Least-squares identification of dynamic systems in closed loop

Research output: Contribution to journalConference articlepeer-review

2 Citations (Scopus)

Abstract

The bias-eliminated least-squares (BELS) methods have been recently proposed as the indirect approach to perform unbiased parameter estimation of closed-loop systems subject to colored noise. This paper introduces a direct approach version of the BELS algorithm for identification of dynamic systems with an ARMAX model structure operating under linear feedback. Built upon linear regression and with no need to estimate parameters of the noise model, the developed algorithm is very attractive computationally while being able to yield open-loop plant parameter estimates with good accuracy. The performance of the developed BELS algorithm is corroborated with simulation results.

Original languageEnglish
Pages (from-to)1139-1140
Number of pages2
JournalProceedings of the IEEE Conference on Decision and Control
Volume2
Publication statusPublished - 2000
Event39th IEEE Confernce on Decision and Control - Sydney, NSW, Australia
Duration: 12 Dec 200015 Dec 2000

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