Recursive Identification for Hammerstein Systems with Hybrid Static Nonlinearities and Asymmetric ARX
In this paper,an iterative identification for the Hammerstein model,which consists of a static nonlinear part in cascade with a linear dynamic part,is introduced.Therein,the static nonlinear part is composed of two-segment polynomials in series with dead-zone nonlinearities,while the linear part takes on the asymmetric ARX(autoregressive with exogenous inputs)dynamics.For the Hammerstein system,the so-called key-term separation principle was firstly implemented to separate the parameters of both the static nonlinear sub-model and dynamic block.Thereafter,the system output is represented by a special form of linear combination of the parameters.Then,a modified Recursive General Least Squares Algorithm(RGLS)was introduced for the iterative estimation of the parameters.Finally,the presented simulation results had validated the effectiveness of the proposed method.
polynomial nonlinear dead-zone key term separation Hammerstein model two-segment
ZHANG Xinliang TAN Yonghong
School of Electrical Engineering and Automation,Henan Polytechnic University,Jiaozuo,Henan,454003,Ch College of Information,Mechanical and Electronic Engineering,Shanghai Normal University,Shanghai 200
国际会议
The 33th Chinese Control Conference第33届中国控制会议
南京
英文
6678-6681
2014-07-28（万方平台首次上网日期，不代表论文的发表时间）