A Discrete-time AILC for Systems with Non-parametric Uncertainties

Key Words:Adaptive Iterative learning control; Non-parametric Uncertainties; Random Initial Condition; Iteration-varying Trajectories; Discrete-time Systems

Abstract:In this paper, a discrete adaptive ILC is presented for a time-varying nonlinear system with nonparametric uncertainties. A novel estimation of nonparametric uncertainties is constructed just using the past I/O data, and the uncertainties are completely compensated such that the output tracking error is only affected by external disturbance. As a main contribution of this paper, all the discussions are done with the random initial condition and the iteration-varying target trajectories. Both the rigorous mathematical analysis and the simulation results illustrate the correctness and effectiveness of the proposed approach.

Translation or Not:no