[1]谢 莉,杨慧中.非均匀采样Hammerstein系统的梯度迭代辨识算法[J].南京理工大学学报(自然科学版),2017,41(06):738.[doi:10.14177/j.cnki.32-1397n.2017.41.06.012]
 Xie Li,Yang Huizhong.Gradient based iterative identification algorithm for non-uniformlysampled Hammerstein systems[J].Journal of Nanjing University of Science and Technology,2017,41(06):738.[doi:10.14177/j.cnki.32-1397n.2017.41.06.012]
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非均匀采样Hammerstein系统的梯度迭代辨识算法()
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
41卷
期数:
2017年06期
页码:
738
栏目:
出版日期:
2017-12-31

文章信息/Info

Title:
Gradient based iterative identification algorithm for non-uniformlysampled Hammerstein systems
文章编号:
1005-9830(2017)06-0738-10
作者:
谢 莉杨慧中
江南大学 教育部轻工过程先进控制重点实验室,江苏 无锡 214122
Author(s):
Xie LiYang Huizhong
Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education),Jiangnan University,Wuxi 214122,China
关键词:
非均匀采样 Hammerstein模型 梯度迭代算法 参数辨识 关键项分离技术 负梯度搜索原理
Keywords:
non-uniform sampling Hammerstein model gradient based iterative algorithm parameter identification key-term separation technique negative gradient search principle
分类号:
TP273
DOI:
10.14177/j.cnki.32-1397n.2017.41.06.012
摘要:
为了解决Hammerstein非线性系统在非均匀采样条件下的辨识问题,该文提出了1种能够用于在线参数估计的梯度迭代算法。通过引入时变后移算子,推导了非均匀采样Hammerstein系统的离散时间模型。采用关键项分离技术将系统参数化为1个线性回归模型。基于辅助模型辨识思想对未知中间变量进行重构,并利用负梯度搜索原理获得模型参数的迭代估计。仿真结果表明,该文方法是有效的,且比辅助模型随机梯度算法具有更快的收敛速度,参数估计精度提高近40倍。
Abstract:
A gradient based iterative algorithm for online parameter estimation is proposed to solve the identification problem of Hammerstein nonlinear systems with non-uniform sampling.A discrete-time model of non-uniformly sampled Hammerstein systems is derived by introducing a time-varying backward shift operator.The system is parameterized into a linear regression model by applying the key-term separation technique.The unknown intermediate variables are reconstructed based on the auxiliary model identification idea,and the iterative estimates of model parameters are obtained through the negative gradient search principle.The simulation results indicate that,the proposed method is effective and has a faster convergence rate than the auxiliary model based stochastic gradient algorithm,and the estimation accuracy is improved by nearly 40 times.

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相似文献/References:

[1]王庆超,张健中.基于Hammerstein模型的连续搅拌反应釜非线性预测控制[J].南京理工大学学报(自然科学版),2010,(05):618.
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[2]熊伟丽,陈敏芳,王 肖,等.运用改进差分进化算法辨识Hammerstein模型[J].南京理工大学学报(自然科学版),2013,37(04):536.
 Xiong Weili,Chen Minfang,Wang Xiao,et al.System identification method for Hammerstein model based on improved differential evolution algorithm[J].Journal of Nanjing University of Science and Technology,2013,37(06):536.

备注/Memo

备注/Memo:
收稿日期:2017-07-11 修回日期:2017-09-11
基金项目:国家自然科学基金(61403166; 61773181); 江苏省自然科学基金(BK20140164); 中央高校基本科研业务费专项资金(JUSRP11561; JUSRP51510)
作者简介:谢莉(1985-),女,博士,讲师,主要研究方向:多率系统辨识,E-mail:xieli@jiangnan.edu.cn。
引文格式:谢莉,杨慧中.非均匀采样Hammerstein系统的梯度迭代辨识算法[J].南京理工大学学报,2017,41(6):738-747.
投稿网址:http://zrxuebao.njust.edu.cn
更新日期/Last Update: 2017-12-31