Recursive Identification Methods for a Hammerstein System 

Wentian Liu 

College of Automation and Electrical Engineering, Qingdao University, Qingdao, 266071, China 

Abstract: The maximum likelihood algorithm has extensive applications in dynamic nonlinear systems with colored noise. This paper proposes recursive identification methods based on maximum likelihood algorithm for a multivariable Hammerstein system with controlled autoregressive moving average noises. The result from simulation indicates that the estimates of system are consistent with their true values and the proposed methods have well stability, feasibility and validity.

Keywords: Maximum likelihood; Multivariable; Hammerstein