An iterative learning control based identification for a class of MIMO continuous-time systems in the presence of fixed input disturbances and measurement noises

摘要

This article presents an identification method based on an iterative learning control (ILC) for a class of linear MIMO (multi-input, multi-output) continuous-time systems with unknown but fixed input disturbances. For this purpose, a formula of a specific type of ILC which updates the input in an appropriate parameter space is extended to the case of MIMO systems with fixed disturbances. Then a concrete procedure to construct such an ILC is given to apply the ILC to the continuous-time system identification. Finally, numerical examples demonstrate how the parameter estimation can be achieved through the proposed ILC method in the presence of heavy measurement noises.