引用本文:唐斌,曾启杰,章云.基于多输入时滞脉冲模型的采样数据控制系统的随机镇定[J].控制理论与应用,2012,29(7):899~908.[点击复制]
TANG Bin,ZENG Qi-jie,ZHANG Yun.Stochastic stabilization of sampled-data control systems based on impulsive model with multiple input delays[J].Control Theory and Technology,2012,29(7):899~908.[点击复制]
基于多输入时滞脉冲模型的采样数据控制系统的随机镇定
Stochastic stabilization of sampled-data control systems based on impulsive model with multiple input delays
摘要点击 2077  全文点击 1574  投稿时间:2011-05-30  修订日期:2011-10-08
查看全文  查看/发表评论  下载PDF阅读器
DOI编号  10.7641/j.issn.1000-8152.2012.7.CCTA110619
  2012,29(7):899-908
中文关键词  采样数据控制系统  多元独立同分布过程  多输入时滞脉冲模型  随机镇定
英文关键词  sampled-data control systems  multiple independent identically distributed process  multiple input delay impulsive model  stochastic stabilization
基金项目  国家自然科学基金资助项目(U0735003, 60974047, 61104105); 广东省自然科学基金博士启动项目资助项目(9451009001002702).
作者单位E-mail
唐斌* 广东工业大学 自动化学院 tangbin316@163.com 
曾启杰 广东工业大学 自动化学院  
章云 广东工业大学 自动化学院  
中文摘要
      针对具有非均匀采样的采样数据控制系统, 把区间内连续分布的采样间隔序列描述为多元独立同分布随机过程, 把闭环系统转化为多输入时滞脉冲模型, 通过构造合适的非连续Lyapunov泛函, 以及合理地利用在所有采样间隔内输入时滞的时间导数等于1的条件, 结合自由权矩阵方法推导了基于LMIs的全局均方渐近稳定性条件, 在此基础上运用调节因子法和锥补线性化方法, 把控制器设计转化为具有LMI约束的非线性优化问题, 并给出了基于LMIs的迭代求解算法. 数值实例和实验表明了所得理论结果的优越性和有效性.
英文摘要
      For a sampled-data control system with nonuniform sampling, the sampling interval sequence, which is distributed in an interval, is described as a multiple independent identically distributed process. The closed-loop system is transformed into an impulsive model with multiple input delays. By creating an appropriate discontinuous Lyapunov functional and rationally exploiting the condition that the derivative of input delay equals 1 in all sampling intervals, we derive a LMIs-based global mean-square asymptotical stability criterion based on free weight matrix approach. By using regulatory factor technique and cone-complementary linearization method, we transform the controller design method to a nonlinear optimization problem with LMI constraints, and an LMI-based iterative solution algorithm is given. Numerical examples and experimental results demonstrate the advantages and effectiveness of our theoretic results.