Performance analysis of the AM-SG parameter estimation for multivariable systems

The auxiliary model based stochastic gradient (AM-SG) parameter estimation method is an important identification one. This paper analyzes the performances of the AM-SG estimation algorithm for multiple-input single-output systems (i.e., multivariable systems) under the strong persistent excitation condition. The analysis and simulation results indicate that the parameter estimation errors converge to zero.