Iterative learning control for switched singular systems

Abstract

In this paper, the problem of iterative learning control is considered for a class of switched singular systems. And the considered switched singular systems with arbitrary switching rules are operated in a fixed time interval repetitively. Based on the singular value decomposition method, the switched singular systems are transformed into the switched differential-algebraic systems. Then an iterative learning control algorithm, which is composed of D-type and P-type learning algorithms, is proposed. Using the contraction mapping principle, it is shown that the algorithm can guarantee the state tracking error to converge uniformly to zero as the iteration increases. Finally, a numerical example is constructed to illustrate the effectiveness of the presented algorithm.