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研究生: 葉信麟
Hsin-lin Yeh
論文名稱: 離散模糊系統非二次穩定性分析
Non-Quadratic Lyapunov Stabilization Discrete-time case
指導教授: 羅吉昌
Ji-chang Lo
口試委員:
學位類別: 碩士
Master
系所名稱: 工學院 - 機械工程學系
Department of Mechanical Engineering
論文出版年: 2013
畢業學年度: 101
語文別: 中文
論文頁數: 59
中文關鍵詞: 參數相依線性矩陣不等式 (PD-LMIs)非二次穩定 (nonquadratic)參數相依齊次多項式 (HPPD)Takagi-Sugeno (T-S) 模糊 控制系統
外文關鍵詞: Parameter-dependent LMIs, Non-quadratic stability, Homogeneous polynomially parameter-dependent (HPPD) functions, T-S fuzzy systems
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  • 本論文主要研究離散 Takagi-Sugeno (T-S) 模糊控制系統的非二次
    (non-quadratic) 寬鬆穩定條件分析,透過波雅定理 (Pólya Theorem)
    的代數性質結合寬鬆矩陣變數 (slack matrix variables) 的激發強度排
    列來建立一組寬鬆的線性矩陣不等式 (LMI),由於非二次穩定的分
    析加上波雅定理 (Pólya Theorem) 以及寬鬆矩陣變數 (slack matrix
    variables); 使得系統求解的保守性大大的降低。
    此外,本文另一貢獻在於寬鬆矩陣變數的架構與以往文獻不同;
    即是將波雅定理結合寬鬆矩陣變數所產生的線性矩陣不等式以多項式
    矩陣型態來表示,透過多項式矩陣型態之特性,同階數的激發強度所
    對應的元素可放在矩陣對角線上或同階數之非對角線上做變化,如此
    一來可使求解的保守度進一步降低。最後舉幾個例子來呈現本文所提
    出的理論之優點。


    In this thesis, we investigate a non-quadratic stabilization problem of discrete-time Takagi- Sugeno (T-S) fuzzy systems by means of homogeneous polynomially parameter-dependent (HPPD) functions, exploiting the algebraic property of Pólya to construct a family of matrixvalued HPPD functions that releases conservatism, assuring existence to non-quadratic Lyapunov functions. The obtained stabilization conditions, characterized by parameter-dependent LMIs (PD-LMIs), are further relaxed by using the proposed right-hand side slackness. A solution technique is proposed through the SOS decomposition of positive semidefinite matrixvalued polynomials. That is, we transform the PD-LMIs based on non-quadratic Lyapunov method into SOS matrix polynomials and then apply matrix RHS relaxation with semi-definite programming searching for a feasible solution to PD-LMIs. Lastly, numerical experiments to illustrate the advantage of RHS relaxation, being less conservative and effective, are provided.

    中文摘要 ........................... i 英文摘要 ........................... ii 謝誌 .............................. iii 目錄 .............................. iv 圖目錄 ............................ vi 表目錄 ............................ vii 一、 背景介紹 ....................... 1 1.1 文獻回顧 ....................... 1 1.2 研究動機 ....................... 2 1.3 論文結構 ....................... 3 1.4 符號標記........................ 3 1.5 預備定理 ...................... 6 二、 系統架構與穩定度條件.............. 7 2.1 控制系統架構 .................... 7 2.2 波雅定理 (Pólya Theorem)........ 8 2.3 離散模糊閉迴路系統之穩定檢測條件 .... 8 2.3.1 使用共同李亞普諾夫函數 (Lyapunov Function) ... 9 2.3.2 使用非共同李亞普諾夫函數 (Lyapunov Function) .. 11 三、 寬鬆穩定條件 ................... 15 3.1 二次穩定結合寬鬆矩陣變數........... 15 3.2 非二次穩定結合寬鬆矩陣變數 ........ 18 3.3 複雜度分析 ..................... 29 四、 電腦模擬 ...................... 31 4.1 例子 1 ........................ 31 4.2 例子 2 ........................ 33 4.3 例子 3 ........................ 39 4.4 例子 4 ........................ 51 五、 結論與未來方向................... 53 5.1 結論 .......................... 53 5.2 未來方向........................ 54 參考文獻............................ 55

    [1] T. Takagi and M. Sugeno. Fuzzy identification of systems and its applications to modelling and control. IEEE Trans. Syst., Man, Cybern., 15(1):116–132, January 1985.
    [2] T. Taniguchi, K. Tanaka, H. Ohatake, and H.O. Wang. Model construction, rule reduction and robust compensation for generalized form of Takagi-Sugeno fuzzy systems. IEEE Trans. Fuzzy Systems,9(4):525–538, August 2001.
    [3] H.W. Wang, J. Li, D. Niemann, and K. Tanaka. T-S fuzzy model with linear rule consequence and PDC controller: a universal framework for nonlinear control systems. In Proc. 9th IEEE Conf. Fuzzy
    Syst., volume 2, pages 549–554, San Antonio, TX., 2000.
    [4] K. Tanaka, T. Taniguchi, and H.O. Wang. Generalized TakagiSugeno fuzzy systems: rule reduction and robust control. In Proc. of 7th IEEE Conf. on Fuzzy Systems, 2000.
    [5] H.O. Wang, K. Tanaka, and M.F. Griffin. An approach to fuzzy control of nonlinear systems: stability and design issues. IEEE Trans. Fuzzy Systems, 4(1):14–23, February 1996.
    [6] K. Tanaka and H.O. Wang. Fuzzy Control Systems Design and Analysis: A Linear Matrix Inequality Approach. John Wiley & Sons, Inc., New York, NY, 2001.
    [7] K. Tanaka, T. Ikeda, and H.O. Wang. Fuzzy regulators and
    fuzzy observers: relaxed stability conditions and LMI-based designs. IEEE Trans. Fuzzy Systems, 6(2):250–265, May 1998.
    [8] J.C. Lo and M.L. Lin. Observer-based robust H∞ control for fuzzy systems using two-step procedure. IEEE Trans. Fuzzy Systems, 12(3):350–359, June 2004
    [9] J.C. Lo and M.L. Lin. Robust H∞ nonlinear control via fuzzy static output feedback. IEEE Trans. Circuits and Syst. I: Fundamental Theory and Applications, 50(11):1494–1502, November 2003.
    [10] T. M. Guerra and L. Vermeiren. LMI-based relaxed nonquadratic stabilization conditions for nonlinear systems in the TakagiSugeno’s form. Automatica, 40:823–829, 2004.
    [11] M. Johansson, A. Rantzer, and K.-E. Arzen. Piecewise quadratic stability of fuzzy systems. IEEE Trans. Fuzzy Systems, 7(6):713–722, December 1999.
    [12] G. Feng. Controller synthesis of fuzzy dynamic systems based on piecewise Lyapunov functions. IEEE Trans. Circuits and Syst. I:Fundamental Theory and Applications, 11(5):605–612, 2003.
    [13] D. Sun G. Feng, C. Chen and Y. Zhu. H∞ controller synthesis of fuzzy dynamic systems based on piecewise Lyapunov functions and bilinear matrix inequalities. IEEE Trans. Circuits and Syst. I:Fundamental Theory and Applications, 13(1):94–103, 2005.
    [14] B.C. Ding, H. Sun, and P Yang. Further studies on LMI-based relaxed stabilization conditions for nonlinear systems in Takagisugeno’s form. Automatica, 43:503–508, 2006.
    [15] X. Chang and G. Yang. FA descriptor representation approach to observer-based H∞ control synthesis for discrete-time fuzzy systems. Fuzzy Set and Systems, 185(1):38–51, 2010.
    [16] B. Ding. Stabilization of Takagi-Sugeno model via nonparallel distributed compensation law. IEEE Trans. Fuzzy Systems, 18(1):188–194, February 2010.
    [17] A. Jaadari J. Pan, S. Fei and T. M. Guerra. Nonquadratic stabilization of continuous T-S fuzzy models: LMI solution for local approach. IEEE Trans. Fuzzy Systems, 20(3):594–602, 2012.
    [18] J. B. Park D. H. Lee and Y. H. Joo. Approaches to extended non-quadratic stability and stabilization conditions for discrete-time Takagi-Sugeno fuzzy systems. Automatica, 47(3):534–538, 2011.
    [19] B. Ding and B. Huang. Reformulation of LMI-based stabilization conditions for non-linear systems in Takagi-Sugeno’s form. Int’l J.of Systems Science, 39(5):487–496, 2008.
    [20] T. M. Guerra and L. Vermeiren. Conditions for non quadratic stabilization of discrete fuzzy models. In 2001 IFAC Conference, 2001.
    [21] D. Peaucelle, D. Arzelier, O. Bachelier, and J. Bernussou. A new robust D-stability condition for real convex polytopic uncertainty. Syst. & Contr. Lett., 40:21–23, 2000.
    [22] J.R. Wan and J.C. Lo. LMI relaxations for nonlinear fuzzy control systems via homogeneous polynomials. In The 2008 IEEE World Congress on Computational Intelligence, FUZZ2008, pages 134–140, Hong Kong, CN, June 2008.
    [23] V.F. Montagner, R.C.L.F Oliveira, and P.L.D. Peres. Necessary and sufficient LMI conditions to compute quadratically stabilizing state feedback controller for Takagi-sugeno systems. In Proc. of the 2007 American Control Conference, pages 4059–4064, July 2007.
    [24] A. Sala and C. Arino. Asymptotically necessary and sufficient conditions for stability and performance in fuzzy control: Applications of Polya’s theorem. Fuzzy Set and Systems, 158:2671–2686, December 2007.
    [25] V.F. Montagner, R.C.L.F Oliveira, and P.L.D. Peres. Convergent LMI relaxations for quadratic stabilization and H∞ control of Takagi-sugeno fuzzy systems. IEEE Trans. Fuzzy Systems, (4):863–873, August 2009.
    [26] R.C.L.F Oliveira and P.L.D. Peres. Parameter-dependent LMIs in robust analysis: characterization of homogeneous polynomially parameter-dependent solutions via LMI relaxations. IEEE Trans. Automatic Control, 52(7):1334–1340, July 2007.
    [27] R.C.L.F Oliveira and P.L.D. Peres. LMI conditions for the existence of polynomially parameter-dependent Lyapunov functions assuring robust stability. In Proc. of 44th IEEE Conf. on Deci and Contr, pages 1660–1665, Seville, Spain, December 2005.
    28] J. C. Geromel M. C. De Oliveira and J.Bernussou. Extend H2 and H∞ norm characteizations and controller parametrizations for discrete time systems. Int. J. Contr., 75(9):666–679, 2002.
    [29] J. Park D. H. Lee and Y. Joo. Improvement on Nonquadratic Stabilization of Discrete-Time Takagi–Sugeno Fuzzy Systems: MultipleParameterization Approach. IEEE Trans. Fuzzy Systems, 18(2):425–429, April 2010.
    [30] B. Ding. Homogeneous Polynomially Nonquadratic Stabilization of Discrete-Time Takagi–Sugeno Systems via Nonparallel Distributed Compensation Law. IEEE Trans. Fuzzy Systems, 18(5):994–1000,October 2010.
    [31] J.C. Lo and C.F. Tsai. LMI relaxations for non-quadratic discrete stabilization via Polya theorem. In Proc. of the 48th IEEE Conference on Decision and Control, pages 7430–7435, Shanghai,CH, December 2009.
    [32] V.F. Montagner, R.C.L.F Oliveira, P.L.D. Peres, and P.-A. Bliman. Linear matrix inequality characterization for H∞ and H2 guaranteed cost gain-scheduling quadratic stabilization of linear timevarying polytopic systems. IET Control Theory & Appl., 1(6):1726–1735, 2007.
    [33] G.H. Hardy, J.E. Littlewood, and G. Pólya. Inequalities, second edition. Cambridge University Press, Cambridge, UK., 1952.
    [34] V. Powers and B. Reznick. A new bound for Pólya’s Theorem with applications to polynomials positive on polyhedra. J. Pure Appl. Algebra, 164:221–229, 2001.
    [35] J. de Loera and F. Santos. An effect version of Pólya’s Theorem on positive definite forms. J. Pure Appl. Algebra, 108:231–240, 1996.
    [36] Y. Zhao D. W. Ding X. Xie, H. Ma and Y. Wang. Control synthesis of discrete-time T-S fuzzy systems based on a novel Non-PDC control scheme. IEEE Trans. Fuzzy Systems, 21(1):147–157, February 2013.
    [37] J.F. Sturm. Using SeDuMi 1.02, a MATLAB toolbox for optimization over symmetric cones. Optimization Methods and Software, 11-12:625–653, 1999.

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