Adaptive iterative learning control with trajectory shift

Abstract

In order to solve the problem of trajectory shift in iterative learning control, an adaptive iterative learning control strategy was proposed. For linear time-varying systems with unknown parameters, an adaptive parameter updating algorithm was constructed by solving a quadratic programming problem. The estimated parameter information and trajectory information with shift were used to design an adaptive iterative learning control strategy. The results show that the estimation error of parameters is bounded, and the tracking error of the system is bounded when the trajectory shift is bounded. The effectiveness and practicability of the proposed adaptive iterative learning control strategy are verified by numerical simulation.

Keywords

• trajectory shift
• adaptive iterative learning control
• parameter matrix estimation
• linear system
• boundedness