期刊文献+

T-S模糊广义系统稳定性的一个新判据 被引量:1

A New Stabilization Conditions for T-S Fuzzy Descriptor System
在线阅读 下载PDF
导出
摘要 以模糊模型为基础的控制技术为非线性系统的研究提供了有效的方法,而对于连续的T-S模糊系统,在对模糊Lyapunov函数求导进而研究系统的稳定性的时候,不可避免的会产生一定的保守性。基于广义系统方法研究了连续T-S广义模糊系统的稳定性问题。通过引入新的变量给出了开环模糊系统的一个宽松稳定条件。然后通过引入新的变量和使用新的松弛技术,得到了一类non-PDC(Parallel Distributed Compensation)控制器的设计方法。该方法具有比现有结果更小的保守性。所得到的定理均通过线性矩阵不等式组表出。数值算例的结果证明了结论的有效性和所得条件具有较低的保守性。 Fuzzy-model-based(FMB)control approach offered a systematic ways to tackle nonlinear systems. At the same time, For continuous - time T-S fuzzy systems, a certain degree of conservativeness remains because information on the time derivative of member- ship functions is generated into the fuzzy Lyapunov function(FLF) time2derivative. In this paper, we investigated the problems of stabili- ty analysis of continuous - time T-S fuzzy descriptor systems based on the descriptor system approach. New criteria for the asymptotic stability of the T-S fuzzy descriptor systems are established. Moreover, with the usage of the non-PDC control scheme, less conservative stabilizations are attained by both introducing additional variables and applying a kind of relaxed technique. Furthermore, all the condi- tions we obtained are expressed in the terms of linear matrix inequalities. And numerical examples are given to illustrate the effectiveness and the less conservatism of the proposed conditions.
出处 《控制工程》 CSCD 北大核心 2013年第4期598-601,606,共5页 Control Engineering of China
基金 国家自然科学基金(61203001) 中央高校基本科研业务费专项资金(N110305010) 吉林省教育厅项目(2013444) 吉林省四平市科技局项目(2012030)
关键词 模糊Lyapunov函数(FLF) 松弛稳定条件 T—S模糊广义系统 线性矩阵不等式组 fuzzy Lyapunov function relaxed stabilization conditions T-S fuzzy descriptor system linear matrix inequalities (LMIs)
  • 相关文献

参考文献18

  • 1G. Feng. A survey on analysis and design of model-based fuzzy con-trol systems [ J ]. IEEE Transactions on Fuzzy Systems, 2006,14(5):676-697.
  • 2袁宇浩,张广明.T-S模糊广义系统研究综述[J].自动化学报,2010,36(7):901-911. 被引量:19
  • 3T. Takagi, M. Sugeno. Fuzzy identification of systems and its appli-cations to modeling and control[ J]. IEEE Transactions on Syst.,Man, Cybem. ,1985,15(2) :116-132.
  • 4K. Tanaka, H. O. Wang. Fuzzy control systems design andan alysis;a linear matrix inequality proach [ J ]. John Wiley and Sons,2001.
  • 5Xiao-Heng Chang, Liang Hong, Yi - Fu Feng. HM Control forContinuous-time T-§ Fuzzy Systems Using Fuzzy Lyapunov Func-tions: A LMI Approach [ C ]. Control and Decision Conference(CCDC),2010( Chinese) :2519-2524.
  • 6E. Kim, H. Lee. New approaches to relaxed quadratic stability con-dition of fuzzy control systems[ J]. IEEE Transactions on Fuzzy Sys-terns,2000,8(5) :523-534.
  • 7C. H. Fang, Y. S. Liu, S. W. Kau, L. Hong. A new LMI-based ap-proach to relaxed quadratic stabilization of T-S fuzzy control sys-tems. IEEE Transactions on Fuzzy Systems,2006 ,14(2) :386-397.
  • 8H. D. Tuan, P. Apkarian, T. Narikiyo, Y. Yamamoto, arameterizedlinear matrix inequality techniques in fuzzy control system design[J]. IEEE Transactions on Fuzzy Systems,2001,9(2) :324-332.
  • 9Leonardo A. Mozelli, Reinaldo M. Palhares, Gustavo S. C. Avellar.A systematic approach to improve multiple Lyapunov function sta-bility and stabilization conditions for fuzzy systems[ J]. InformationSciences,2009,179(8) :1149-1162.
  • 10Miguel Bemal, Antonio Sala, Abdelhafidh Jaadari, Thierry-MarieGuerra. Stability analysis of polynomial fuzzy mdels via polynomialfuzzy Lyapunov functions[ J]. Fuzzy Sets amd Systems,2011,185(15):5-14.

二级参考文献27

共引文献18

同被引文献17

  • 1何勇,吴敏.多时变时滞系统的鲁棒稳定及有界实引理的时滞相关条件[J].控制理论与应用,2004,21(5):735-741. 被引量:12
  • 2Takagi T, Sugeno M. Fuzzy identification of systems and its applications to modeling and control[J]. IEEE Transaction on Systems, 1985, 15(1): 116-132.
  • 3Cao Y Y, Frank P M. Analysis and synthesis of nonlinear time delay systems via thzzy control approach[J]. IEEE Transactions on Fuzzy Systems, 2000, 8(2): 200-211.
  • 4Katayama H, Ichikawa A. H control for discrete time Takagi-Sugeno fuzzy systems[J]. International Journal of Systerms Science, 2002, 33(14): 1099-1107.
  • 5Tian E, Peng C. Delay-dependent stabilization analysis and synthesis of uncertain T-S fuzzy systems with time-varying delay[J]. Fuzzy Sets and Systems, 2006, 157(4): 544-559.
  • 6Jiang X F, Hart Q L. Robust Hcontrol for uncertain Takagi-Sugeno fuzzy systems with interval time-varying Delay[J]. IEEE Transactions on Fuzzy Systems, 2007(a), 15(2): 321-331.
  • 7James L, Gao H J. Stability analysis for continuous systems with two additive time-varying delay components[J]. Systems and Control Letters, 2007, 56(1): 16-24.
  • 8Xiao N, Jia Y M. New approaches on stability criteria for neural networks with two additive time-varying delay components[J]. Neurocomputing, 2013, 118(1): 150-156.
  • 9Idrissi S, El H T. Delay dependent robust stability of T-S fuzzy systems with additive time varying delays[J]. Applied Mathematical Sciences, 2012, 6(1): 1-12.
  • 10Rajeeb D, Ray G, Ghosh S. Stability analysis for continuous system with additive time-varying delays: A less conservative result[J]. Applied Mathematics and Computation, 2010, 265(10): 374 0-3745.

引证文献1

二级引证文献4

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部