Skip to main content

Learning Based Adaptive Control

Download Learning Based Adaptive Control Full eBooks in PDF, EPUB, and kindle. Learning Based Adaptive Control is one my favorite book and give us some inspiration, very enjoy to read. you could read this book anywhere anytime directly from your device.

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

DOWNLOAD

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

DOWNLOAD

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.

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

DOWNLOAD

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.

Model Free Adaptive Control

Model Free Adaptive Control Book
Author : Zhongsheng Hou,Shangtai Jin
Publisher : CRC Press
Release : 2013-09-24
ISBN : 1466594187
Language : En, Es, Fr & De

DOWNLOAD

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.

Functional Adaptive Control

Functional Adaptive Control Book
Author : Simon G. Fabri,Visakan Kadirkamanathan
Publisher : Springer Science & Business Media
Release : 2012-12-06
ISBN : 144710319X
Language : En, Es, Fr & De

DOWNLOAD

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.

Advances in Aerospace Guidance Navigation and Control

Advances in Aerospace Guidance  Navigation and Control Book
Author : Qiping Chu,Bob Mulder,Daniel Choukroun,Erik-Jan van Kampen,Coen de Visser,Gertjan Looye
Publisher : Springer Science & Business Media
Release : 2013-11-18
ISBN : 3642382533
Language : En, Es, Fr & De

DOWNLOAD

Book Description :

Following the successful 1st CEAS (Council of European Aerospace Societies) Specialist Conference on Guidance, Navigation and Control (CEAS EuroGNC) held in Munich, Germany in 2011, Delft University of Technology happily accepted the invitation of organizing the 2nd CEAS EuroGNC in Delft, The Netherlands in 2013. The goal of the conference is to promote new advances in aerospace GNC theory and technologies for enhancing safety, survivability, efficiency, performance, autonomy and intelligence of aerospace systems using on-board sensing, computing and systems. A great push for new developments in GNC are the ever higher safety and sustainability requirements in aviation. Impressive progress was made in new research fields such as sensor and actuator fault detection and diagnosis, reconfigurable and fault tolerant flight control, online safe flight envelop prediction and protection, online global aerodynamic model identification, online global optimization and flight upset recovery. All of these challenges depend on new online solutions from on-board computing systems. Scientists and engineers in GNC have been developing model based, sensor based as well as knowledge based approaches aiming for highly robust, adaptive, nonlinear, intelligent and autonomous GNC systems. Although the papers presented at the conference and selected in this book could not possibly cover all of the present challenges in the GNC field, many of them have indeed been addressed and a wealth of new ideas, solutions and results were proposed and presented. For the 2nd CEAS Specialist Conference on Guidance, Navigation and Control the International Program Committee conducted a formal review process. Each paper was reviewed in compliance with good journal practice by at least two independent and anonymous reviewers. The papers published in this book were selected from the conference proceedings based on the results and recommendations from the reviewers.

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

DOWNLOAD

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

DOWNLOAD

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.

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

DOWNLOAD

Book Description :

A systematic and unified presentation of the fundamentals of adaptive control theory in both continuous time and discrete time 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. Adaptive Control Design and Analysis features: Introduction to systems and control Stability, operator norms, and signal convergence Adaptive parameter estimation State feedback adaptive control designs Parametrization of state observers for adaptive control Unified continuous and discrete-time adaptive control L1+a robustness theory for adaptive systems Direct and indirect adaptive control designs Benchmark comparison study of adaptive control designs Multivariate adaptive control Nonlinear adaptive control Adaptive compensation of actuator nonlinearities End-of-chapter discussion, problems, and advanced topics 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.

Learning Based Control

Learning Based Control Book
Author : Zhong-Ping Jiang,Tao Bian,Weinan Gao
Publisher : Now Publishers
Release : 2020-12-07
ISBN : 9781680837520
Language : En, Es, Fr & De

DOWNLOAD

Book Description :

The recent success of Reinforcement Learning and related methods can be attributed to several key factors. First, it is driven by reward signals obtained through the interaction with the environment. Second, it is closely related to the human learning behavior. Third, it has a solid mathematical foundation. Nonetheless, conventional Reinforcement Learning theory exhibits some shortcomings particularly in a continuous environment or in considering the stability and robustness of the controlled process. In this monograph, the authors build on Reinforcement Learning to present a learning-based approach for controlling dynamical systems from real-time data and review some major developments in this relatively young field. In doing so the authors develop a framework for learning-based control theory that shows how to learn directly suboptimal controllers from input-output data. There are three main challenges on the development of learning-based control. First, there is a need to generalize existing recursive methods. Second, as a fundamental difference between learning-based control and Reinforcement Learning, stability and robustness are important issues that must be addressed for the safety-critical engineering systems such as self-driving cars. Third, data efficiency of Reinforcement Learning algorithms need be addressed for safety-critical engineering systems. This monograph provides the reader with an accessible primer on a new direction in control theory still in its infancy, namely Learning-Based Control Theory, that is closely tied to the literature of safe Reinforcement Learning and Adaptive Dynamic Programming.

Learning for Adaptive and Reactive Robot Control

Learning for Adaptive and Reactive Robot Control Book
Author : Aude Billard,Sina Mirrazavi,Nadia Figueroa
Publisher : MIT Press
Release : 2022-02-08
ISBN : 0262367017
Language : En, Es, Fr & De

DOWNLOAD

Book Description :

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.

The Cerebellum and Adaptive Control

The Cerebellum and Adaptive Control Book
Author : John S. Barlow
Publisher : Cambridge University Press
Release : 2005-08-22
ISBN : 9780521018074
Language : En, Es, Fr & De

DOWNLOAD

Book Description :

This book reinforces the view that the cerebellum functions as an adaptive control system, automatically adjusting its output as needed for such eventualities as temporary or lasting muscle weakness. It is the first text to synthesize the substantial body of literature on the subject, combining the neuroscience of the cerebellum with the science of control theory common to electrical and computer engineers. An appendix demonstrates evidence to support the adaptive control model from a detailed comparison of the cerebellum with an adaptive signal processor of the author's design and construction. In addition, the author's clinical perspective offers a broader view of cerebellar function beyond basic neuroscience.

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

DOWNLOAD

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.

Discrete Time Adaptive Iterative Learning Control

Discrete Time Adaptive Iterative Learning Control Book
Author : Ronghu Chi,Na Lin,Huimin Zhang,Ruikun Zhang
Publisher : Springer Nature
Release : 2022-03-21
ISBN : 9811904642
Language : En, Es, Fr & De

DOWNLOAD

Book Description :

This book belongs to the subject of control and systems theory. The discrete-time adaptive iterative learning control (DAILC) is discussed as a cutting-edge of ILC and can address random initial states, iteration-varying targets, and other non-repetitive uncertainties in practical applications. This book begins with the design and analysis of model-based DAILC methods by referencing the tools used in the discrete-time adaptive control theory. To overcome the extreme difficulties in modeling a complex system, the data-driven DAILC methods are further discussed by building a linear parametric data mapping between two consecutive iterations. Other significant improvements and extensions of the model-based/data-driven DAILC are also studied to facilitate broader applications. The readers can learn the recent progress on DAILC with consideration of various applications. This book is intended for academic scholars, engineers and graduate students who are interested in learning control, adaptive control, nonlinear systems, and related fields.

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

DOWNLOAD

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/.

Adaptive Control Tutorial

Adaptive Control Tutorial Book
Author : Petros Ioannou,Baris Fidan
Publisher : SIAM
Release : 2006-01-01
ISBN : 0898716152
Language : En, Es, Fr & De

DOWNLOAD

Book Description :

Designed to meet the needs of a wide audience without sacrificing mathematical depth and rigor, Adaptive Control Tutorial presents the design, analysis, and application of a wide variety of algorithms that can be used to manage dynamical systems with unknown parameters. Its tutorial-style presentation of the fundamental techniques and algorithms in adaptive control make it suitable as a textbook. Adaptive Control Tutorial is designed to serve the needs of three distinct groups of readers: engineers and students interested in learning how to design, simulate, and implement parameter estimators and adaptive control schemes without having to fully understand the analytical and technical proofs; graduate students who, in addition to attaining the aforementioned objectives, also want to understand the analysis of simple schemes and get an idea of the steps involved in more complex proofs; and advanced students and researchers who want to study and understand the details of long and technical proofs with an eye toward pursuing research in adaptive control or related topics. The authors achieve these multiple objectives by enriching the book with examples demonstrating the design procedures and basic analysis steps and by detailing their proofs in both an appendix and electronically available supplementary material; online examples are also available. A solution manual for instructors can be obtained by contacting SIAM or the authors. Preface; Acknowledgements; List of Acronyms; Chapter 1: Introduction; Chapter 2: Parametric Models; Chapter 3: Parameter Identification: Continuous Time; Chapter 4: Parameter Identification: Discrete Time; Chapter 5: Continuous-Time Model Reference Adaptive Control; Chapter 6: Continuous-Time Adaptive Pole Placement Control; Chapter 7: Adaptive Control for Discrete-Time Systems; Chapter 8: Adaptive Control of Nonlinear Systems; Appendix; Bibliography; Index

Neural Networks for Control

Neural Networks for Control Book
Author : W. Thomas Miller,Richard S. Sutton,Paul J. Werbos
Publisher : MIT Press
Release : 1995
ISBN : 9780262631617
Language : En, Es, Fr & De

DOWNLOAD

Book Description :

Neural Networks for Control brings together examples of all the most important paradigms for the application of neural networks to robotics and control. Primarily concerned with engineering problems and approaches to their solution through neurocomputing systems, the book is divided into three sections: general principles, motion control, and applications domains (with evaluations of the possible applications by experts in the applications areas.) Special emphasis is placed on designs based on optimization or reinforcement, which will become increasingly important as researchers address more complex engineering challenges or real biological-control problems.A Bradford Book. Neural Network Modeling and Connectionism series

Adaptive and Learning Systems

Adaptive and Learning Systems Book
Author : Kumpati S. Narendra
Publisher : Springer Science & Business Media
Release : 2013-11-22
ISBN : 1475718950
Language : En, Es, Fr & De

DOWNLOAD

Book Description :

This volume offers a glimpse of the status of research in adaptive and learning systems in 1985. In recent years these areas have spawned a multiplicity of ideas so rapidly that the average research worker or practicing engineer is overwhelmed by the flood of information. The Yale Workshop on Applications of Adaptive Systems Theory was organized in 1979 to provide a brief respite from this deluge, wherein critical issues may be examined in a calm and collegial environment. The fourth of the series having been held in May 1985, it has now become well established as a biennial forum for the lively exchange of ideas in the ever changing domain of adaptive systems. The scope of this book is broad and ranges from theoretical investigations to practical applications. It includes twenty eight papers by leaders in the field, selected from the Pro ceedings of the Fourth Yale Workshop and divided into five sections. I have provided a brief introduction to each section so that it can be read as a self-contained unit. The first section, devoted to adaptive control theory, suggests the intensity of activity in the field and reveals signs of convergence towards some common themes by workers with rather different moti vation. Preliminary results concerning the reduced order model problem are dramatically changing the way we view the field and bringing it closer to other areas such as robust linear control where major advances have been recently reported.

Trends in Nonlinear and Adaptive Control

Trends in Nonlinear and Adaptive Control Book
Author : Zhong-Ping Jiang,Christophe Prieur,Alessandro Astolfi
Publisher : Springer Nature
Release : 2021-09-11
ISBN : 3030746283
Language : En, Es, Fr & De

DOWNLOAD

Book Description :

This book, published in honor of Professor Laurent Praly on the occasion of his 65th birthday, explores the responses of some leading international authorities to new challenges in nonlinear and adaptive control. The mitigation of the effects of uncertainty and nonlinearity – ubiquitous features of real-world engineering and natural systems – on closed-loop stability and robustness being of crucial importance, the contributions report the latest research into overcoming these difficulties in: autonomous systems; reset control systems; multiple-input–multiple-output nonlinear systems; input delays; partial differential equations; population games; and data-driven control. Trends in Nonlinear and Adaptive Control presents research inspired by and related to Professor Praly’s lifetime of contributions to control theory and is a valuable addition to the literature of advanced control.