Design of Takagi-Sugeno Fuzzy Region Controller Based on Rule Reduction, Robust Control, and Switching Concept

[+] Author and Article Information
Chein-Chung Sun, Sheng-Ming Wu

Department of Electrical Engineering, National Central University, Chung-li 320, Taiwan, ROC

Hung-Yuan Chung1

Department of Electrical Engineering, National Central University, Chung-li 320, Taiwan, ROChychung@ee.ncu.edu.tw

Wen-Jer Chang

Department of Marine Engineering, National Taiwan Ocean University, Keelung 202, Taiwan, ROC


Corresponding author.

J. Dyn. Sys., Meas., Control 129(2), 163-170 (Aug 02, 2006) (8 pages) doi:10.1115/1.2431811 History: Received February 26, 2004; Revised August 02, 2006

This paper presents a new structure of Takagi-Sugeno (T-S) fuzzy controllers, which is called T-S fuzzy region controller or TSFRC for short. The fuzzy region concept is used to partition the plant rules into several fuzzy regions so that only one region is fired at the instant of each input vector being coming. Because each fuzzy region contains several plant rules, the fuzzy region can be regarded as a polytopic uncertain model. Therefore, robust control techniques would be essential for designing the feedback gains of each fuzzy region. To improve the speed of response, the decay rate constraint is imposed when deriving the stability conditions with Lyapunov stability criterion. To design TSFRC with the linear matrix inequality (LMI) solver, all stability conditions are represented in terms of LMIs. Finally, a two-link robot system is used to prove the feasibility and validity of the proposed method.

Copyright © 2007 by American Society of Mechanical Engineers
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Figure 1

Membership functions of the rule premise

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Figure 2

Example of illustrating fuzzy region

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Figure 3

Membership function of TSFRM in operating point ϕjn

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Figure 4

Two-link robot system

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Figure 5

Membership functions of Mjn

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Figure 6

Definition of membership function for x1 and x3

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Figure 7

State responses (case 2)

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Figure 8

State responses (case 3: horizontal-combination)

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Figure 9

State responses (case 3: vertical-combination)

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Figure 10

State responses (case 4: robust design)




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