학술논문

Hybrid Fuzzy Cuckoo Search Algorithm for MIMO Hammerstein Model Identification Under Heavy-Tailed Noises
Document Type
Conference
Source
2018 37th Chinese Control Conference (CCC) Control Conference (CCC), 2018 37th Chinese. :1881-1886 Jul, 2018
Subject
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Hybrid fiber coaxial cables
Fuzzy systems
MIMO communication
Heuristic algorithms
Fuzzy logic
Optimization
Search problems
HFCS
cuckoo search
NLJ
MIMO Hammerstein system
Heavy-tailed noises
Language
ISSN
1934-1768
Abstract
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.