Run-time efficient observer-based fuzzy-neural controller for nonaffine multivariable systems with dynamical uncertainties

Yi Hsing Chien, Wei Yen Wang, Chen Chien Hsu

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

In this paper, a novel hierarchical structure with run-time efficiency is developed to solve the rule explosion problem of fuzzy-neural network control for a class of uncertain nonaffine multivariable systems. The parameters of the hybrid adaptive controller are on-line tuned by the derived update laws under the constraint that only system outputs are available for measurement. Compared with the previous approaches, the proposed design process is more flexible and requires less computation time. According to the stability analysis, the overall control scheme guarantees that the closed-loop systems can obtain successful system control, effective state observer, and desired tracking performance. Finally, illustrative examples are provided to show the effectiveness of the proposed approach.

Original languageEnglish
Pages (from-to)1-26
Number of pages26
JournalFuzzy Sets and Systems
Volume302
DOIs
Publication statusPublished - 2016 Nov 1

Keywords

  • Fuzzy-neural controller
  • Nonaffine multivariable systems
  • Run-time efficiency
  • Trajectory-tracking control

ASJC Scopus subject areas

  • Logic
  • Artificial Intelligence

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