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    Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/107350


    Title: H∞ fuzzy control synthesis for a large-scale system with a reduced number of LMIs
    Authors: 王文俊;Chang, Wei;Wang, Wen-June
    Contributors: 資訊電機學院電機工程學系
    Keywords: Aerospace electronics;Approximation methods;Control systems;Design engineering;Frequency modulation;Fuzzy control;Fuzzy systems;Large-scale systems;Linear matrix inequalities;Nonlinearity;Reduction;Synthesis;Theorems
    Date: 2015-08-01
    Issue Date: 2026-04-23 14:09:51 (UTC+8)
    Publisher: Institute of Electrical and Electronics Engineers Inc.;IEEE
    Abstract: 摘要: This paper introduces an H ∞ fuzzy control synthesis method for a nonlinear large-scale system with a reduced number of linear matrix inequalities (LMIs). It is well known that a nonlinear large-scale system can be transformed to a Takagi-Sugeno (T-S) fuzzy system by using "sector nonlinearity" or "local approximation in fuzzy partition spaces" methods. Next, in order to achieve the fuzzy control design for this T-S fuzzy system, we solve the stabilization conditions that are represented by the LMIs. However, if the number of LMIs is large, the control design process may become very complicated. In this study, based on the Lyapunov method and S-procedure, several theorems are proposed for the synthesis of parallel distributed compensation (PDC)-type fuzzy control such that the nonlinear large-scale system achieves H ∞ control performance, and the number of LMIs to be solved is reduced explicitly. As a result, the control design process will become much easier. Furthermore, if the modeling error between the nonlinear system and T-S fuzzy system exists, the robust H ∞ control performance and the number reduction of LMIs are also achieved by the proposed theorem. Several examples are presented in this paper to show the number reduction effect of LMIs and the effectiveness of the proposed controller synthesis.
    其他題名: TFUZZ
    出版者: IEEE
    出版日期: 2015-08
    出處: IEEE transactions on fuzzy systems, 2015-08, Vol.23 (4), p.1197-1210
    資源來源: IEEE Electronic Library (IEL)
    識別號: ISSN: 1063-6706
    識別號: EISSN: 1941-0034
    識別號: DOI: 10.1109/TFUZZ.2014.2347995
    識別號: CODEN: IEFSEV
    Appears in Collections:[Department of Electrical Engineering] journal & Dissertation

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