ROBUST LEARNING CONTROL FOR NONLINEAR UNCERTAIN SYSTEMS BASED ON COMPOSITE ENERGY FUNCTION

摘要

In this paper the learnability of Iterative Learning Control (ILC) under the framework of energy function is explored. First we show that ILC is in essence a pointwise adaptation learning mechanism which can henceforth learn iteration-independent time-varying uncertainties. Next we propose a new robust ILC scheme to address norm-bounded uncertainties. The concept of Composite Energy Function (CEF) is introduced in the analysis of the learning convergence, consequently the proposed ILC schemes are applicable to quite general systems.