A comparison study of system identification using Hammerstein model

Abstract

An attempt has been made in this paper to present performance analysis of a Hammerstein model for system identification area. Hammerstein model block structure is formed by cascade of linear and nonlinear parts. This study different from the studies in literature, focuses on the performance of Hammerstein block model that Second Order Volterra (SOV) Model is preferred instead of Memoryless Polynomial Nonlinear (MPN) as nonlinear part. In simulations, different systems are identified by proposed Hammerstein model which is optimized with classical and heuristic algorithms. Also, its performance is compared with different models.