PD-type iterative learning control for linear continuous systems with arbitrary relative degree

Abstract

This article investigates the iterative learning control problem for linear continuous systems with fixed initial shifts. The systems have arbitrary relative degree and PD-type learning schemes are proposed. Under the effect of the PD-type learning schemes, the output-limiting trajectory is constructed. Based on the contraction mapping method, we show that the schemes can guarantee that the output of the iterative system converges uniformly to the output-limiting trajectory on the finite-time interval as the iteration index tends to infinity. A simulation example is used to illustrate the effectiveness of the proposed method.