Comparison of stochastic and deterministic parameter identification algorithms for indirect vector control

S. Wade, M. W. Dunnigan, B. W. Williams

Research output: Contribution to journalArticle

Abstract

A stochastic and a deterministic state-space estimator for the indirect vector control are compared using experimental results, as regards their estimate of the rotor resistance. Simulation results are used to compare stationary and synchronous reference frame versions of the extended Kalman filter (EKF). Induction machine core losses are usually neglected due to the required increase in model complexity. However, a standard method of core loss compensation which does not require higher order estimators is shown to improve the EKF and extended Leunberger observer (ELO) accuracy, while requiring only a minimal increase in computation. The experimental system used to implement vector control and on-line rotor resistance estimation, using a high performance digital signal processor, is described.

Original languageEnglish
Pages (from-to)2/1-2/5
JournalIEE Colloquium (Digest)
Issue number181
Publication statusPublished - 1 Jan 1995
EventIEE Colloquium on Vector Control and Direct Torque Control of Induction Motors - London, UK
Duration: 27 Oct 199527 Oct 1995

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Extended Kalman filters
Identification (control systems)
Rotors
Digital signal processors
Compensation and Redress

Cite this

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Comparison of stochastic and deterministic parameter identification algorithms for indirect vector control. / Wade, S.; Dunnigan, M. W.; Williams, B. W.

In: IEE Colloquium (Digest), No. 181, 01.01.1995, p. 2/1-2/5.

Research output: Contribution to journalArticle

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