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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.

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.

Adaptive Control of Nonsmooth Dynamic Systems

Adaptive Control of Nonsmooth Dynamic Systems Book
Author : Gang Tao,Frank L. Lewis
Publisher : Springer Science & Business Media
Release : 2013-04-17
ISBN : 144713687X
Language : En, Es, Fr & De

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Book Description :

Many of the non-smooth, non-linear phenomena covered in this well-balanced book are of vital importance in almost any field of engineering. Contributors from all over the world ensure that no one area’s slant on the subjects predominates.

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.

Issues in Robotics and Automation 2013 Edition

Issues in Robotics and Automation  2013 Edition Book
Author : N.A
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/.

Functional Adaptive Control

Functional Adaptive Control Book
Author : Simon Fabri,Visakan Kadirkamanathan
Publisher : Springer Science & Business Media
Release : 2001-02-28
ISBN : 9781852334383
Language : En, Es, Fr & De

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Book Description :

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

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.

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.

Industrial Intelligent Control

Industrial Intelligent Control Book
Author : Yong-Zai Lu
Publisher : John Wiley & Sons
Release : 1996-05-01
ISBN : 9780471950585
Language : En, Es, Fr & De

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Book Description :

With a strong emphasis on applications of intelligent control, this extremely accessible book covers the fundamentals, methodologies, architectures and algorithms of automatic control systems. The author summarizes several current concepts to improve industrial control systems, combining classical control techniques of dynamic modeling and control with new approaches discussed in the text. Addresses such intelligent systems as neural networks, fuzzy logic, ruled based, and genetic algorithms. Demonstrates how to develop, design and use intelligent systems to solve sophisticated industrial control problems. Includes numerous worked application examples.

Knowledge Based Intelligent System Advancements Systemic and Cybernetic Approaches

Knowledge Based Intelligent System Advancements  Systemic and Cybernetic Approaches Book
Author : Jozefczyk, Jerzy,Orski, Donat
Publisher : IGI Global
Release : 2010-08-31
ISBN : 1616928131
Language : En, Es, Fr & De

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Book Description :

Knowledge-Based Intelligent System Advancements: Systemic and Cybernetic Approaches presents selected new AI–based ideas and methods for analysis and decision making in intelligent information systems derived using systemic and cybernetic approaches. This book is useful for researchers, practitioners and students interested intelligent information retrieval and processing, machine learning and adaptation, knowledge discovery, applications of fuzzy based methods and neural networks.

Model Free Adaptive Control

Model Free Adaptive Control Book
Author : Zhongsheng Hou,Shangtai Jin
Publisher : CRC Press
Release : 2013-09-24
ISBN : 1466594195
Language : En, Es, Fr & De

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Book Description :

Model Free Adaptive Control: Theory and Applications summarizes theory and applications of model-free adaptive control (MFAC). MFAC is a novel adaptive control method for the unknown discrete-time nonlinear systems with time-varying parameters and time-varying structure, and the design and analysis of MFAC merely depend on the measured input and output data of the controlled plant, which makes it more applicable for many practical plants. This book covers new concepts, including pseudo partial derivative, pseudo gradient, pseudo Jacobian matrix, and generalized Lipschitz conditions, etc.; dynamic linearization approaches for nonlinear systems, such as compact-form dynamic linearization, partial-form dynamic linearization, and full-form dynamic linearization; a series of control system design methods, including MFAC prototype, model-free adaptive predictive control, model-free adaptive iterative learning control, and the corresponding stability analysis and typical applications in practice. In addition, some other important issues related to MFAC are also discussed. They are the MFAC for complex connected systems, the modularized controller designs between MFAC and other control methods, the robustness of MFAC, and the symmetric similarity for adaptive control system design. The book is written for researchers who are interested in control theory and control engineering, senior undergraduates and graduated students in engineering and applied sciences, as well as professional engineers in process control.

Intelligent Control

Intelligent Control Book
Author : Zi-Xing Cai
Publisher : World Scientific
Release : 1997
ISBN : 9789810225643
Language : En, Es, Fr & De

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Book Description :

Introducton; Methology of knowledge representation; General inference principles; Hierarchical control systems; Expert control systems; Fuzzy control systems; Neurocontrol systems; Learning control systems; Intelligente control systems in application; Prospectives of intelligente control; References; Bibliography; Subject index.

Adaptive Control Design and Analysis

Adaptive Control Design and Analysis Book
Author : Gang Tao
Publisher : John Wiley & Sons
Release : 2003-07-09
ISBN : 9780471274520
Language : En, Es, Fr & De

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Book Description :

Annotation "Today, adaptive control theory has grown to be a rigorous and mature discipline. As the advantages of adaptive systems for developing advanced applications grow apparent, adaptive control is becoming more popular in many fields of engineering and science. Using a simple, balanced, and harmonious style, this book provides a convenient introduction to the subject and improves one's understanding of adaptive control theory." "As either a textbook or reference, this self-contained tutorial of adaptive control design and analysis is ideal for practicing engineers, researchers, and graduate students alike."--BOOK JACKET. Title Summary field provided by Blackwell North America, Inc. All Rights Reserved.

Fast Learning and Adaptation in Control and Machine Learning

Fast Learning and Adaptation in Control and Machine Learning Book
Author : Joseph Emilio Gaudio
Publisher :
Release : 2020
ISBN :
Language : En, Es, Fr & De

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Book Description :

As machine learning methods become more prevalent in society, problems of a dynamical nature will increasingly need to be considered, especially in the interactions of learning-based algorithms with the physical world. The dynamical nature of these problems may include regressors which are time-varying, necessitating new algorithms in machine learning approaches as well as real-time decision making in the presence of uncertainties using adaptive control approaches. Problems of stability, fast learning with analytical guarantees, and constrained nonlinear systems have to be simultaneously addressed. Some of these problems have to be addressed from a machine learning perspective, while others have to be dealt with using adaptive control approaches. Throughout, analytical guarantees must be considered in order to apply machine learning for decision making in real-time, especially for safety-critical systems. This thesis develops fast learning and adaptation algorithms for problems that lie at the intersection of adaptive control and machine learning. From the point of view of adaptive control, this thesis derives algorithms which ensure fast parameter convergence, with minimal overhead in computational complexity. In particular, algorithms with time-varying learning rates are employed to show fast parameter convergence with reduced requirements of persistent excitation, and analysis for time-varying parameters. From the point of view of machine learning, this thesis derives algorithms that are applicable for real-time decision making. In particular, these algorithms ensure fast prediction convergence, which is a necessary feature for satisfactory behavior in real-time systems. Algorithms which take into account natural system constraints, such as input magnitude and rate saturation are also derived order to provide for stability and learning in physically constrained dynamical systems. Throughout the thesis, analytical guarantees for all algorithms are provided.

Principles of Adaptive Filters and Self learning Systems

Principles of Adaptive Filters and Self learning Systems Book
Author : Anthony Zaknich
Publisher : Springer Science & Business Media
Release : 2006-03-30
ISBN : 1846281210
Language : En, Es, Fr & De

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Book Description :

Teaches students about classical and nonclassical adaptive systems within one pair of covers Helps tutors with time-saving course plans, ready-made practical assignments and examination guidance The recently developed "practical sub-space adaptive filter" allows the reader to combine any set of classical and/or non-classical adaptive systems to form a powerful technology for solving complex nonlinear problems

Intelligent Control

Intelligent Control Book
Author : Kaushik Das Sharma,Amitava Chatterjee,Anjan Rakshit
Publisher : Springer
Release : 2018-08-28
ISBN : 9811312982
Language : En, Es, Fr & De

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Book Description :

This book discusses systematic designs of stable adaptive fuzzy logic controllers employing hybridizations of Lyapunov strategy-based approaches/H∞ theory-based approaches and contemporary stochastic optimization techniques. The text demonstrates how candidate stochastic optimization techniques like Particle swarm optimization (PSO), harmony search (HS) algorithms, covariance matrix adaptation (CMA) etc. can be utilized in conjunction with the Lyapunov theory/H∞ theory to develop such hybrid control strategies. The goal of developing a series of such hybridization processes is to combine the strengths of both Lyapunov theory/H∞ theory-based local search methods and stochastic optimization-based global search methods, so as to attain superior control algorithms that can simultaneously achieve desired asymptotic performance and provide improved transient responses. The book also demonstrates how these intelligent adaptive control algorithms can be effectively utilized in real-life applications such as in temperature control for air heater systems with transportation delay, vision-based navigation of mobile robots, intelligent control of robot manipulators etc.

Neural Information Processing

Neural Information Processing Book
Author : Minho Lee,Akira Hirose,Zeng-Guang Hou,Rhee Man Kil
Publisher : Springer
Release : 2013-10-29
ISBN : 3642420540
Language : En, Es, Fr & De

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Book Description :

The three volume set LNCS 8226, LNCS 8227, and LNCS 8228 constitutes the proceedings of the 20th International Conference on Neural Information Processing, ICONIP 2013, held in Daegu, Korea, in November 2013. The 180 full and 75 poster papers presented together with 4 extended abstracts were carefully reviewed and selected from numerous submissions. These papers cover all major topics of theoretical research, empirical study and applications of neural information processing research. The specific topics covered are as follows: cognitive science and artificial intelligence; learning theory, algorithms and architectures; computational neuroscience and brain imaging; vision, speech and signal processing; control, robotics and hardware technologies and novel approaches and applications.

Applied Control Systems Design

Applied Control Systems Design Book
Author : Magdi S. Mahmoud,Yuanqing Xia
Publisher : Springer Science & Business Media
Release : 2012-04-13
ISBN : 1447128796
Language : En, Es, Fr & De

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Book Description :

Applied Control System Design examines several methods for building up systems models based on real experimental data from typical industrial processes and incorporating system identification techniques. The text takes a comparative approach to the models derived in this way judging their suitability for use in different systems and under different operational circumstances. A broad spectrum of control methods including various forms of filtering, feedback and feedforward control is applied to the models and the guidelines derived from the closed-loop responses are then composed into a concrete self-tested recipe to serve as a check-list for industrial engineers or control designers. System identification and control design are given equal weight in model derivation and testing to reflect their equality of importance in the proper design and optimization of high-performance control systems. Readers’ assimilation of the material discussed is assisted by the provision of problems and examples. Most of these exercises use MATLAB® to make computation and visualization more straightforward. Applied Control System Design will be of interest to academic researchers for its comparison of different systems models and their response to different control methods and will assist graduate students in learning the practical necessities of advanced control system design. The consistent reference to real systems coupled with self-learning tools will assist control practitioners who wish to keep up to date with the latest control design ideas.