Hierarchical gradient based iterative parameter estimation algorithm for multivariable output error moving average systems

Authors:
Zhening Zhang;Feng Ding;Xinggao Liu
Affiliations:
Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of IoT Engineering, Jiangnan University, Wuxi214122, PR China;Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of IoT Engineering, Jiangnan University, Wuxi214122, PR China;State Key Laboratory of Industrial Control Technology, Department of Control Science and Engineering, Zhejiang University, Hangzhou310027, PR China
Venue:
Computers & Mathematics with Applications
Year:
2011

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Abstract

According to the hierarchical identification principle, a hierarchical gradient based iterative estimation algorithm is derived for multivariable output error moving average systems (i.e., multivariable OEMA-like models) which is different from multivariable CARMA-like models. As there exist unmeasurable noise-free outputs and unknown noise terms in the information vector/matrix of the corresponding identification model, this paper is, by means of the auxiliary model identification idea, to replace the unmeasurable variables in the information vector/matrix with the estimated residuals and the outputs of the auxiliary model. A numerical example is provided.