跳到主要內容

臺灣博碩士論文加值系統

(44.210.99.209) 您好!臺灣時間:2024/04/15 14:50
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

我願授權國圖
: 
twitterline
研究生:任中華
研究生(外文):Jung-Hua Ren
論文名稱:H∞模糊控制-連續系統線性分式轉換法
論文名稱(外文):no
指導教授:羅吉昌
指導教授(外文):Ji-Chang Lo
學位類別:碩士
校院名稱:國立中央大學
系所名稱:機械工程研究所
學門:工程學門
學類:機械工程學類
論文種類:學術論文
論文出版年:2003
畢業學年度:91
語文別:中文
論文頁數:85
中文關鍵詞:π轉換線性分式轉換模糊蕭氏轉換線性矩陣不等式
外文關鍵詞:LFTLyapunovDPDCLMIH∞
相關次數:
  • 被引用被引用:0
  • 點閱點閱:161
  • 評分評分:
  • 下載下載:0
  • 收藏至我的研究室書目清單書目收藏:0

本篇論文共分為三大部分來進行討論,其第一部分為數學式子的推導,在這一部分中推導出的矩陣不等式為含有μ(激發強度)的非線性矩陣不等式。另外,本篇論文中的模糊模型與模糊控制器都是線性分式轉換(LFT)架構。第二部分為三次參數化動態平行分佈控制器(DPDC)的討論而第三部分則是二次參數化動態平行分佈控制器的探討。
在第一部分中,我們推導出二條矩陣不等式,第一條是根據李亞普諾夫(Lyapunov)定理而推導出來,第二條則是因為系統的架構而產生。在第二部分中,我們將上一部分所推導出的矩陣不等式提出μ,經由推導得到線性矩陣不等式(LMI)並歸納出一個定理。為了求解上的問題,我們也提出較寬鬆的方法並推導出另一個衍生定理。
第三部分與第二部分大同小異,只是控制器設計上的不。最後我們探討三次參數化動態平行分佈控制器的特殊情,目的是不須經由重覆推導,只須要將之前推導出的通式做一些調整與改變即可得到特殊情況下的線性矩陣不等式。在例子方面,我們採用了三個例子來驗證定理的可行性,分別為旋轉平移制動器、球桿系統與質簧系統。將這三個例子做電腦的模擬與分析,其中第一個例子與第二個例子都分別用三次參數化與二次參數化做動態平行分佈控制,第三個例子則用狀態回授平行分佈控制。


論文摘要.............................Ⅰ
誌謝.................................Ⅱ
圖目.................................Ⅵ
第一章 簡介 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..........................4
第二章 數學模型與H∞性能指標 5
2.1 數學模型..........................5
2.2 H∞性能指標.......................8
2.3 預備定理..........................8
第三章 LFT模糊控制器設計(三次參數化) 9
3.1 通式..............................9
3.2 三次參數化.......................17
3.3 寬鬆方法.........................23
第四章 LFT模糊控制器設計(二次參數化) 28
4.1 二次參數化.......................28
4.2 寬鬆方法.........................33
第五章 特殊情況 36
第六章 電腦模擬 41
6.1 旋轉平移制動器...................41
6.1.1 數學架構推導...................41
6.1.2 求解...........................46
6.2 球桿系統.........................56
6.2.1 數學架構推導...................56
6.2.2 求解...........................58
6.3 質簧系統.........................67
6.3.1 數學架構推導...................67
6.3.2 求解...........................69
第七章 總結與未來研究方向 72
7.1 總結.............................72
7.2 未來研究方向.....................72
參考文獻 74
附錄 77


[1] T. Takagi and M. Sugeno, “Fuzzy ientification of systems and its applications to modeling and control”, IEEE Trans. Syst., Man, Cybern., vol. 15, n. 1, pp.116-132, January 1985.
[2] M. Sugeno and G.T. Kang, “Structure identification of fuzzy model”, Fuzzy
Sets and Systems, vol. 28, pp. 15-33, 1988.
[3] K. Tanaka and M. Sugeno, “Stability analysis and design of fuzzy control
systems”, Fuzzy Sets and Systems, vol. 45, pp. 135-156, 1992.
[4] K. Tanaka and M. Sano, “Trajectory stabilization of a model car via fuzzy
control”, Fuzzy Sets and Systems, vol. 70, pp. 155-170, 1995.
[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 Syst., vol. 4, n. 1, pp. 14-23, February 1996.
[6] K. Tanaka, T. Ikeda and H.O. Wang,“Fuzzy regulators and fuzzy observers:
relaxed stability conditions and LMI-based designs”, IEEE Trans. Fuzzy Syst., vol. 6, n. 2, pp. 250-265, May 1998.
[7] S.G. Cao, N.W. Rees and G. Feng,“Analysis and design of fuzzy control
systems using dynamic fuzzy global model”, Fuzzy Sets and Systems, vol. 75,
pp. 47-62, 1995.
[8] S.H. Zak,“Stabilizing fuzzy system models using linear controllers”, IEEE
Trans. Fuzzy Syst., vol. 7, n. 2, pp. 236-240, April 1999.
[9] I.R. Petersen,“A stabilization algorithm for a class of uncertain linear systems”,Syst. & Contr. Lett., vol. 8, pp. 351-357, 1987.
[10] D.S. Bernstein,“Robust static and dynamic output-feedback stabilization: deterministic and stochastic perspectives”, IEEE Trans. Automat. Contr., vol.
32, n. 12, pp. 1076-1084, December 1987.
[11] D.S. Bernstein,“The optimal projection equations for static and dynamic
output feedback: the singular case”, IEEE Trans. Automat. Contr., vol. 32,
n. 12, pp. 1139-1143, December 1987.
[12] K. Zhou and P.P. Khargonekar,“Robust stabilization of linear systems with
norm-bounded time-varying uncertainty”, Syst. & Contr. Lett., vol. 10, pp.
17-20, 1988.
[13] P.P. Khargonekar, I.R. Petersen and K. Zhou,“Robust stabilization of uncer
tain linear systems: quadratic stabilizability and H∞ control theory”, IEEE
Trans. Automat. Contr., vol. 35, n. 3, pp. 356-361, March 1990.
[14] L. Xie, M. Fu and C.E. de Souza,“H∞ control and quadratic stabilization
of systems with parameter uncertainty via output feedback”, IEEE Trans.
Automat. Contr., vol. 37, n. 8, pp. 1253-1256, August 1992.
[15] J.C. Geromel, J. Bernussou and M.C. de Oliveira,“H2-norm optimizationwith
constrained dynamic output feedback controllers: decentralized and reliable
control”, IEEE Trans. Automat. Contr., vol. 44, n. 7, pp. 1449-1454, July
1999.
[16] H.J. Kang, C. Kwon, Y.H. Yee and M. Park,“L2 robust stability analysis for
the fuzzy feedback linearization regulator”, Proc. of the 6th IEEE Int'l Conf.
on Fuzzy Systems, volume 1, pp. 277-280, 1997.
[17] H.J. Kang, C. Kwon, H. Lee and M. Park,“Robust stability analysis and
design method for the fuzzy feedback linearization regulator”, IEEE
Trans. Fuzzy Syst., vol. 6, n. 4, pp. 464-472, November 1998.
[18] K. Kiriakidis, A. Grivas and A. Tzes,“Quadratic stability analysis of the
Takagi-Sugeno fuzzy model”, Fuzzy Sets and Systems, vol. 98, pp. 1-14,
1998.
[19] M.C.M. Teixeira and S.H. Zak,“Stabilizing controller design for uncertain
nonlinear systems using fuzzy models”, IEEE Trans. Fuzzy Syst., vol. 7, n. 2,
pp. 133-142, April 1999.
[20] S.G. Cao, N.W. Rees and G. Feng,“Quadratic stability analysis and design of continuous fuzzy control systems”, Int'l. Journal on Systems Science, vol. 27,n. 2, pp. 193-203, 1996.
[21] S.G. Cao, N.W. Rees and G. Feng,“Analysis and design of fuzzy control
systems using dynamic fuzzy-state space models”, IEEE Trans. Fuzzy Syst.,
vol. 7, n. 2, pp. 192-200, 1999.
[22] K. Tanaka, T. Ikeda and H.O. Wang,“Robust stabilization of a class of uncertain nonlinear systems via fuzzy control: quadratic stabilizability, H∞ control theory, and linear matrix inequalities”, IEEE Trans. Fuzzy Syst., vol. 4, n. 1,pp. 1-13, February 1996.
[23] K. Tanaka, T. Hori and H.O. Wang,“New robust and optimal designs for
Takagi-Sugeno fuzzy control systems”, Proc. of 1999 IEEE Int'l Conf. on
Control Appl., pp. 415-420, Kohala Coast, Hawaii, 1999.
[24] S.G. Cao, N.W. Rees and G. Feng,“H∞ control of uncertain fuzzy continuous-time systems”, Fuzzy Sets and Systems, vol. 115, pp. 171-190, 2000.
[25] Z. Han and G. Feng,“State feedback H,∞ controller design of fuzzy dynamic
systems using LMI techniques”, Proc. of IEEE World Congress on Compu-
tational Intelligence, volume 1, pp. 538-544, Anchorage, AK., May 1998.
[26] Z. Han, G. Feng and N. Zhang,“Dynamic output feedback H∞ controller
design of fuzzy dynamic systems using LMI techniques”, Proc. of Second
International Conference on Knowledge-Based Intelligent Electronic Systems,
Volume 2, pp. 343-352, Adelaide, AU, 1998.
[27] A. Jadbabaie, M. Jamshidi and A. Titli,“Guaranteed-cost design of continuous-time Takagi-Sugeno fuzzy controller via linear matrix inequalities”,in Proc.of IEEE World Congress on Computational Intell., volume 1, pp. 268-273,Anchorage, AK., May 1998.
[28] S.K. Hong and R. Langari,“Synthesis of an LMI-based fuzzy control system
with guaranteed optimal H∞ performance”, Proc. of IEEE World Congress
on Computational Intell., volume 1, pp. 422-427, Anchorage, AK., May 1998.
[29] B.S. Chen, C.S. Tseng and H.J. Uang,“Mixed H2/H∞ fuzzy output feedback
control design for nonlinear dynamic systems: an LMI approach”, IEEE Trans.
Fuzzy Syst., vol. 8, n. 3, pp. 249-265, June 2000.
[30] K. Zhou, Essentials of Robust Control, Prentice-Hall, Upper Saddle River, NJ.,1998.
[31] K. Tanaka and H.O. Wang, Fuzzy Control Systems Design: A Linear Matrix
Inequality Approach, John Wiley & Sons, Inc., New York, NY, 2001.
[32] H.D. Tuan, P. Apkarian, T. Narikiyo and Y. Yamamoto,“New fuzzy control
model and dynamic output feedback parallel distributed compensation”, IEEE
Trans. Fuzzy Syst., 2002, submitted for publication.
[33] J.C. Lo and J.H. Ren,“H∞ control for LFT fuzzy systems”,in Proc. 2003
Conf. Auto. Contr., volume 1, , TW, March 2003.
[34] K.R. Lee, E.T. Jeung and H.B. Park,“Robust fuzzy H∞ control of uncer-
tain nonlinear systems via state feedback: an LMI approach”, Fuzzy Sets and
Systems, vol. 120, pp. 123-134, 2001.

QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top