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

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Title: A Novel Filtering Observer: A Cost-Effective Estimation Solution for Industrial PMSM Drives Using in-Motion Control Systems.
Authors: Dursun, Cagatay1 (AUTHOR) cdursun@akimmetal.com.tr, Ozcira Ozkilic, Selin2 (AUTHOR)
Source: Energies (19961073). Feb2025, Vol. 18 Issue 4, p883. 21p.
Subjects: Pole assignment, Permanent magnet motors, Angular velocity, Industrialism, Kalman filtering
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. [ABSTRACT FROM AUTHOR]
Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: A Novel Filtering Observer: A Cost-Effective Estimation Solution for Industrial PMSM Drives Using in-Motion Control Systems.
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  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Feb2025, Vol. 18 Issue 4, p883. 21p.
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  Data: <searchLink fieldCode="DE" term="%22Pole+assignment%22">Pole assignment</searchLink><br /><searchLink fieldCode="DE" term="%22Permanent+magnet+motors%22">Permanent magnet motors</searchLink><br /><searchLink fieldCode="DE" term="%22Angular+velocity%22">Angular velocity</searchLink><br /><searchLink fieldCode="DE" term="%22Industrialism%22">Industrialism</searchLink><br /><searchLink fieldCode="DE" term="%22Kalman+filtering%22">Kalman filtering</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Energies (19961073) is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.3390/en18040883
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      – Code: eng
        Text: English
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        PageCount: 21
        StartPage: 883
    Subjects:
      – SubjectFull: Pole assignment
        Type: general
      – SubjectFull: Permanent magnet motors
        Type: general
      – SubjectFull: Angular velocity
        Type: general
      – SubjectFull: Industrialism
        Type: general
      – SubjectFull: Kalman filtering
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      – TitleFull: A Novel Filtering Observer: A Cost-Effective Estimation Solution for Industrial PMSM Drives Using in-Motion Control Systems.
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            – D: 15
              M: 02
              Text: Feb2025
              Type: published
              Y: 2025
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