NARMAX Model Based on Wavelet Network with Application in Ship Control
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.
NARMAX wavelet network system identification
Wenjun Zhang Zhengjiang Liu Wei Li
Navigation College, Dalian Maritime University, Dalian 116026
国际会议
The 24th Chinese Control and Decision Conference (第24届中国控制与决策学术年会 2012 CCDC)
太原
英文
2751-2755
2012-05-23（万方平台首次上网日期，不代表论文的发表时间）