NDLI: A robustness design of uncertain nonlinear dynamic systems via fuzzy linear control

Content Provider	IEEE Xplore Digital Library
Author	Chung-Shi Tseng Bor-Sen Chen Huey-Jian Uang
Copyright Year	1998
Description	Author affiliation: Dept. of Electr. Eng., Nat. Tsing Hua Univ., Hsinchu, Taiwan (Chung-Shi Tseng)
Abstract	This study introduces a fuzzy linear control design method for uncertain nonlinear systems with guaranteed control performance. First, the Takagi and Sugeno's fuzzy linear model is employed to approximate an uncertain nonlinear systems. Next, based on fuzzy linear model, a fuzzy controller is developed to stabilize the fuzzy linear model and at the same time the effect of fuzzy approximation error on control performance is attenuated to a prescribed level. Finally, a robustness performance is achieved in the uncertain nonlinear control system. In the proposed fuzzy linear control method, the fuzzy linear model plays the role of rough control to approximate the nonlinear control system and the H/sup /spl infin// scheme plays the role of precise control to achieve a robustness performance. Linear matrix inequality (LMI) techniques will be employed to treat this robustness fuzzy control problem. If the state variables are unavailable, a fuzzy observer-based H/sup /spl infin// control is also proposed to achieve the robustness design of nonlinear uncertain systems.
Starting Page	428
Ending Page	433
File Size	532582
Page Count	6
File Format	PDF
ISBN	078034863X
ISSN	10987584
DOI	10.1109/FUZZY.1998.687524
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-05-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robustness Fuzzy control Nonlinear control systems Fuzzy systems Robust control Nonlinear systems Control systems Control design Approximation error Linear matrix inequalities
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Theoretical Computer Science Software

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