p-Accelerated normal S-iterative learning control algorithm for linear discrete singular time-delay systems

Abstract

This article addresses the issue of iterative learning control for a specific category of discrete linear singular time-delay systems. A new iterative learning control algorithm based on the p-accelerated normal S-iteration method is proposed, and convergence analysis of the corresponding learning control algorithm is studied. With certain assumptions, the proposed algorithm guarantees that the output of the system converges to the desired output trajectory within a finite time interval. The theoretical analysis is supported by numerical examples. The results indicate that the p-accelerated normal S-iterative learning control algorithm outperforms both the first-order PD-type iterative learning control and second-order PD-type iterative learning control algorithms for discrete linear singular systems theoretically and numerically.

KEYWORDS:

• Iterative learning control
• state-delay
• super-vector representation
• p-accelerated normal S-iteration method
• singular system

Disclosure statement

No potential conflict of interest was reported by the author(s).