AN IDENTIFICATION METHOD FOR MIMO CONTINUOUS-TIME SYSTEMS VIA ITERATIVE LEARNING CONTROL CONCEPTS

This paper presents an identification method based on an iterative learning control (ILC) concept for the multivariable continuous-time system. For this purpose a projection type ILC, which updates the input in an appropriate parameter space, is extended to the case of multivariable systems. The robustness against measurement noise is achieved through both projection of continuous-time I/O signals onto a finite dimensional space and noise tolerant learning algorithms. Finally, a numerical example is given to demonstrate how the parameter estimation can be achieved through the proposed identification method in the presence of heavy measurement noises.