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Identification of nonlinear dynamic systems using Hammerstein-type neural network
Yu HS(余洪山); Peng, Jinzhu; Tang YD(唐延东)
作者部门机器人学研究室
发表期刊Mathematical Problems in Engineering
ISSN1024-123X
2014
卷号2014期号:2014
收录类别SCI ; EI
EI收录号20144700235648
WOS记录号WOS:000345050300001
产权排序1
摘要Hammerstein model has been popularly applied to identify the nonlinear systems. In this paper, a Hammerstein-type neural network (HTNN) is derived to formulate the well-known Hammerstein model. The HTNN consists of a nonlinear static gain in cascade with a linear dynamic part. First, the Lipschitz criterion for order determination is derived. Second, the backpropagation algorithm for updating the network weights is presented, and the stability analysis is also drawn. Finally, simulation results show that HTNN identification approach demonstrated identification performances.
语种英语
WOS类目Engineering, Multidisciplinary ; Mathematics, Interdisciplinary Applications
关键词[WOS]PREDICTIVE CONTROL ; WIENER MODELS
WOS研究方向Engineering ; Mathematics
引用统计
文献类型期刊论文
条目标识符http://ir.sia.cn/handle/173321/15661
专题机器人学研究室
通讯作者Yu HS(余洪山)
作者单位1.College of Electrical and Information Engineering, Hunan University, Changsha, China
2.State Key Laboratory of Robotics, Shenyang, China
3.School of Electrical Engineering, Zhengzhou University, Zhengzhou, China
推荐引用方式
GB/T 7714
Yu HS,Peng, Jinzhu,Tang YD. Identification of nonlinear dynamic systems using Hammerstein-type neural network[J]. Mathematical Problems in Engineering,2014,2014(2014).
APA Yu HS,Peng, Jinzhu,&Tang YD.(2014).Identification of nonlinear dynamic systems using Hammerstein-type neural network.Mathematical Problems in Engineering,2014(2014).
MLA Yu HS,et al."Identification of nonlinear dynamic systems using Hammerstein-type neural network".Mathematical Problems in Engineering 2014.2014(2014).
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