引用本文:张 艳, 李少远.一类串联控制系统的优化设计:Backstepping方法[J].控制理论与应用,2005,22(3):481~486.[点击复制]
ZHANG Yan, LI Shao-yuan.Optimization design for a class of cascade control systems: Backstepping approach[J].Control Theory and Technology,2005,22(3):481~486.[点击复制]
一类串联控制系统的优化设计:Backstepping方法
Optimization design for a class of cascade control systems: Backstepping approach
摘要点击 1747  全文点击 895  投稿时间:2003-07-01  修订日期:2004-06-11
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DOI编号  10.7641/j.issn.1000-8152.2005.3.028
  2005,22(3):481-486
中文关键词  串联系统  Backstepping方法  次优控制  SDARE(state-dependentalgebraicRiccatiequation)  全局渐近稳定性
英文关键词  cascade system  backstepping method  suboptimal control  state-dependent algebraic Riccati (equation)) (SDARE)  global asymptotical stability
基金项目  国家自然科学基金资助项目(60474051); 国家教育部新世纪优秀人才计划和高等学校博士学科点专项科研基金(20020248028)资助项目.
作者单位
张 艳, 李少远 上海交通大学 自动化研究所,上海 200030 
中文摘要
      针对一类多输入非线性串联系统提出了基于Backstepping方法的次优控制的设计.首先,将串联控制系统分为几个子系统,然后为每个子系统分别设计辅助子系统及相应的辅助控制变量,进一步利用State-DependentAlgebraicRiccatiEquation(SDARE)技术为每个辅助子系统设计次优控制律.设计出的次优控制律使得原状态变量和辅助控制变量(即:辅助反馈变量)具有一定的渐近特性,因此,不但可在线获得次优控制律的解析解,而且保证了原闭环系统的全局渐近稳定性.最后通过一个两输入的二阶串联系统
英文摘要
      A suboptimal control design is proposed based on Backstepping method for a class of multi-input nonlinear cascade systems.First,the cascade control system is decomposed into several subsystems.Then,the auxiliary subsystem and corresponding auxiliary control variables for each actual subsystem are devised,respectively.Third,a suboptimal control law for each auxiliary subsystem is designed with State-Dependent Algebraic Riccati Equation (SDARE) technique.The original state variables and the auxiliary control variables (i.e. auxiliary feedback variables) have an asymptotical characteristic by imposing the proposed control law,thus the analytic solution to suboptimal control can be achieved on-line and the global asymptotical stability (GAS) of the original closed-loop system can be guaranteed.Finally,the numeric simulation results of the second-order system with two inputs are provided to verify the effectiveness of the proposed optimization design.