A new learning control approach to the active magnetic bearing benchmark system

This paper presents a nonlinear control method for the active magnetic bearing benchmark system. A flux input controller, based on a new iterative learning control strategy, is proposed to asymptotically regulate the system while compensating for periodic, exogenous disturbances. Numerical simulation results are presented to illustrate the performance of the proposed controller.