Robustness and Convergence of Least-Squares Identification and Adaptive Tracking for Stochastic System
Hong Huimin · Control theory & applications · 1992
Based on the extended least squares (ELS) algorithm estimating unknown parameters of modeled part in a stochastic system the adaptive controller for tracking a stochastic reference signal is recursively defined.It is shown that the closed-loop system is stable;the estimation error decreases as the unmodeled dynamics decays and the tracking error differs from the minimum plus a small value when the unmodeled dynamics is bounded in the average sense;the strong consistency of the estimates and the asymptotical optimality of the adaptive tracking are obtained when the unmodeled dynamics approaches zero in the average sense.