Novel direct adaptive fuzzy control system design

Authors:
Yao-Chu Hsueh;Shun-Feng Su
Affiliations:
Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan;Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan
Venue:
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Year:
2009

Citing 9
Cited 0

A course in fuzzy systems and control

A course in fuzzy systems and control
L2-Gain and Passivity Techniques in Nonlinear Control

L2-Gain and Passivity Techniques in Nonlinear Control
Adaptive Approximation Based Control: Unifying Neural, Fuzzy and Traditional Adaptive Approximation Approaches (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)

Adaptive Approximation Based Control: Unifying Neural, Fuzzy and Traditional Adaptive Approximation Approaches (Adaptive and Learning Systems for Signal Processing, Communications and Control Series)
H∞ tracking design of uncertain nonlinear SISO systems: adaptive fuzzy approach

IEEE Transactions on Fuzzy Systems
An improved stable adaptive fuzzy control method

IEEE Transactions on Fuzzy Systems
A fuzzy disturbance observer and its application to control

IEEE Transactions on Fuzzy Systems
Two-Mode Adaptive Fuzzy Control With Approximation Error Estimator

IEEE Transactions on Fuzzy Systems
PI Adaptive Fuzzy Control With Large and Fast Disturbance Rejection for a Class of Uncertain Nonlinear Systems

IEEE Transactions on Fuzzy Systems
Brief Finite gain stabilization of discrete-time linear systems subject to actuator saturation

Automatica (Journal of IFAC)

Quantified Score

Hi-index	0.00

Visualization

Abstract

In our earlier study, the property of L2-gain robust control is incorporated into the direct adaptive fuzzy control design with the use of the compensative controller. The tracking control performance is guaranteed. In the study, we further employ the L2-gain property to improve the adaptive law design. Due to the L2-gain control property, the approximate error of the fuzzy system is estimable, and thus, an adaptive law with the approximate error feedback is proposed in the study. The novel adaptive law improves the learning speed so that the learning performances can be better. Since the L2-gain based compensative controller can guarantee the tracking control performance and remove the effect of the gain function in the adaptive law. The direct adaptive fuzzy control system design of the paper not only has the satisfactory tracking control performance but also has the better learning performance. Various simulations are conducted to demonstrate the effectiveness of the proposed design.