Hybrid Fuzzy Cuckoo Search Algorithm for MIMO Hammerstein Model Identification Under Heavy-Tailed Noises

In this paper, we study the problem of MIMO Hammerstein systems identification under heavy-tailed noises. As far as we know, there is no effective method to solve this problem. Inspired by this, we firstly introduced fuzzy logic and the nonlinear stochastic search (NLJ) algorithm to modify cuckoo search algorithm (CS) and proposed a novel CS algorithm (HFCS). According to Taylor expansion formula, the nonlinear block of the Hammerstein model is approximated by a class of polynomial family. Then, HFCS is used to estimate parameters of the model. The simulation results verify the efficiency of the proposed method.