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author:

Wu, Zehong (Wu, Zehong.) [1] | Zhang, Jiayang (Zhang, Jiayang.) [2] | Zhou, Sheng (Zhou, Sheng.) [3] | Lin, Yunzhi (Lin, Yunzhi.) [4] | Jin, Tao (Jin, Tao.) [5]

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Abstract:

To address the challenges of single current sensor (SCS) control in Permanent Magnet Synchronous Motor (PMSM) drives, this paper proposes a novel discrete-time current state observer control method. Traditional discretization techniques, such as Euler's and Tustin's methods, are widely used in observer-based control but have notable limitations: Euler's method introduces significant discretization errors and potential instability, while the Tustin method improves numerical stability at the cost of increased computational complexity, placing higher demands on processing resources. To overcome these issues, this paper first analyzes the performance of state observers based on these conventional methods and a fourth-order Runge-Kutta hybrid discretization approach. Then, a new discretization scheme is introduced, leading to the development of a discrete-time adaptive observer, which significantly enhances discretization accuracy while ensuring computational efficiency. To validate the effectiveness of the proposed approach, extensive simulation experiments are conducted in MATLAB/SIMULINK under various operating conditions. The results demonstrate that the proposed observer improves current reconstruction accuracy, enhances system stability, and ensures reliable PMSM operation, making it a cost-effective and computationally efficient solution for SCS-based motor drives. © 2025 IEEE.

Keyword:

Computational efficiency Cost effectiveness Discrete time control systems Electric drives Electric motors Finite difference method MATLAB Numerical methods Power electronics System stability

Community:

  • [ 1 ] [Wu, Zehong]Fuzhou University, College of Electrical Engineering and Automation, Fuzhou, China
  • [ 2 ] [Zhang, Jiayang]Fuzhou University, College of Electrical Engineering and Automation, Fuzhou, China
  • [ 3 ] [Zhou, Sheng]Fuzhou University, College of Electrical Engineering and Automation, Fuzhou, China
  • [ 4 ] [Lin, Yunzhi]China Railway Electification Engineering Group Co. Ltd., Beijing, China
  • [ 5 ] [Jin, Tao]Fuzhou University, College of Electrical Engineering and Automation, Fuzhou, China

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Year: 2025

Page: 1-6

Language: English

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 5

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