Mean-square error constrained approach to robust stochastic iterative learning control

	Mean-square error constrained approach to robust stochastic iterative learning control
	Li Li; Yang Liu; Zhile Yang; Xiaofeng Yang; Kang Li
刊名	IET Control Theory & Applications
	2018
文献子类	期刊论文
英文摘要	A Kalman filtering-based robust iterative learning control algorithm is proposed in this study for linear stochastic systems with uncertain dynamics and unknown noise statistics. Firstly, a learning gain matrix is designed for the nominal case by minimising the trace of the mean-square matrix of the input tracking error. Theoretical results show that the proposed algorithm guarantees not only the asymptotic but also monotonic convergence of the input tracking error in the mean-square error sense, especially when random noises are Gaussian distributed the proposed algorithm is further proved to be asymptotically efficient. In addition, a new mean-square error constrained approach is presented in designing the robust learning gain matrix, taking into account model uncertainties. A sufficient condition is provided such that the mean-square matrix of the input tracking error is constrained within a predesigned upper bound which can monotonically converge to zero. Finally, numerical examples considering both structured and unstructured model uncertainties are included to illustrate the effectiveness of the proposed algorithms.
URL标识	查看原文
语种	英语
WOS记录号	WOS:000419019000005
内容类型	期刊论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/12493]
专题	深圳先进技术研究院_数字所
作者单位	IET Control Theory & Applications
推荐引用方式 GB/T 7714	Li Li,Yang Liu,Zhile Yang,et al. Mean-square error constrained approach to robust stochastic iterative learning control[J]. IET Control Theory & Applications,2018.
APA	Li Li,Yang Liu,Zhile Yang,Xiaofeng Yang,&Kang Li.(2018).Mean-square error constrained approach to robust stochastic iterative learning control.IET Control Theory & Applications.
MLA	Li Li,et al."Mean-square error constrained approach to robust stochastic iterative learning control".IET Control Theory & Applications (2018).