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