中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Mean-square error constrained approach to robust stochastic iterative learning control

文献类型:期刊论文

作者Li Li; Yang Liu; Zhile Yang; Xiaofeng Yang; Kang Li
刊名IET Control Theory & Applications
出版日期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
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).

入库方式: OAI收割

来源:深圳先进技术研究院

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