Robust direct model reference adaptive controllers

Abstract

This paper presents the design of a robust model reference adaptive control (MRAC) algorithm with focus on the satisfaction of an almost strictly positive real (ASPR) condition over the maximal range of parameter variations of the plant. To alleviate the ASPR condition, a feedforward compensator design procedure is developed using Kharitonov's theorem for robust stability. A MRAC algorithm which ensures asymptotic model following is integrated with the feedforward compensator design procedure. Thus, the sufficient conditions for asymptotic stability are extended over a wide range of parameter variations. The new algorithm is applied to single input-single output plants (SISO) with significant parametric uncertainty and unmodeled dynamics. Simulation examples are given to demonstrate the usefulness of the algorithm.