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A Novel Filtering Observer: A Cost-Effective Estimation Solution for Industrial PMSM Drives Using in-Motion Control Systems

Author

Listed:
  • Cagatay Dursun

    (Research and Development Department, Akim Metal Industry and Trade Inc., Istanbul 34953, Turkey)

  • Selin Ozcira Ozkilic

    (Department of Electrical Engineering, Yildiz Technical University, Istanbul 34220, Turkey)

Abstract

This paper presents a cost-efficient estimation method, the filtering observer (FOBS), which provides a smooth estimation through prior estimation, enhancing the field-oriented control (FOC) performance of motion control systems by estimating the angular rotor position, angular rotor velocity, and disturbance torque of permanent magnet synchronous motors (PMSMs). The cost-effective FOBS demonstrates characteristics akin to optimal estimating methods and employs arbitrary pole placement, facilitating more straightforward adjustment of the FOBS gain. The non-linear characteristics of low-resolution and low-cost encoders, the computation of angular rotor velocity using traditional techniques, and disturbances over broad frequency ranges in the servo drive system impair the efficacy of the motion control system. As a cost-effective solution, the FOBS minimizes the deficiencies of the low-cost encoder, reduces oscillations and measurement delays in the speed feedback signal, and provides smooth estimation of disturbance torque. Based on the results from experiments, the FOBS was compared against traditional approaches and the performance of the motion control system was examined. Also, the performance of the motion control system was investigated. The results indicate that these enhancements were achieved with low processing power and an easily implementable estimate technique suitable for low-cost industrial systems.

Suggested Citation

  • Cagatay Dursun & Selin Ozcira Ozkilic, 2025. "A Novel Filtering Observer: A Cost-Effective Estimation Solution for Industrial PMSM Drives Using in-Motion Control Systems," Energies, MDPI, vol. 18(4), pages 1-21, February.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:4:p:883-:d:1589858
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    References listed on IDEAS

    as
    1. Dongri Shan & Di Wang & Dongmei He & Peng Zhang, 2024. "Position Sensorless Vector Control System for Lawnmower Permanent Magnet Synchronous Motor Based on Extended Kalman Filter," Energies, MDPI, vol. 17(5), pages 1-23, March.
    2. Mengji Zhao & Quntao An & Changqing Chen & Fuqiang Cao & Siwen Li, 2022. "Observer Based Improved Position Estimation in Field-Oriented Controlled PMSM with Misplaced Hall-Effect Sensors," Energies, MDPI, vol. 15(16), pages 1-14, August.
    3. Dongyang Li & Shuo Wang & Chunyang Gu & Yuli Bao & Xiaochen Zhang & Chris Gerada & He Zhang, 2024. "An Anti-Disturbance Extended State Observer-Based Control of a PMa-SynRM for Fast Dynamic Response," Energies, MDPI, vol. 17(17), pages 1-24, August.
    4. Bo Xu & Fangqiang Mu & Guoding Shi & Wei Ji & Huangqiu Zhu, 2016. "State Estimation of Permanent Magnet Synchronous Motor Using Improved Square Root UKF," Energies, MDPI, vol. 9(7), pages 1-14, June.
    5. Omar Aguilar-Mejia & Antonio Valderrabano-Gonzalez & Norberto Hernández-Romero & Juan Carlos Seck-Tuoh-Mora & Julio Cesar Hernandez-Ochoa & Hertwin Minor-Popocatl, 2024. "A Neuroadaptive Position-Sensorless Robust Control for Permanent Magnet Synchronous Motor Drive System with Uncertain Disturbance," Energies, MDPI, vol. 17(21), pages 1-17, November.
    6. Ravi Gandhi & Dipak Adhyaru & Gulshan Sharma & Pitshou N. Bokoro, 2023. "Dual-Extended State Observer-Based Feedback Linearizing Control for a Nonlinear System with Mismatched Disturbances and Uncertainties," Energies, MDPI, vol. 16(7), pages 1-21, March.
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