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

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 wit...

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Bibliographic Details
Published in:IEEE transactions on fuzzy systems 2016-08, Vol.24 (4), p.966-980
Main Authors: Wang, Wei-Yen, Chien, Yi-Hsing, Leu, Yih-Guang, Hsu, Chen-Chien
Format: Article
Language:English
Subjects:
Adaptive control
Fuzzy logic
Fuzzy systems
Mean-based fuzzy control
MIMO
multiple-input multiple-output (MIMO) robotic system
Nonlinear systems
Robots
state estimator
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Summary: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.
ISSN:1063-6706
1941-0034
DOI:10.1109/TFUZZ.2015.2500220