Coupled stochastic gradient identification algorithms for multivariate output-error systems using the auxiliary model

Abstract

This paper considers the gradient based identification problem of a multivariate output-error system. By using the auxiliary model identification idea and the coupling identification concept, an auxiliary model based stochastic gradient (AM-SG) algorithm and a coupled AM-SG algorithm are presented. The results indicate that the parameter estimation errors converge to zero under the persistent excitation conditions. The simulation examples confirm the theoretical results.