A high performance globally exponentially convergent sensorless observer for the IPMSM: Theoretical and experimental results

In a recent paper (Ortega et al., 2021) the authors proposed the first solution to the problem of designing a globally exponentially stable (GES) flux observer for the interior permanent magnet synchronous motor. However, the establishment of the stability proof relies on the assumption that the adaptation gain is sufficiently small —a condition that may degrade the quality of the transient behavior. In this paper we propose a new globally exponentially convergent flux observer that mitigates this limitation ensuring a high performance behavior under an operating constraint of motor currents. The design relies on the use of a novel theoretical tool—the generation of a “virtual” invariant manifold —that allows the use of the more advanced Kreisselmeier’s regression extension estimator, instead of a simple gradient descent one. We illustrate its superior transient behavior via extensive simulations and experiments.

Authors

Publication Details

Journal
Automatica
Published
2025-01-27
DOI
https://doi.org/10.1016/j.automatica.2025.112138
Citations
2
Primary Topic
Sensorless Control of Electric Motors
Type
article
Field-Weighted Citation Impact
1.46

Funders

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article

A high performance globally exponentially convergent sensorless observer for the IPMSM: Theoretical and experimental results

Roméo Ortega, Bowen Yi, Jong-Won Choi, Kwanghee Nam
2 citations
Automatica
Sensorless Control of Electric Motors
1.46
article

A high performance globally exponentially convergent sensorless observer for the IPMSM: Theoretical and experimental results

Roméo Ortega, Bowen Yi, Jong-Won Choi, Kwanghee Nam
article en
2 citations

Abstract

In a recent paper (Ortega et al., 2021) the authors proposed the first solution to the problem of designing a globally exponentially stable (GES) flux observer for the interior permanent magnet synchronous motor. However, the establishment of the stability proof relies on the assumption that the adaptation gain is sufficiently small —a condition that may degrade the quality of the transient behavior. In this paper we propose a new globally exponentially convergent flux observer that mitigates this limitation ensuring a high performance behavior under an operating constraint of motor currents. The design relies on the use of a novel theoretical tool—the generation of a “virtual” invariant manifold —that allows the use of the more advanced Kreisselmeier’s regression extension estimator, instead of a simple gradient descent one. We illustrate its superior transient behavior via extensive simulations and experiments.

AutomaticaVol. 174
Polytechnique Montréal, National Research Foundation of Korea, Natural Sciences and Engineering Research Council of Canada
Openalex Percentile: Top 20%
Sensorless Control of Electric Motors
1.46
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