Optimal Gains of Iterative Learning Control with Forgetting Factor

doi:10.1051/jnwpu/20193751077

CORC > 兰州理工大学 > 兰州理工大学 > 机电工程学院

	Optimal Gains of Iterative Learning Control with Forgetting Factor
	Dai, Baolin; Gong, Jun; Li, Cuiming
刊名	Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University
	2019-10-01
卷号	37 期号:5 页码:1077-1084
关键词	Algorithms Discrete time control systems Iterative methods Linear control systems Linear systems Matrix algebra Optimization Time varying systems Two term control systems Convergence conditions Convergence speed Forgetting factors Iterative learning control Optimal control gain Simulation Time-iteration-varying disturbances
ISSN号	10002758
DOI	10.1051/jnwpu/20193751077
英文摘要	In order to solve the optimization problems of convergence characteristics of a class of single-input single-output (SISO) discrete linear time-varying systems (LTI) with time-iteration-varying disturbances, an optimal control gain design method of PID type iterative learning control (ILC) algorithm with forgetting factor was presented. The necessary and sufficient condition for the ILC system convergence was obtained based on iterative matrix theory. The convergence of the learning algorithm was proved based on operator theory. According to optimization theory and Toeplitz matrix characteristics, the monotonic convergence condition of the system was established. The accurate solution of the optimal control gain and the relationship equation between the forgetting factor and the optimal control gains were obtained according to the optimal theory which ensures the fastest system convergence speed, thereby reaching the end of the system convergence improvement. The convergence condition is weaker than the known results. The proposed method overcomes the shortcomings of traditional optimal control gain in ILC algorithm with forgetting factor, effectively accelerates the system convergence speed, suppresses the system output track error fluctuation, and provides a better solution for LTI system with time-iteration-varying disturbances. Simulation verifies the effectiveness of the control algorithm. © 2019 Journal of Northwestern Polytechnical University.
语种	中文
出版者	Northwestern Polytechnical University
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/113871]
专题	机电工程学院
作者单位	School of Mechanical & Electronical Engineering, Lanzhou University of Technology, Lanzhou; 730050, China
推荐引用方式 GB/T 7714	Dai, Baolin,Gong, Jun,Li, Cuiming. Optimal Gains of Iterative Learning Control with Forgetting Factor[J]. Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University,2019,37(5):1077-1084.
APA	Dai, Baolin,Gong, Jun,&Li, Cuiming.(2019).Optimal Gains of Iterative Learning Control with Forgetting Factor.Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University,37(5),1077-1084.
MLA	Dai, Baolin,et al."Optimal Gains of Iterative Learning Control with Forgetting Factor".Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University 37.5(2019):1077-1084.