南京理工大学学报（自然科学版）2017，Vol.41Issue(6)：738-747,10.DOI:10.14177/j.cnki.32-1397n.2017.41.06.012
非均匀采样Hammerstein系统的梯度迭代辨识算法
Gradient based iterative identification algorithm for non-uniformly sampled Hammerstein systems
摘要
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.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Key words
non-uniform sampling/Hammerstein model/gradient based iterative algorithm/parameter identification/key-term separation technique/negative gradient search principle分类
信息技术与安全科学引用本文复制引用
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(6):738-747,10.基金项目
国家自然科学基金(61403166 （）
61773181) （）
江苏省自然科学基金(BK20140164) （BK20140164）
中央高校基本科研业务费专项资金(JUSRP11561 （）
JUSRP51510) （）
