Learning Based Adaptive Control

Produk Detail:
  • Author : Mouhacine Benosman
  • Publisher : Butterworth-Heinemann
  • Pages : 282 pages
  • ISBN : 0128031514
  • Rating : /5 from reviews
CLICK HERE TO GET THIS BOOK >>>Learning Based Adaptive Control

Download or Read online Learning Based Adaptive Control full in PDF, ePub and kindle. this book written by Mouhacine Benosman and published by Butterworth-Heinemann which was released on 02 August 2016 with total page 282 pages. We cannot guarantee that Learning Based Adaptive Control book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. 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
  • Author : Mouhacine Benosman
  • Publisher : Butterworth-Heinemann
  • Release : 02 August 2016
GET THIS BOOK Learning Based Adaptive Control

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 based Adaptive Control

Learning based Adaptive Control
  • Author : Mouhacine Benosman
  • Publisher : Butterworth-Heinemann
  • Release : 11 July 2016
GET THIS BOOK Learning based Adaptive Control

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

Neural Network Based Adaptive Control of Uncertain Nonlinear Systems

Neural Network Based Adaptive Control of Uncertain Nonlinear Systems
  • Author : Kasra Esfandiari,Farzaneh Abdollahi,Heidar A. Talebi
  • Publisher : Springer Nature
  • Release : 18 June 2021
GET THIS BOOK Neural Network Based Adaptive Control of Uncertain Nonlinear Systems

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

Adaptive Control for Robotic Manipulators

Adaptive Control for Robotic Manipulators
  • Author : Dan Zhang,Bin Wei
  • Publisher : CRC Press
  • Release : 03 February 2017
GET THIS BOOK Adaptive Control for Robotic Manipulators

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

Control Systems

Control Systems
  • Author : Jitendra R. Raol,Ramakalyan Ayyagari
  • Publisher : CRC Press
  • Release : 12 July 2019
GET THIS BOOK Control Systems

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

Informatics in Control Automation and Robotics

Informatics in Control  Automation and Robotics
  • Author : Oleg Gusikhin,Kurosh Madani,Janan Zaytoon
  • Publisher : Springer Nature
  • Release : 01 January 2022
GET THIS BOOK Informatics in Control Automation and Robotics

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

Machine Vision Inspection Systems Machine Learning Based Approaches

Machine Vision Inspection Systems  Machine Learning Based Approaches
  • Author : Muthukumaran Malarvel,Soumya Ranjan Nayak,Prasant Kumar Pattnaik,Surya Narayan Panda
  • Publisher : John Wiley & Sons
  • Release : 14 January 2021
GET THIS BOOK Machine Vision Inspection Systems Machine Learning Based Approaches

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

Issues in Robotics and Automation 2013 Edition

Issues in Robotics and Automation  2013 Edition
  • Author : Anonim
  • Publisher : ScholarlyEditions
  • Release : 01 May 2013
GET THIS BOOK Issues in Robotics and Automation 2013 Edition

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

Evolutionary Learning Algorithms for Neural Adaptive Control

Evolutionary Learning Algorithms for Neural Adaptive Control
  • Author : Dimitris C. Dracopoulos
  • Publisher : Springer
  • Release : 21 December 2013
GET THIS BOOK Evolutionary Learning Algorithms for Neural Adaptive Control

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.

Applications of Neural Adaptive Control Technology

Applications of Neural Adaptive Control Technology
  • Author : Jens Kalkkuhl,Rafal Zbikowski
  • Publisher : World Scientific
  • Release : 24 January 1997
GET THIS BOOK Applications of Neural Adaptive Control Technology

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

Handbook of Reinforcement Learning and Control

Handbook of Reinforcement Learning and Control
  • Author : Kyriakos G. Vamvoudakis,Yan Wan,Frank L. Lewis,Derya Cansever
  • Publisher : Springer Nature
  • Release : 23 June 2021
GET THIS BOOK Handbook of Reinforcement Learning and Control

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

Deep Reinforcement Learning with Guaranteed Performance

Deep Reinforcement Learning with Guaranteed Performance
  • Author : Yinyan Zhang,Shuai Li,Xuefeng Zhou
  • Publisher : Springer Nature
  • Release : 09 November 2019
GET THIS BOOK Deep Reinforcement Learning with Guaranteed Performance

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

Adaptive and Learning Systems

Adaptive and Learning Systems
  • Author : Kumpati S. Narendra
  • Publisher : Springer Science & Business Media
  • Release : 22 November 2013
GET THIS BOOK Adaptive and Learning Systems

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