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An Adaptive Control Using Fuzzy Basis Function Expansions for a Class of Nonlinear Systems

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Abstract

An adaptive control using fuzzy basis function expansions is proposed for a class of nonlinear systems in this paper. It is shown that two system uncertainty bounds are approximated in a compact set by using fuzzy basis function expansion networks in the Lyapunov sense, and the outputs of the fuzzy networks are then used as the parameters of the controller to adaptively compensate for the effects of system uncertainties. Using this scheme, not only strong robustness with respect to unknown system dynamics and nonlinearities can be obtained, but also the output tracking error between the plant output and the desired reference output can be guaranteed to asymptotically converge to zero. Simulation results are provided to demonstrate the effectiveness, simplicity and practicality of the proposed control scheme.

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Authors and Affiliations

  1. Department of Electrical Engineering and Computer Science, University of Tasmania, Hobart, 7001, Australia

    Man Zhihong

  2. Department of Mathematics and Computing, Central Queensland University, QLD 4702, Australia

    X. H. Yu

Authors
  1. Man Zhihong
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  2. X. H. Yu
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Zhihong, M., Yu, X.H. An Adaptive Control Using Fuzzy Basis Function Expansions for a Class of Nonlinear Systems. Journal of Intelligent and Robotic Systems 21, 257–275 (1998). https://doi.org/10.1023/A:1007962117548

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  • DOI: https://doi.org/10.1023/A:1007962117548

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