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Other titles in the Adaptive and Learning Systems for Signal Processing, Communications and Control series:

Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques (Adaptive and Learning Systems for Signal Processing, Communications and Control)

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Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques (Adaptive and Learning Systems for Signal Processing, Communications and Control) Cover

ISBN13: 9780471415466
ISBN10: 0471415464
Condition:
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Synopses & Reviews

Publisher Comments:

A powerful, yet easy-to-use design methodology for the control of nonlinear dynamic systems

A key issue in the design of control systems is proving that the resulting closed-loop system is stable, especially in cases of high consequence applications, where process variations or failure could result in unacceptable risk. Adaptive control techniques provide a proven methodology for designing stable controllers for systems that may possess a large amount of uncertainty. At the same time, the benefits of neural networks and fuzzy systems are generating much excitement-- and impressive innovations-- in almost every engineering discipline.

Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques brings together these two different but equally useful approaches to the control of nonlinear systems in order to provide students and practitioners with the background necessary to understand and contribute to this emerging field.

The text presents a control methodology that may be verified with mathematical rigor while possessing the flexibility and ease of implementation associated with "intelligent control" approaches. The authors show how these methodologies may be applied to many real-world systems including motor control, aircraft control, industrial automation, and many other challenging nonlinear systems. They provide explicit guidelines to make the design and application of the various techniques a practical and painless process.

Design techniques are presented for nonlinear multi-input multi-output (MIMO) systems in state-feedback, output-feedback, continuous or discrete-time, or even decentralized form. To help students and practitioners new to the field grasp and sustain mastery of the material, the book features:

* Background material on fuzzy systems and neural networks

* Step-by-step controller design

* Numerous examples

* Case studies using "real world" applications

* Homework problems and design projects

Book News Annotation:

Two useful approaches to the control of nonlinear systems are brought together for students and practitioners in need of background information. The text presents a control methodology that may be verified with mathematical rigor while possessing the flexibility associated with intelligent control approaches. Examples demonstrate how the methodology can be applied to real-world systems such as motor control, aircraft control, industrial automation, and other nonlinear systems. Guidelines are provided for design and application of techniques, and design techniques are presented for nonlinear multi- input multi-output systems. Homework problems and design projects are included. Spooner is a senior member of the technical staff at Sandia National Laboratories.
Annotation c. Book News, Inc., Portland, OR (booknews.com)

Synopsis:

Homework problems and design projects

Synopsis:

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.

Synopsis:

  • Includes a solution manual for problems.
  • Provides MATLAB code for examples and solutions.
  • Deals with robust systems in both theory and practice.

About the Author

JEFFREY T. SPOONER is a senior member of the technical staff at Sandia National Laboratories, Albuquerque, New Mexico.

MANFREDI MAGGIORE is an assistant professor in the Department of Electrical and Computer Engineering at the University of Toronto, Canada.

RAUL ORDO?EZ is an assistant professor in the Department of Electrical and Computer Engineering at the University of Dayton, Ohio.

KEVIN M. PASSINO is a professor in the Department of Electrical Engineering at The Ohio State University.

Table of Contents

Introduction.

PART I: FOUNDATIONS.

Mathematical Foundations.

Neural Networks and Fuzzy Systems.

Optimization for Training Approximators.

Function Approximation.

PART II: STATE-FEEDBACK CONTROL.

Control of Nonlinear Systems.

Direct Adaptive Control.

Indirect Adaptive Control.

Implementations and Comparative Studies.

PART III:OUTPUT-FEEDBACK CONTROL.

Output-Feedback Control.

Adaptive Output Feedback Control.

Applications.

PART IV: EXTENSIONS.

Discrete-Time Systems.

Decentralized Systems.

Perspectives on Intelligent Adaptive Systems.

For Further Study.

Bibliography.

Index.

What Our Readers Are Saying

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Average customer rating based on 1 comment:

navidabjadi, September 10, 2006 (view all comments by navidabjadi)
It's a good book specially for control engineers, but it looks more like a collection than a book. In addition, there is some mixed an wrong notations in this book that confuse the reader.
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Product Details

ISBN:
9780471415466
Author:
Spooner, Jeffrey T.
Author:
Passino, Kevin M.
Author:
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Author:
Maggiore, M.
Publisher:
Wiley-Interscience
Subject:
Automation
Subject:
Neural Networks
Subject:
Fuzzy logic
Subject:
Adaptive control systems
Subject:
Artificial Intelligence - General
Subject:
Intelligence (AI) & Semantics
Subject:
System Theory
Subject:
Control Systems; Technology
Subject:
Science Reference-Technology
Copyright:
Edition Description:
WOL online Book (not BRO)
Series:
Adaptive and Learning Systems for Signal Processing, Communications and Control Series
Series Volume:
28
Publication Date:
May 2002
Binding:
HARDCOVER
Grade Level:
Professional and scholarly
Language:
English
Illustrations:
Y
Pages:
568
Dimensions:
9.52x6.38x1.22 in. 2.03 lbs.

Related Subjects

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Computers and Internet » Artificial Intelligence » General
Computers and Internet » Computers Reference » General
Computers and Internet » Networking » General
Reference » Science Reference » General
Reference » Science Reference » Technology
Science and Mathematics » Biology » General
Science and Mathematics » Electricity » General Electronics

Stable Adaptive Control and Estimation for Nonlinear Systems: Neural and Fuzzy Approximator Techniques (Adaptive and Learning Systems for Signal Processing, Communications and Control) New Hardcover
0 stars - 0 reviews
$171.50 In Stock
Product details 568 pages Wiley-Interscience - English 9780471415466 Reviews:
"Synopsis" by , Homework problems and design projects
"Synopsis" by , 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.
"Synopsis" by ,
  • Includes a solution manual for problems.
  • Provides MATLAB code for examples and solutions.
  • Deals with robust systems in both theory and practice.
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