引用本文:卢洁莹,李俊辉,苏为洲.有损信道下网络化系统的均方最优渐近跟踪[J].控制理论与应用,2021,38(11):1761~1771.[点击复制]
LU Jie-ying,LI Jun-hui,SU Wei-zhou.Mean-square optimal asymptotic tracking for networked systems over lossy channels[J].Control Theory and Technology,2021,38(11):1761~1771.[点击复制]
有损信道下网络化系统的均方最优渐近跟踪
Mean-square optimal asymptotic tracking for networked systems over lossy channels
摘要点击 1396  全文点击 400  投稿时间：2021-08-09  修订日期：2021-09-10
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DOI编号  10.7641/CTA.2021.10730
  2021,38(11):1761-1771
中文关键词  网络化控制  丢包  乘性噪声  渐近跟踪  均方最优控制
英文关键词  networked control  packet loss  multiplicative noise  asymptotic tracking  mean-square optimal control
基金项目  国家自然科学基金项目(61933006, 61673183)资助.
作者单位E-mail
卢洁莹 华南理工大学 aujylu@scut.edu.cn 
李俊辉 华南理工大学  
苏为洲* 华南理工大学 wzhsu@scut.edu.cn 
中文摘要
      对于通讯信道具有丢包的网络化反馈控制系统, 运用乘性噪声模型来描述丢包这一信道不确定性, 并根据 网络化系统的结构特点提出了一种渐近跟踪控制器结构, 研究了该结构下系统的均方可镇定性以及均方最优渐近 跟踪与均方可镇定性的等价关系. 在此基础上, 运用随机均方最优控制理论给出了该系统均方最优渐近跟踪设计方 法, 该方法取决于广义代数黎卡提方程(MARE)的均方镇定解. 进一步, 本文提出了求解上述均方镇定解的新算法. 最后的仿真验证了对于信道具有丢包的网络化反馈系统最优渐近跟踪问题, 本文所提方法的有效性和可行性.
英文摘要
      For a networked feedback control system with packet loss in the communication channel, the multiplicative noise model is used to describe the channel uncertainty induced by packet loss. According to features of the networked system, a new controller structure is proposed for the asymptotic tracking problem of the networked system. The meansquare stabilizability of the system under this structure is studied. And then the equivalence between the optimal asymptotic tracking and the mean-square stabilizability is studied. On this basis, the stochastic mean-square optimal control theory is used to solve the mean-square optimal asymptotic tracking design for the system, which depends on the mean-square stabilizing solution of a modified algebraic Riccati equation (MARE). Further, we propose a new algorithm for searching the mean-square stabilizing solution to the MARE. Finally, the simulation results verify the effectiveness and feasibility of the method proposed in this paper for the optimal asymptotic tracking problem of the networked feedback system over the lossy channel.