Adaptive Robust Control of DC Motors With Extended State Observer

Abstract

Structured and unstructured uncertainties always exist in physical servo systems and degrade their tracking accuracy. In this paper, a practical method named adaptive robust control with extended state observer (ESO) is synthesized for high-accuracy motion control of a dc motor. The proposed controller accounts for not only the structured uncertainties (i.e., parametric uncertainties) but also the unstructured uncertainties (i.e., nonlinear friction, external disturbances, and/or unmodeled dynamics). Adaptive control for the structured uncertainty and ESO for the unstructured uncertainty are designed for compensating them respectively and integrated together via a feedforward cancellation technique. The global robustness of the controller is guaranteed by a feedback robust law. Furthermore, the controller theoretically guarantees a prescribed tracking performance in the presence of various uncertainties, which is very important for high-accuracy control of motion systems. Extensive comparative experimental results are obtained to verify the high-performance nature of the proposed control strategy.