期刊文献+

不确定非线性系统的二次稳定新方法 被引量:1

A new approach to quadratic stability for uncertain nonlinear systems
原文传递
导出
摘要 针对一类不确定非线性系统,采用模糊技术,提出了一种新的二次稳定控制方案.应用模糊T-S模型和模糊逻辑系统对非线性系统建模,所设计的模糊控制器使得闭环系统二次稳定并满足期望的L_2范数界.该方案的主要优点是不对逼近误差和不确定性做约束假设.仿真结果表明了该方案的可行性. This paper addresses the problem of quadratic stability for a class of uncertain nonlinear systems using fuzzy technique.Fuzzy T-S model and fuzzy logic systems are used to model the nonlinear systems. The fuzzy controller is designed such that the closed-loop system is quadratically stable and satisfies the desired L_2norm bound.The main advantage is that the designer makes no constraint assumption for the approximating error arisen from fuzzy T-S model and the uncertainties in nonlinear systems.Simulation results demonstrate the effectiveness of the developed control scheme.
出处 《系统工程理论与实践》 EI CSSCI CSCD 北大核心 2011年第9期1784-1789,共6页 Systems Engineering-Theory & Practice
基金 国家自然科学基金(60974028 61175086) 山东省自然科学基金(ZR2011FQ037)
关键词 模糊T-S模型 模糊逻辑系统 非线性系统 不确定性 二次稳定 fuzzy T-S model fuzzy logic systems nonlinear systems uncertainties quadratic stability
  • 相关文献

参考文献12

  • 1Rhee B J, Won S. A new fuzzy Lyapunov function approach for a Takagi-Sugeno fuzzy control system design[J].Fuzzy Sets and Systems, 2006, 157(8): 1211 -1228.
  • 2Dong J X, Wang Y Y, Yang G H. Control synthesis of continuous-time T-S fuzzy systems with local nonlinear models[J]. IEEE Transactions on Systems, Man, and Cybernetics - Part B: Cybernetics, 2009, 39(4): 1245 -1258.
  • 3Kim E, Lee H. New approaches to relaxed quadratic stability condition of fuzzy control systems[J]. IEEE Trans- actions on Fuzzy Systems, 2000, 8(4): 523 -533.
  • 4Liu X D, Zhang Q L. New approaches to H∞ controller designs based on fuzzy observers for T-S fuzzy systems via LMI[J]. Automatica, 2003, 39(8): 1571-1582.
  • 5Lo J C, Lin M L. Robust H∞ nonlinear modeling and control via uncertain fuzzy systems[J]. Fuzzy Sets and Systems, 2004, 143(1): 189-209.
  • 6Yang F W, Li Y M. Set-membership fuzzy filtering for nonlinear discrete-time systems[J]. IEEE Transactions on Fuzzy Systems, 2010, 40(1): 116-123.
  • 7Chert B S, Tseng C S, Uang H J. Mixed H2/H∞ fuzzy output feedback control design for nonlinear dynamic systems: An LMI approach[J]. IEEE Transactions on Fuzzy Systems, 2000, 8(2): 249 -265.
  • 8Park C M. LMI-based robust stability analysis for fuzzy feedback linearization regulators with its application[J]. Information Sciences, 2003, 152:287- 301.
  • 9Chiu C S, Chiang T S. Robust output regulation of T-S fuzzy systems with multiple time-varying state and input delays[J]. IEEE Transactions on Fuzzy Systems, 2009, 17(3): 962- 975.
  • 10Liu Y J, Tong S C, Wang W. Adaptive fuzzy output tracking control for a class of uncertain nonlinear systems[J]. Fuzzy Sets and Systems, 2009, 160(16): 2727- 2754.

同被引文献14

  • 1Rudenko O G, Bezsonov A A, Liashenko A S, et al. Approximation of Gaussian basis functions in the problem of adaptive control of nonlinear objects[J]. Cybernetics and Systems Analysis, 2011, 47(1): 1-10.
  • 2Zhao T, Sui S L. Adaptive control for a class of non-aNne nonlinear systems via two-layer neural networks[C]// The Sixth World Congress on Intelligent Control and Automation, 2006, 1: 958-962.
  • 3Boskovic d D, Chen L J, Mehra R K. Multivariable adaptive controller design for a class of non-affine models arising in flight control[C]// Proceedings of the 40th IEEE Conference on Decision and Control, 2001, 3: 2442- 2447.
  • 4Calise A J, Sharma M, Corban J E. Adaptive autopilot design for guided munitions[J]. Journal of Guidance,Control and Dynamics, 2000, 23(5): 837-843.
  • 5Yang B J, Calise A J. Adaptive control of a class of nonaiTine systems using neural networks[J]. IEEE Transactions on Neural Networks, 2007, 18(4): 1149-1159.
  • 6Hovakimyan N, Lavretsky E, Sasane A, et al. Dynamic inversion for nonaffine-in-control systems via time-scale separation: Part I[C]// Proceedings of the 2005 American Control Conference, 2005: 3542-3547.
  • 7Lavretsky E. Hovakimyan N. Adaptive dynamic inversion for nonaffine-in-control systems via time-scale separa- tion: Part II[C]// Proceedings of the 2005 American Control Conference, 2005: 3548-3553.
  • 8Tee K P, Ge S S, Tay F E H. Adaptive neural network control for helicopters in vertical flight[J]. IEEE Trans- actions on Control Systems Technology, 2008, 16(4): 753 -762.
  • 9Imai A K, Costa R R, Hsu L, et al. Multivariable adaptive control using high-frequency gain matrix factoriza- tion[J]. IEEE Transactions on Automatic Control, 2004, 49(7): 1152-1156.
  • 10Ge S S, Tian Z, Lee T H. Nonlinear control of a dynamic model of HIV-I[J]. IEEE Transactions on Biomedical Engineering, 2005, 52(3): 353-361.

引证文献1

二级引证文献1

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