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Introduction

  • Ruiyun Qi
  • Gang Tao
  • Bin Jiang
Chapter
Part of the Communications and Control Engineering book series (CCE)

Abstract

This book presents fuzzy system identification and fuzzy system based adaptive control methodologies that employ fuzzy systems as dynamic approximation models of nonlinear systems. Fuzzy system identification can be carried out using offline input/output (I/O) data collection or in an online mode. Dynamic fuzzy systems are treated as the design models of nonlinear systems, whose structure and parameters serve as a foundation for adaptive control designs. This book aims at providing a systematic and unified framework for identification and adaptive control of fuzzy system, especially Takagi–Sugeno (T–S) fuzzy systems.

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

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

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