Stability judgement and accurate simulation of stochastic systems with discrete time feedbacks and applications
The talk is concerned with some essential features of stochastic control systems with sampled data based (SCSwSDs). Firstly it is shown by two propositions that the moment asymptotic stability of the underlying system is equivalent to that of any regular accurate numerical scheme under simple conditions, which is convenient to be structured specially for SCSwSDs. This kind of principle provides a way for inferring moment asymptotic stability of SCSwSDs by numerical simulations logically. The accurate scheme construction procedure is introduced in a general framework and illustrated for the quasi linear models, the mean square asymptotic stability of linear SCSwSDs is investigated as the first application of the propositions. It is found that stochastic systems may be stabilized in appointed time by sampled data based control (SDBC). The restriction to the upper bound of the sampling period is confirmed by the way. The almost sure stability of a kind of controlled system with sampled noise is analyzed via the discrete scheme approach as the second application of the propositions. The concepts of accurate numerical computation and simulation (ANCS) are proposed.A distinctive character, SDBC-only in short, for SDBC is reported and studied preliminarily based on ANCS and the equivalence propositions. Some important remarks are given as further analyses on some related issues. Finally, three numerical examples are given to illustrate the applications of the theoretical results of the paper.
1983年毕业于湖南大学计算数学专业，获学士学位，1997年毕业于华南理工大学自动控制专业，获工学博士学位。现为华南理工大学学术委员会委员、系统工程研究所所长；IEEE CSS Guangzhou Chapter主席、中国自动化学会控制理论专业委员会（TCCT）委员、广东省物联网技术标准委员会主任、IEEE Access Associate Editor、《华南理工大学学报》（自然科学版）副主编、CCC-中国科学张贴论文奖评奖委员会委员、TCCT随机系统控制学组主任，中国仿真学会不确定系统分析与仿真专业委员会副主任。主要研究复杂系统控制理论，出版专著4部，发表论文300多篇。2016年度中国自动化学会优秀博士论文奖指导教师。