer
Release : 2009-10-13
ISBN : 3642036333
Language : En, Es, Fr & De

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Book Description :

Soft computing, as a collection of techniques exploiting approximation and tolerance for imprecision and uncertainty in traditionally intractable problems, has become very effective and popular especially because of the synergy derived from its components. The integration of constituent technologies provides complementary methods that allow developing flexible computing tools and solving complex problems. A wide area of natural applications of soft computing techniques consists of the control of dynamic systems, including robots. Loosely speaking, control can be understood as driving a process to attain a desired goal. Intelligent control can be seen as an extension of this concept, to include autonomous human-like interactions of a machine with the environment. Intelligent robots can be characterized by the ability to operate in an uncertain, changing environment with the help of appropriate sensing. They have the power to autonomously plan and execute motion sequences to achieve a goal specified by a human user without detailed instructions. In this volume leading specialists address various theoretical and practical aspects in soft computing, intelligent robotics and control. The problems discussed are taken from fuzzy systems, neural networks, interactive evolutionary computation, intelligent mobile robotics, and intelligent control of linear and nonlinear dynamic systems.