Stable weighted multiple model adaptive control: discrete-time stochastic plant

摘要

A stable weighted multiple model adaptive control system for uncertain linear, discrete-time stochastic plant is presented in the paper. First, a new scheme for calculating controller weights is proposed with assured convergence, that is, the controller weight corresponding to the model closest to the true plant converges to 1, and others converge to 0; second, on the basis of virtual equivalent system concept and methodology, the stability of the overall closed-loop control system is proved under a unified framework which is independent of specific 'local' control strategy.