Gradient-based iterative parameter estimation for Box-Jenkins systems

Authors:
Dongqing Wang;Guowei Yang;Ruifeng 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 presents a gradient-based iterative identification algorithms for Box-Jenkins systems with finite measurement input/output data. Compared with the pseudo-linear regression stochastic gradient approach, the proposed algorithm updates the parameter estimation using all the available data at each iterative computation (at each iteration), and thus can produce highly accurate parameter estimation. An example is given.