Hierarchical recursive gradient identification of Hammerstein nonlinear systems based on the key term separation

This is the authors' abstract. We don't add key points for this paper.

This article explores recursive algorithms for parameter identification issues of Hammerstein output-error systems. The proposed approach includes the key term separation auxiliary model recursive gradient algorithm, which utilizes the gradient search and the key term separation. To enhance computational efficiency, the system is decomposed into two or three subsystems through the hierarchical identification principle. Based on this, a key term separation auxiliary model two-stage recursive gradient algorithm and a key term separation auxiliary model three-stage recursive gradient algorithm are presented. The simulation results verify the validity of the obtained algorithms.