Robust Adaptive Controller Design for a Class of Uncertain Nonlinear Systems Using Online T–S Fuzzy-Neural Modeling Approach
學年 99
學期 2
出版（發表）日期 2011-04-01
作品名稱 Robust Adaptive Controller Design for a Class of Uncertain Nonlinear Systems Using Online T–S Fuzzy-Neural Modeling Approach
作品名稱（其他語言）
著者 Chien, Yi-Hsing; Wang, Wei-Yen; Leu, Yih-Guang; Lee, Tsu-Tian
單位 淡江大學電機工程學系
出版者 Piscataway: Institute of Electrical and Electronics Engineers
著錄名稱、卷期、頁數 IEEE Transactions on Systems, Man, and Cybernetics, Part B 41(2), pp.542-552
摘要 This paper proposes a novel method of online modeling and control via the Takagi-Sugeno (T-S) fuzzy-neural model for a class of uncertain nonlinear systems with some kinds of outputs. Although studies about adaptive T-S fuzzy-neural controllers have been made on some nonaffine nonlinear systems, little is known about the more complicated uncertain nonlinear systems. Because the nonlinear functions of the systems are uncertain, traditional T-S fuzzy control methods can model and control them only with great difficulty, if at all. Instead of modeling these uncertain functions directly, we propose that a T-S fuzzy-neural model approximates a so-called virtual linearized system (VLS) of the system, which includes modeling errors and external disturbances. We also propose an online identification algorithm for the VLS and put significant emphasis on robust tracking controller design using an adaptive scheme for the uncertain systems. Moreover, the stability of the closed-loop systems is proven by using strictly positive real Lyapunov theory. The proposed overall scheme guarantees that the outputs of the closed-loop systems asymptotically track the desired output trajectories. To illustrate the effectiveness and applicability of the proposed method, simulation results are given in this paper.
關鍵字 Fuzzy-neural model; online modeling; robust adaptive control; uncertain nonlinear systems
語言 en
ISSN 1083-4419
期刊性質
收錄於 SCI
產學合作
通訊作者
審稿制度
國別 USA
公開徵稿
出版型式 紙本
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