Comparative studies of model reference adaptive control systems

Abstract

A brief but up-to-date survey on existing methods of designing a class of model reference adaptive control systems is given in this paper. A comparison of the merits of the various design rules is also made with particular attention to the M.I.T. rule and the Lyapunov synthesis technique. Subsequently a systematic performance comparison of the various designs, with deterministic as well as stochastic inputs, is presented using the computer simulation studies of two simple gain adjustment schemes. From the dimensionless characteristic graphs obtained the Lyapunov schemes are found to exhibit superior performance over other designs. These graphs also uncover the strange adaptive response of those designs based on gradient methods in that the performance index may increase or decrease with increasing system gain parameters.