Data-Driven based Iterative Learning Control for A Class of Discrete-Time Descriptor Systems

Data-driven iterative learning control (ILC) for discrete-time descriptor systems is concerned. The input-output property of single-input and single-output (SISO) discrete-time descriptor system is analyzed firstly. Then the relative degree of the underlying descriptor is investigated. Under the assumption that the system is causal, an ILC algorithm is presented based on the lifted form of descriptor system with zero relative degree. The ILC algorithm update the inputs serial by using the system tracking error, and does not need to know the inner structure of the target descriptor system in advance. Simulation results shows that, the presented ILC algorithm can make the target descriptor system's output track the desired output well.