Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
7109638 | Automatica | 2016 | 7 Pages |
Abstract
This note proposes convergence analysis of iterative learning control (ILC) for discrete-time linear systems with randomly varying iteration lengths. No prior information is required on the probability distribution of randomly varying iteration lengths. The conventional P-type update law is adopted with Arimoto-like gain and/or causal gain. The convergence both in almost sure and mean square senses is proved by direct math calculating. Numerical simulations verifies the theoretical analysis.
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Dong Shen, Wei Zhang, Youqing Wang, Chiang-Ju Chien,