Advertisement

Fuzzy System Identification and Adaptive Control

  • Ruiyun Qi
  • Gang Tao
  • Bin Jiang
Book

Part of the Communications and Control Engineering book series (CCE)

Table of contents

  1. Front Matter
    Pages i-xvii
  2. Ruiyun Qi, Gang Tao, Bin Jiang
    Pages 1-24
  3. Ruiyun Qi, Gang Tao, Bin Jiang
    Pages 25-54
  4. Ruiyun Qi, Gang Tao, Bin Jiang
    Pages 55-74
  5. Ruiyun Qi, Gang Tao, Bin Jiang
    Pages 75-103
  6. Ruiyun Qi, Gang Tao, Bin Jiang
    Pages 105-138
  7. Ruiyun Qi, Gang Tao, Bin Jiang
    Pages 139-162
  8. Ruiyun Qi, Gang Tao, Bin Jiang
    Pages 163-195
  9. Ruiyun Qi, Gang Tao, Bin Jiang
    Pages 197-221
  10. Ruiyun Qi, Gang Tao, Bin Jiang
    Pages 223-246
  11. Ruiyun Qi, Gang Tao, Bin Jiang
    Pages 247-273
  12. Back Matter
    Pages 275-282

About this book

Introduction

This book provides readers with a systematic and unified framework for identification and adaptive control of Takagi–Sugeno (T–S) fuzzy systems. Its design techniques help readers applying these powerful tools to solve challenging nonlinear control problems. The book embodies a systematic study of fuzzy system identification and control problems, using T–S fuzzy system tools for both function approximation and feedback control of nonlinear systems. Alongside this framework, the book also:

  • introduces basic concepts of fuzzy sets, logic and inference system;
  • discusses important properties of T–S fuzzy systems;
  • develops offline and online identification algorithms for T–S fuzzy systems;
  • investigates the various controller structures and corresponding design conditions for adaptive control of continuous-time T–S fuzzy systems;
  • develops adaptive control algorithms for discrete-time input–output form T–S fuzzy systems with much relaxed design conditions, and discrete-time state-space T–S fuzzy systems; and
  • designs stable parameter-adaptation algorithms for both linearly and nonlinearly parameterized T–S fuzzy systems.
The authors address adaptive fault compensation problems for T–S fuzzy systems subject to actuator faults. They cover a broad spectrum of related technical topics and to develop a substantial set of adaptive nonlinear system control tools.

Fuzzy System Identification and Adaptive Control helps engineers in the mechanical, electrical and aerospace fields, to solve complex control design problems. The book can be used as a reference for researchers and academics in nonlinear, intelligent, adaptive and fault-tolerant control.

Keywords

Takagi-Sugeno(T–S) Fuzzy System Adaptive Fuzzy Control Fuzzy Identification Model-based Design MIMO T–S Fuzzy System Dynamic Fuzzy System Input–output T–S Fuzzy System T–S Fuzzy Prediction model Minimum Phase T–S Fuzzy System

Authors and affiliations

  • Ruiyun Qi
    • 1
  • Gang Tao
    • 2
  • Bin Jiang
    • 3
  1. 1.College of Automation EngineeringNanjing University of Aeronautics and AstronauticsNanjingChina
  2. 2.School of Engineering and Applied ScienceUniversity of VirginiaCharlottesvilleUSA
  3. 3.College of Automation EngineeringNanjing University of Aeronautics and AstronauticsNanjingChina

Bibliographic information

Industry Sectors
Materials & Steel
Automotive
Chemical Manufacturing
Electronics
Aerospace
Oil, Gas & Geosciences
Engineering