A design of discrete-time multivariable iterative learning control systems with interactor matrix

In this paper, it is proposed a discrete-time multivariable iterative learning control (ILC) algorithm which guarantees the monotonic convergence of the tracking error norms along with the number of the trials. It is pointed out that an interactor matrix plays an important role in the iterative learning control. Since ILC is a design method not requiring plant parameters explicitly, the information on the interactor matrix should be treated same manner as in an adaptive control systems. In this paper, it is presented a design of ILC using G-interactor which is derived not requiring the plant parameters. It is also presented a design of ILC using a diagonal precompensator which will make the interactor of the compensated plant be diagonal. Numerical simulations are presented to confirm the validity of the proposed design.