New hybrid controller for systems with deterministic uncertainties

Improving both transient and steady-state response performances of systems is a challenging problem, especially in the face of system nonlinearities and uncertainties. In this paper, a new hybrid controller for systems with deterministic uncertainties is developed. The proposed controller identifiies and compensates deterministic uncertainties simultaneously. It is the combination of a time-domain feedback controller and a frequency-domain iterative learning controller. The feedback controller decreases system variability and reduces the effect of random disturbances. The iterative learning controller shapes the system input to suppress the error caused by deterministic uncertainties such as friction and backlash. The control scheme use only local input and output information, no system model is required. The uncertainties can be structured or unstructured. The effectiveness of the proposed controller is experimentally verified on a servo system with gearbox.