Parameter identification for Hammerstein nonlinear systems using the maximum likelihood principle and Levenberg-Marquardt optimization method

This paper studies the parameter estimation problems of Hammerstein output error autoregressive (OEAR) systems. A maximum likelihood Levenberg-Marquardt recursive (ML-LM-R) algorithm using the varying interval input-output data is presented by using the maximum likelihood principle and Levenberg-Marquardt optimization method. The effectiveness of the algorithm is verified by a numerical example.