Parameter identification of a class of nonlinear systems with numerical optimization technique

Abstract

A time domain technique for the identification of unknown parameters in the nonlinear system of some given structures is presented. The nonlinearities considered in this paper are in the forms of saturation, deadzone and backlash. The steps of the identification process are first to set the initial or guessed system parameters in a learning model, then apply the recorded input signal of the actual system to the mathematical learning model. By comparing the output errors between the model's and the system's responses, an optimization algorithm can be applied to search for the true parameters of the nonlinear system in order to meet a least mean square error criterion. The computer simulations have demonstrated the feasibility of this numerical technique.