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Extended State Observer Based Model Prediction Control for PMSM Field Weakening Control

Cheng, Zeyu; Yan, Yunda; Yang, Kaifeng; Li, Shihua; (2024) Extended State Observer Based Model Prediction Control for PMSM Field Weakening Control. In: Proceedings of the 36th Chinese Control and Decision Conference. (pp. pp. 4611-4616). IEEE (Institute of Electrical and Electronics Engineers): Xi'an, China. Green open access

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Abstract

This paper presents an extended state observer (ESO) based model predictive control (MPC) strategy for regulating the speed of permanent magnet synchronous motor (PMSM) during field weakening control, aiming to optimize the field weakening control performance in the presence of external disturbances and model uncertainty. An extended state observer is utilized to estimate disturbances caused by external disturbances and model parameter uncertainties, as well as nonlinear terms in the equations that are not easily handled. Through the incorporation of disturbance estimation and the anticipation of future disturbances within the prediction horizon, a predictive control law is derived by solving an optimization problem with constrains. Simulation results indicate that the proposed field weakening controller achieves better disturbance rejection, and solve the current and voltage constraints well.

Type: Proceedings paper
Title: Extended State Observer Based Model Prediction Control for PMSM Field Weakening Control
Event: 2024 36th Chinese Control and Decision Conference (CCDC)
Location: Xi'an, China
Dates: 25 Mar 2024 - 27 Mar 2024
ISBN-13: 979-8-3503-8778-0
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/CCDC62350.2024.10588121
Publisher version: https://doi.org/10.1109/CCDC62350.2024.10588121
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Uncertain systems, Uncertainty, Computational modeling, Simulation, Observers, Predictive models, Mathematical models
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10188759
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