A Decentralized Learning controller for Nonlinear Systems

Abstract

This paper presents a decentralized learning controller for large-scale nonlinear systems. A new learning method which is based on a performance index of sliding mode control is used to derive an iterative learning algorithm to obtain control actions. The effectiveness and the performance of the proposed approach are illustrated by the simulation results of a two-inverted pendulum system and a two-link manipulator. The attractive features also include a smaller residual error and robustness against nonlinear interactions.