Gradient based and least-squares based iterative identification methods for OE and OEMA systems

Authors:
Feng Ding;Peter X. Liu;Guangjun Liu
Affiliations:
School of Communication and Control Engineering, Jiangnan University, Wuxi 214122, PR China;Department of Systems and Computer Engineering, Carleton University, Ottawa, Canada K1S 5B6;Department of Aerospace Engineering, Ryerson University, Toronto, Canada M5B 2K3
Venue:
Digital Signal Processing
Year:
2010

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Abstract

Gradient based and least-squares based iterative identification algorithms are developed for output error (OE) and output error moving average (OEMA) systems. Compared with recursive approaches, the proposed iterative algorithms use all the measured input-output data at each iterative computation (at each iteration), and thus can produce highly accurate parameter estimation. The basic idea of the iterative methods is to adopt the interactive estimation theory: the parameter estimates relying on unknown variables are computed by using the estimates of these unknown variables which are obtained from the preceding parameter estimates. The simulation results confirm theoretical findings.