Model-Free Predictive Sliding Mode Control for PMSM Drives Using Ultra-Local Method

Yao Wei, Dongliang Ke, Fengxiang Wang, Marcelo Lobo Heldwein

Publikation: Beitrag in Buch/Bericht/KonferenzbandKonferenzbeitragBegutachtung

4 Zitate (Scopus)

Abstract

Since some physical parameters of the motor are time-varying, the realized control performances are inevitably affected by the parameter mismatches in the sliding mode control (SM C). To fully eliminate the influences caused by the parameter mismatches and enhance the robustness of the conventional SMC, an ultra-local-based model-free predictive SMC is proposed in this paper, and used as the current controller in the permanent magnet synchronous motor (PMSM) driving system. A priori model is replaced by the ultra-local, in which physical parameters of the plant are not required anymore. The unknown terms of the plant are summarized as a single variable and online estimated by an extended state observer (ESO) to maintain a well model accuracy. The effectiveness and correctness are demonstrated by the simulation and experimental results, as well as the advantage of current quality and speed integral of time and absolute error (ITAE) with suitable robustness.

OriginalspracheEnglisch
TitelIECON 2023 - 49th Annual Conference of the IEEE Industrial Electronics Society
Herausgeber (Verlag)IEEE Computer Society
ISBN (elektronisch)9798350331820
DOIs
PublikationsstatusVeröffentlicht - 2023
Veranstaltung49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023 - Singapore, Singapur
Dauer: 16 Okt. 202319 Okt. 2023

Publikationsreihe

NameIECON Proceedings (Industrial Electronics Conference)
ISSN (Print)2162-4704
ISSN (elektronisch)2577-1647

Konferenz

Konferenz49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023
Land/GebietSingapur
OrtSingapore
Zeitraum16/10/2319/10/23

Fingerprint

Untersuchen Sie die Forschungsthemen von „Model-Free Predictive Sliding Mode Control for PMSM Drives Using Ultra-Local Method“. Zusammen bilden sie einen einzigartigen Fingerprint.

Dieses zitieren