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	Optimal adaptive controller for stochastic systems based on weighted least-squares algorithm
	Jiang Rui ; Luo Gui-Ming
	2010-05-06 ; 2010-05-06
关键词	Theoretical or Mathematical/ adaptive control closed loop systems control system synthesis convergence least squares approximations linear systems optimal control stability stochastic systems/ optimal adaptive controller linear stochastic systems weighted least-squares algorithm recursive least-squares algorithm self-convergence property random vector control law design asymptotic properties closed-loop system one-step-ahead optimal controller/ C1340G Time-varying control systems C1340E Self-adjusting control systems C1330 Optimal control C1310 Control system analysis and synthesis methods C1320 Stability in control theory
中文摘要	In general, we can not guarantee the convergence of the common LS method. A recursive least-squares algorithm with slowly decreasing weights for linear stochastic systems is found to have self-convergence property, i.e., it converges to a certain random vector almost surely irrespective of the control law design. Such algorithms enjoy almost the same nice asymptotic properties as the standard least-squares. With adaptive control, the closed-loop system is globally stable and the adaptive controller may converge to the one-step-ahead optimal controller.
语种	中文 ; 中文
出版者	Science Press ; China
内容类型	期刊论文
源URL	[http://hdl.handle.net/123456789/9806]
专题	清华大学
推荐引用方式 GB/T 7714	Jiang Rui,Luo Gui-Ming. Optimal adaptive controller for stochastic systems based on weighted least-squares algorithm[J],2010, 2010.
APA	Jiang Rui,&Luo Gui-Ming.(2010).Optimal adaptive controller for stochastic systems based on weighted least-squares algorithm..
MLA	Jiang Rui,et al."Optimal adaptive controller for stochastic systems based on weighted least-squares algorithm".(2010).

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