Error-Tracking Learning Control Method Based on Iterative Extended State Observer

Abstract

we propose an error-tracking learning control method based on iterative extended state observer for a class of nonparametric uncertain systems, aiming at relaxation of initial positioning conditions for conventional iterative learning control method so as to allow any position of the initial value at each iteration and effectively process the effect of uncertain system items on tracking accuracy. It firstly constructs an appropriate expected error trajectory, followed by the linear iterative extended state observer proposed for uncertain system items which evaluates uncertain system items with LIESO, and then presents a learning control algorithm based on this method, which allows convergence of actual tracking error to the default error trajectory to realize that the system state accurately tracks reference signals within the work interval. Simulation results indicate the effectiveness of the method.