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Fuzzy Modeling of Non-Uniformly Sampling Nonlinear Systems Based on Clustering Method and Convergence Analysis

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Abstract

The studying motivation of this paper is that there exist many modeling issues of non-uniformly sampling nonlinear systems in industrial systems. Based on multi-model modeling principle, the corresponding model of non-uniformly sampling nonlinear systems is described by the nonlinear weighted combination of some linear models at local working points. Fuzzy modeling based on multimodel scheme is a common method to describe the dynamic process of non-linear systems. In this paper, the fuzzy modeling method of non-uniformly sampling nonlinear systems is studied. The premise structure of the fuzzy model is confirmed by GK fuzzy clustering, and the conclusion parameters of the fuzzy model are estimated by the recursive least squared algorithm. The convergence perfromance of the proposed identification algorithm is given by using lemmas and martingale theorem. Finally, the simulation example is given to demonstrate the effectiveness of the proposed method.

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Author information

Authors and Affiliations

  1. School of Electrical Engineering, Xinjiang University, Urumqi, 830047, China

    Hongwei Wang & Lirong Xie

  2. School of Control Science and Control Engineering, Dalian University of Technology, Dalian, 116024, China

    Hongwei Wang

Authors
  1. Hongwei Wang
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  2. Lirong Xie
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Corresponding author

Correspondence to Hongwei Wang.

Additional information

The research was supported by the National Natural Science Foundation of China under Grant Nos. 61863034 and 51667021.

This paper was recommended for publication by Editor FENG Gang.

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Wang, H., Xie, L. Fuzzy Modeling of Non-Uniformly Sampling Nonlinear Systems Based on Clustering Method and Convergence Analysis. J Syst Sci Complex 34, 502–519 (2021). https://doi.org/10.1007/s11424-020-9119-7

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  • DOI: https://doi.org/10.1007/s11424-020-9119-7

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