Simplified Hybrid Adaptive Kalman Filter With Fading-Triggered Resonance Mechanism for PMSM Speed-Sensorless Control

Wenjie Li; Yongting Deng; Jia Fu; Haiyang Cao; Yuxin Kang; Chuanlong Zhai; Xiufeng Liu; Gaolin Wang

doi:10.1109/TCSII.2025.3612703

Simplified Hybrid Adaptive Kalman Filter With Fading-Triggered Resonance Mechanism for PMSM Speed-Sensorless Control

Wenjie Li
, Yongting Deng^*
, Jia Fu
, Haiyang Cao
, Yuxin Kang
, Chuanlong Zhai
, Xiufeng Liu
, Gaolin Wang

^*Corresponding author for this work

CAS - Changchun Institute of Optics Fine Mechanics and Physics
University of Chinese Academy of Sciences
CAS - Ningbo Institute of Material Technology and Engineering
School of Electrical Engineering and Automation, Harbin Institute of Technology

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

To enhance the position estimation accuracy of permanent magnet synchronous motor (PMSM) speed-sensorless control, a simplified hybrid adaptive kalman filter (SHAKF) with fading-triggered resonance (FTR) is proposed in this brief. By simplifying the iterative calculation of forgetting factor and noise covariance matrix, the computational burden is effectively reduced. Through the FTR mechanism, the steady-state error compensation without compromising stability is achieved. The stability and convergence are rigorously analyzed. Finally, the experimental results validate the superiority of the proposed sensorless control strategy in steady-state accuracy, dynamic speed response, and computational efficiency.

Original language	English
Pages (from-to)	1740-1744
Number of pages	5
Journal	IEEE Transactions on Circuits and Systems II: Express Briefs
Volume	72
Issue number	11
DOIs	https://doi.org/10.1109/TCSII.2025.3612703
State	Published - 2025
Externally published	Yes

Keywords

Hybrid adaptive Kalman filter
permanent magnet synchronous motor
sensorless control
triggered resonance

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10.1109/TCSII.2025.3612703

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@article{a40393f9c3914b908dc59657c9af2ff9,

title = "Simplified Hybrid Adaptive Kalman Filter With Fading-Triggered Resonance Mechanism for PMSM Speed-Sensorless Control",

abstract = "To enhance the position estimation accuracy of permanent magnet synchronous motor (PMSM) speed-sensorless control, a simplified hybrid adaptive kalman filter (SHAKF) with fading-triggered resonance (FTR) is proposed in this brief. By simplifying the iterative calculation of forgetting factor and noise covariance matrix, the computational burden is effectively reduced. Through the FTR mechanism, the steady-state error compensation without compromising stability is achieved. The stability and convergence are rigorously analyzed. Finally, the experimental results validate the superiority of the proposed sensorless control strategy in steady-state accuracy, dynamic speed response, and computational efficiency.",

keywords = "Hybrid adaptive Kalman filter, permanent magnet synchronous motor, sensorless control, triggered resonance",

author = "Wenjie Li and Yongting Deng and Jia Fu and Haiyang Cao and Yuxin Kang and Chuanlong Zhai and Xiufeng Liu and Gaolin Wang",

note = "Publisher Copyright: {\textcopyright} 2004-2012 IEEE.",

year = "2025",

doi = "10.1109/TCSII.2025.3612703",

language = "英语",

volume = "72",

pages = "1740--1744",

journal = "IEEE Transactions on Circuits and Systems II: Express Briefs",

issn = "1549-7747",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "11",

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TY - JOUR

T1 - Simplified Hybrid Adaptive Kalman Filter With Fading-Triggered Resonance Mechanism for PMSM Speed-Sensorless Control

AU - Li, Wenjie

AU - Deng, Yongting

AU - Fu, Jia

AU - Cao, Haiyang

AU - Kang, Yuxin

AU - Zhai, Chuanlong

AU - Liu, Xiufeng

AU - Wang, Gaolin

PY - 2025

Y1 - 2025

N2 - To enhance the position estimation accuracy of permanent magnet synchronous motor (PMSM) speed-sensorless control, a simplified hybrid adaptive kalman filter (SHAKF) with fading-triggered resonance (FTR) is proposed in this brief. By simplifying the iterative calculation of forgetting factor and noise covariance matrix, the computational burden is effectively reduced. Through the FTR mechanism, the steady-state error compensation without compromising stability is achieved. The stability and convergence are rigorously analyzed. Finally, the experimental results validate the superiority of the proposed sensorless control strategy in steady-state accuracy, dynamic speed response, and computational efficiency.

AB - To enhance the position estimation accuracy of permanent magnet synchronous motor (PMSM) speed-sensorless control, a simplified hybrid adaptive kalman filter (SHAKF) with fading-triggered resonance (FTR) is proposed in this brief. By simplifying the iterative calculation of forgetting factor and noise covariance matrix, the computational burden is effectively reduced. Through the FTR mechanism, the steady-state error compensation without compromising stability is achieved. The stability and convergence are rigorously analyzed. Finally, the experimental results validate the superiority of the proposed sensorless control strategy in steady-state accuracy, dynamic speed response, and computational efficiency.

KW - Hybrid adaptive Kalman filter

KW - permanent magnet synchronous motor

KW - sensorless control

KW - triggered resonance

UR - https://www.scopus.com/pages/publications/105017436772

U2 - 10.1109/TCSII.2025.3612703

DO - 10.1109/TCSII.2025.3612703

M3 - 文章

AN - SCOPUS:105017436772

SN - 1549-7747

VL - 72

SP - 1740

EP - 1744

JO - IEEE Transactions on Circuits and Systems II: Express Briefs

JF - IEEE Transactions on Circuits and Systems II: Express Briefs

IS - 11

ER -

Simplified Hybrid Adaptive Kalman Filter With Fading-Triggered Resonance Mechanism for PMSM Speed-Sensorless Control

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