Auxiliary model‐based iterative parameter estimation for a nonlinear output‐error system with saturation and dead‐zone nonlinearity
Xiao Wang, Feng Ding, Ahmed Alsaedi, Tasawar Hayat
Abstract
Abstract This article is concerned with the parameter estimation problem of a nonlinear output‐error system with saturation and dead‐zone nonlinearity. The saturation nonlinearities and the dead‐zone nonlinearities are widely encountered in engineering applications and the identification for the nonlinear systems with these nonlinearities is very crucial. Based on the over‐parameterization identification model and the auxiliary model identification idea, an auxiliary model least‐squares‐based iterative algorithm is presented for estimating the parameters of the nonlinear system with saturation and dead‐zone nonlinearity. In order to enhance the computational efficiency, an auxiliary model gradient‐based iterative algorithm is presented for the nonlinear system. Using the multi‐innovation identification theory, an auxiliary model multi‐innovation gradient‐based iterative algorithm is derived for tracking time‐varying parameters. An example is carried out to show the effectiveness of the proposed algorithms. The numerical simulation results show that all the proposed algorithms can generate accurate parameter estimates.