Hybrid Direct-Indirect Adaptive Control of Nonlinear System with Unmatched Uncertainty
This work addresses the challenge of controlling nonlinear systems with unmatched uncertainties, which is a known bottleneck in adaptive control.
The paper presents a hybrid direct-indirect adaptive controller for nonlinear systems with both matched and unmatched uncertainties, achieving reference model tracking by estimating unmatched uncertainty online and canceling matched uncertainty via a direct adaptive controller.
In this paper, we present a hybrid direct-indirect model reference adaptive controller (MRAC), to address a class of problems with matched and unmatched uncertainties. In the proposed architecture, the unmatched uncertainty is estimated online through a companion observer model. Upon convergence of the observer, the unmatched uncertainty estimate is remodeled into a state dependent linear form to augment the nominal system dynamics. Meanwhile, a direct adaptive controller designed for a switching system cancels the effect of matched uncertainty in the system and achieves reference model tracking. We demonstrate that the proposed hybrid controller can handle a broad class of nonlinear systems with both matched and unmatched uncertainties