Model reference adaptive control based on a novel scalar update law

Abstract

AbstractThis paper puts forward a model reference adaptive control (MRAC) framework with a compensator based on a novel scalar update law for the dynamical systems with matched uncertainty. The scalar update law is given by an algebraic expression of basis functions and system errors. The main advantage of the proposed MRAC framework is that only a scalar function requires updating online such that the architecture is simple and the computational burden in the existing results can be relieved. Furthermore, the asymptotic stability of the system error dynamics is guaranteed by the proposed controller. Two numerical examples are given to demonstrate the effectiveness of the proposed MRAC framework.