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Fuzzy System Identification and Adaptive Control

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

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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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Authors and Affiliations

  1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing, Jiangsu, China

    Ruiyun Qi & Bin Jiang

  2. School of Engineering and Applied Science, University of Virginia, Charlottesville, VI, USA

    Gang Tao

Authors
  1. Ruiyun Qi
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  2. Gang Tao
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  3. Bin Jiang
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Qi, R., Tao, G., Jiang, B. (2019). Introduction. In: Fuzzy System Identification and Adaptive Control. Communications and Control Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-19882-4_1

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