Mean-Based Fuzzy Control for a Class of MIMO Robotic Systems

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4 Citations (Scopus)

Abstract

This paper presents mean-based fuzzy controllers for trajectory tracking for a class of multiple-input multiple-output robotic systems with nonaffine-like form and parametric uncertainties, in which direct adaptive controllers with state estimators are developed via a mean-based fuzzy identifier without prior knowledge of the membership functions. By using the proposed adaptive technique, unfavorable influence from the initial design of membership functions can be effectively diminished. Moreover, the computation burden of the adaptive laws can be successfully alleviated because the derivative of the fuzzy systems is not required. A Lyapunov-based stability analysis is utilized to guarantee successful system control and desired tracking performance of the closed-loop system. Finally, two examples are provided to demonstrate the feasibility of the proposed control method.

Original languageEnglish
Article number7329994
Pages (from-to)966-980
Number of pages15
JournalIEEE Transactions on Fuzzy Systems
Volume24
Issue number4
DOIs
Publication statusPublished - 2016 Aug 1

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Keywords

  • Mean-based fuzzy control
  • multiple-input multiple-output (MIMO) robotic system
  • state estimator

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computational Theory and Mathematics
  • Artificial Intelligence
  • Applied Mathematics

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