Abstract
This paper deals with the design of a weighted adaptive one-step-ahead minimum variance controller based on the extended least squares (ELS) algorithm for a discrete time stochastic system. The stability of the closed-loop system and the convergence rates of the general adaptive tracking and estimation errors are respectively established under strictly positive real and minimum phase conditions. The best possible convergence rate of the average error between the predicted and desired outputs is obtained given some identifying condition and the above-stated conditions. No modification of the adaptive controller is made. © 1997 by John Wiley & Sons, Ltd.
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