Stability analysis of iterative learning control system with interval uncertainty

Authors:	Chen YangQuan, CSOIS, Utah State University, United States Ahn Hyosung, CSOIS, Utah State University, United States Moore Kevin L., APL, Johns Hopkins University, United States
Topic:	1.2 Adaptive and Learning Systems
Session:	Iterative Learning Control
Keywords:	Iterative learning control; monotonic convergence; interval uncertainty; Schur stability; vertex matrices

Abstract

This paper presents a stability analysis of the iterative learning control (ILC) problem when the plant Markov parameters are subject to interval uncertainty. Using the super-vector approach to ILC, vertex Markov matrices are employed to develop sufficient conditions for both asymptotic stability and monotonic convergence of the ILC process. It is shown that Kharitonov segments between vertex matrices are not required for checking the stability of interval super-vector ILC systems, but instead checking just the vertex Markov matrices is sufficient.