Parameter estimation for dual-rate sampled Hammerstein systems with dead-zone nonlinearity  

作　　者：WANG Hongwei CHEN Yuxiao 

机构地区：[1]School of Electrical Engineering,Xinjiang University,Urumqi 830047,China [2]School of Control Science and Engineering,Dalian University of Technology,Dalian 110024,China

出　　处：《Journal of Systems Engineering and Electronics》2020年第1期185-193,共9页系统工程与电子技术（英文版）

基　　金：supported by the National Natural Science Foundation of China(61863034)

摘　　要：The identification of nonlinear systems with multiple sampled rates is a difficult task.The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by using the dual-rate sampled data.Firstly,the auxiliary model identification principle is used to estimate the unmeasurable variables,and the recursive estimation algorithm is proposed to identify the parameters of the static nonlinear model with the dead-zone function and the parameters of the dynamic linear system model.Then,the convergence of the proposed identification algorithm is analyzed by using the martingale convergence theorem.It is proved theoretically that the estimated parameters can converge to the real values under the condition of continuous excitation.Finally,the validity of the proposed algorithm is proved by the identification of the dual-rate sampled nonlinear systems.The identification of nonlinear systems with multiple sampled rates is a difficult task. The motivation of our paper is to study the parameter estimation problem of Hammerstein systems with dead-zone characteristics by using the dual-rate sampled data. Firstly, the auxiliary model identification principle is used to estimate the unmeasurable variables, and the recursive estimation algorithm is proposed to identify the parameters of the static nonlinear model with the dead-zone function and the parameters of the dynamic linear system model. Then, the convergence of the proposed identification algorithm is analyzed by using the martingale convergence theorem. It is proved theoretically that the estimated parameters can converge to the real values under the condition of continuous excitation. Finally, the validity of the proposed algorithm is proved by the identification of the dual-rate sampled nonlinear systems.

关 键 词：dual-rate sampled data dead-zone nonlinearity Hammerstein model system identification convergence analysis 

分 类 号：O212.1[理学—概率论与数理统计]