Parameter Identification for a Class of Stochastic Systems with Unknown Parameters via Modified Gauss-Newton Method

Abstract

In this paper, an identification problem of uncertain parameters which are involved in the mathematical model is investigated for a class of stochastic uncertain systems. First, it is shown that the parameter identification can be achieved by solving the state estimation and the least-squares problem simultaneously. Secondly, a modified Gauss-Newton method is proposed, showing that it has contraction property. Finally, a numerical example is shown to demonstrate the efficiancy of the identification method proposed here for a process modeled by a first-order system with time-delay.