Title
Adaptive Filtering Scheme For Parameter Identification Of Nonlinear Wiener-Hammerstein Systems And Its Application
Abstract
In this paper, a novel adaptive filtering scheme is first proposed to estimate the parameters of the nonlinear Wiener-Hammerstein systems with hysteresis, which is derived by exploiting the filtering technique and cost function framework. Different from the conventional cost function, the cost function of this paper involves estimation error information term and initial estimate term. In this scheme, the filtering technique is utilised to produce the estimation error information by using a group of auxiliary variables. The estimation error information term can improve the estimation accuracy. Based on developed cost function framework, the parameter update law is derived. Furthermore, the convergence of the proposed scheme is proved under the persistent excitation condition (PE). The efficiency and applicability of the proposed scheme are validated through the simulation and experiment.
Year
DOI
Venue
2020
10.1080/00207179.2019.1566634
INTERNATIONAL JOURNAL OF CONTROL
Keywords
DocType
Volume
Wiener-Hammerstein systems, hysteresis, parameter identification, cost function, filtering technique
Journal
93
Issue
ISSN
Citations 
10
0020-7179
0
PageRank 
References 
Authors
0.34
23
2
Name
Order
Citations
PageRank
Linwei Li193.94
xuemei ren2134.28