NDLI: Guaranteed cost control for uncertain fuzzy systems with time-delay

Content Provider	IEEE Xplore Digital Library
Author	He Shuaitian Du Chunyan
Copyright Year	2009
Description	Author affiliation: Department of Foundation, the First Aeronautical College of Air Force, Henan Xinyang, 464000, China (He Shuaitian; Du Chunyan)
Abstract	A guaranteed cost control method for nonlinear systems with time-delay is introduced in this paper, which can be represented by Takagi-Sugeno (T-S) fuzzy models with time-delays. The state feedback approach is considered. By introducing a new Lyapunov-Krasovskii functional with adjustable parameters, and based on delay-dependent stability analysis, some sufficient conditions for the existence of state feedback controller via parallel distributed compensation (PDC) are given in the form of linear matrix inequalities (LMIs). The different guaranteed cost and different feedback gains are gotten by choosing different adjustable parameters. Different feedback gains lead to different dynamic performance of closed-loop systems, therefore, the optimal dynamic performance of closed-loop systems can be gotten by choosing proper adjustable parameters. The guaranteed cost can be regarded as the function of adjustable parameters, and an algorithm is given to get the minimum of the guaranteed cost. The effectiveness of the proposed method can be illustrated by the simulation example.
Starting Page	4100
Ending Page	4105
File Size	152204
Page Count	6
File Format	PDF
ISBN	9781424427222
DOI	10.1109/CCDC.2009.5192443
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-06-17
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	State feedback guaranteed cost control T-S fuzzy model Nonlinear control systems Control systems Stability analysis Delay linear matrix inequality Time-delay systems Fuzzy control Cost function Takagi-Sugeno model Nonlinear systems Fuzzy systems
Content Type	Text
Resource Type	Article

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