Open AccessStability of varying two‐dimensional Roesser systems and its application to iterative learning control convergence analysis
Author(s) -
Meng Deyuan,
Jia Yingmin,
Du Junping
Publication year - 2015
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2014.0643
Subject(s) - iterative learning control , control theory (sociology) , robustness (evolution) , convergence (economics) , stability (learning theory) , mathematics , linear system , mathematical optimization , computer science , control (management) , artificial intelligence , mathematical analysis , machine learning , economics , economic growth , biochemistry , chemistry , gene
This study considers the convergence analysis approach to iterative learning control (ILC) which is achieved based on two‐dimensional (2D) Roesser systems. Stability results are proposed for 2D Roesser systems when they are subject to varying parameters with respect to independent time and iteration axes. It is shown that the convergence analysis of ILC for a class of non‐linear systems can be performed based on the established stability results of varying 2D Roesser systems. Moreover, the presented convergence results of ILC can work with sufficient robustness against iteration‐varying initial state shifts. Illustrative simulations are included to verify the established convergence results of ILC for non‐linear systems.