DocumentCode
2650101
Title
NARMAX model based on wavelet network with application in ship control
Author
Zhang, Wenjun ; Liu, Zhengjiang ; Li, Wei
Author_Institution
Dalian Maritime Univ., Dalian, China
fYear
2012
fDate
23-25 May 2012
Firstpage
2739
Lastpage
2743
Abstract
A wavelet neural network (WNN) is introduced to realize the system identification with nonlinear auto-regressive moving average with exogenous inputs (NARMAX) model. The method takes both advantages of the wavelet network and NARMAX model, and the multi-objective optimization method is used to real-time estimate the network coefficient. The wavelet-network-based NARMAX identification model is used as online system identifier, and the experimental result of ship course control proves the efficiency of the proposed neural identification model.
Keywords
autoregressive moving average processes; neural nets; optimisation; ships; wavelet transforms; NARMAX model; WNN; multi-objective optimization method; nonlinear auto-regressive moving average with exogenous inputs model; online system identifier; ship course control; wavelet neural network; Least squares approximation; Marine vehicles; Mathematical model; Neural networks; Predictive control; Predictive models; NARMAX; system identification; wavelet network;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2012 24th Chinese
Conference_Location
Taiyuan
Print_ISBN
978-1-4577-2073-4
Type
conf
DOI
10.1109/CCDC.2012.6243061
Filename
6243061
Link To Document