Abstract

In this paper, we study the identification problem of Hammerstein nonlinear systems. A Levenberg-Marquardt iterative (LMI) algorithm is developed for Hammerstein nonlinear systems. The basic idea is to establish a Hammerstein nonlinear model by means of the key-term separation principle and then derive the LMI algorithm by replacing the unmeasurable variables in the information vector with their corresponding iterative estimates for the proposed model. Finally, the simulation results show the effectiveness of the LMI algorithm.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.