Adaptive sampled-data based linear quadratic optimal control of stochastic systems

doi:10.1080/00207170701487763

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	Adaptive sampled-data based linear quadratic optimal control of stochastic systems
	Tan, S.; Zhang, J. F.
	2007
发表期刊	INTERNATIONAL JOURNAL OF CONTROL
ISSN	0020-7179
卷号	80 期号:10 页码:1676-1689
摘要	The problem of sampled-data (SD) based adaptive linear quadratic (LQ) optimal control is considered for linear stochastic continuous-time systems with unknown parameters and disturbances. To overcome the difficulties caused by the unknown parameters and incompleteness of the state information, and to probe into the influence of sample size on system performance, a cost-biased parameter estimator and an adaptive control design method are presented. Under the assumption that the unknown parameter belongs to a known finite set, some sufficient conditions ensuring the convergence of the parameter estimate are obtained. It is shown that when the sample step size is small, the SD-based adaptive control is LQ optimal for the corresponding discretized system, and sub-optimal compared with that of the case where the parameter is known and the information is complete.
DOI	10.1080/00207170701487763
语种	英语
WOS研究方向	Automation & Control Systems
WOS类目	Automation & Control Systems
WOS记录号	WOS:000249589400013
出版者	TAYLOR & FRANCIS LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/4080
专题	中国科学院数学与系统科学研究院
通讯作者	Zhang, J. F.
作者单位	1.Beijing Inst Control Engn, Natl Lab Space Intelligent Control, Beijing 100080, Peoples R China 2.Chinese Acad Sci, Key Lab Syst & Control, Acad Math & Syst Sci, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Tan, S.,Zhang, J. F.. Adaptive sampled-data based linear quadratic optimal control of stochastic systems[J]. INTERNATIONAL JOURNAL OF CONTROL,2007,80(10):1676-1689.
APA	Tan, S.,&Zhang, J. F..(2007).Adaptive sampled-data based linear quadratic optimal control of stochastic systems.INTERNATIONAL JOURNAL OF CONTROL,80(10),1676-1689.
MLA	Tan, S.,et al."Adaptive sampled-data based linear quadratic optimal control of stochastic systems".INTERNATIONAL JOURNAL OF CONTROL 80.10(2007):1676-1689.