An enhanced deadbeat predictive current control of SPMSM with linear disturbance observer

Deadbeat predictive current control (DPCC) with a linear disturbance observer (LDO) in the surface-mounted permanent magnet synchronous machine (SPMSM) has been widely applied in many applications due to better dynamic response performance and easy implementation. However, the evaluated lumped distu...

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Main Authors: Yuan, Xin, Xie, Shuangchun, Chen, Jiahao, Zhang, Shuo, Zhang, Chengning, Lee, Christopher Ho Tin
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2023
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Online Access:https://hdl.handle.net/10356/166304
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Institution: Nanyang Technological University
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spelling sg-ntu-dr.10356-1663042023-04-21T15:45:39Z An enhanced deadbeat predictive current control of SPMSM with linear disturbance observer Yuan, Xin Xie, Shuangchun Chen, Jiahao Zhang, Shuo Zhang, Chengning Lee, Christopher Ho Tin School of Electrical and Electronic Engineering Engineering::Electrical and electronic engineering Inverter Nonlinearity Linear Disturbance Observer Deadbeat predictive current control (DPCC) with a linear disturbance observer (LDO) in the surface-mounted permanent magnet synchronous machine (SPMSM) has been widely applied in many applications due to better dynamic response performance and easy implementation. However, the evaluated lumped disturbances caused by current measurement noises, inverter nonlinearity, abrupt reference current, and initial inductance parameter mismatch can restrain the high-performance development. In order to handle this issue, an enhanced DPCC with LDO is proposed in this article, where a modified DPCC with the LDO model and the noninvasive inductance and inverter disturbance observer are developed. In this case, the initial inductance parameter mismatch and high-frequency disturbances effect on the DPCC with LDO is reduced, while the current measurement noises' suppression is enhanced by the proposed LDO. The theoretical analysis has shown that the proposed DPCC with LDO has a better performance than the conventional DPCC with LDO. Also, the superiority of the proposed DPCC with LDO has been validated by an SPMSM drive test rig. National Research Foundation (NRF) Submitted/Accepted version This work was supported by the National Research Foundation (NRF), Singapore, through its NRF Fellowship, under Grant NRF-NRFF12-2020-0003. 2023-04-21T05:06:37Z 2023-04-21T05:06:37Z 2022 Journal Article Yuan, X., Xie, S., Chen, J., Zhang, S., Zhang, C. & Lee, C. H. T. (2022). An enhanced deadbeat predictive current control of SPMSM with linear disturbance observer. IEEE Journal of Emerging and Selected Topics in Power Electronics, 10(5), 6304-6316. https://dx.doi.org/10.1109/JESTPE.2022.3168435 2168-6777 https://hdl.handle.net/10356/166304 10.1109/JESTPE.2022.3168435 2-s2.0-85128597615 5 10 6304 6316 en NRF-NRFF12-2020-0003 IEEE Journal of Emerging and Selected Topics in Power Electronics © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/JESTPE.2022.3168435. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Electrical and electronic engineering
Inverter Nonlinearity
Linear Disturbance Observer
spellingShingle Engineering::Electrical and electronic engineering
Inverter Nonlinearity
Linear Disturbance Observer
Yuan, Xin
Xie, Shuangchun
Chen, Jiahao
Zhang, Shuo
Zhang, Chengning
Lee, Christopher Ho Tin
An enhanced deadbeat predictive current control of SPMSM with linear disturbance observer
description Deadbeat predictive current control (DPCC) with a linear disturbance observer (LDO) in the surface-mounted permanent magnet synchronous machine (SPMSM) has been widely applied in many applications due to better dynamic response performance and easy implementation. However, the evaluated lumped disturbances caused by current measurement noises, inverter nonlinearity, abrupt reference current, and initial inductance parameter mismatch can restrain the high-performance development. In order to handle this issue, an enhanced DPCC with LDO is proposed in this article, where a modified DPCC with the LDO model and the noninvasive inductance and inverter disturbance observer are developed. In this case, the initial inductance parameter mismatch and high-frequency disturbances effect on the DPCC with LDO is reduced, while the current measurement noises' suppression is enhanced by the proposed LDO. The theoretical analysis has shown that the proposed DPCC with LDO has a better performance than the conventional DPCC with LDO. Also, the superiority of the proposed DPCC with LDO has been validated by an SPMSM drive test rig.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Yuan, Xin
Xie, Shuangchun
Chen, Jiahao
Zhang, Shuo
Zhang, Chengning
Lee, Christopher Ho Tin
format Article
author Yuan, Xin
Xie, Shuangchun
Chen, Jiahao
Zhang, Shuo
Zhang, Chengning
Lee, Christopher Ho Tin
author_sort Yuan, Xin
title An enhanced deadbeat predictive current control of SPMSM with linear disturbance observer
title_short An enhanced deadbeat predictive current control of SPMSM with linear disturbance observer
title_full An enhanced deadbeat predictive current control of SPMSM with linear disturbance observer
title_fullStr An enhanced deadbeat predictive current control of SPMSM with linear disturbance observer
title_full_unstemmed An enhanced deadbeat predictive current control of SPMSM with linear disturbance observer
title_sort enhanced deadbeat predictive current control of spmsm with linear disturbance observer
publishDate 2023
url https://hdl.handle.net/10356/166304
_version_ 1764208120964317184