Auxiliary model-based RELS and MI-ELS algorithm for Hammerstein OEMA systems

Authors:
Dongqing Wang;Yanyun Chu;Feng Ding
Affiliations:
College of Automation Engineering, Qingdao University, Qingdao 266071, PR China;College of Automation Engineering, Qingdao University, Qingdao 266071, PR China;School of Communication and Control Engineering, Jiangnan University, Wuxi 214122, PR China
Venue:
Computers & Mathematics with Applications
Year:
2010

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Abstract

This paper considers the identification problem for Hammerstein output error moving average (OEMA) systems. An auxiliary model-based recursive extended least-squares (RELS) algorithm and an auxiliary model-based multi-innovation extended least-squares (MI-ELS) algorithm are presented using the multi-innovation identification theory. The basic idea is to express the system output as a linear combination of the parameters by using the key-term separation principle and auxiliary model method. The proposed algorithms can give highly accurate parameter estimates. The simulation results show the effectiveness of the proposed algorithms.