System and Disturbance Identification for Model-Based learning and Repetitive Control

An extension of interaction matrix formulation to the problem of system and disturbance identification for a plant that is corrupter by both process and output disturbances is presented. With only an assumed upper bound on the order of the system and an assumed upper bound on the number of disturbance frequencies, it is shown that both the disturbance-free model and disturbance effect can be recovered exactly from disturbance-corrupted input-output data without direct measurement of the periodic disturbances. The rich information returned by the identification can be used by a performance-oriented model-based loaming or repetitive control system to eliminate unwanted periodic disturbances.