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Fuzzy Logic Driven Self‐Tuned PI Controller for Enhanced Speed Regulation of PMSM Drives.

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Title: Fuzzy Logic Driven Self‐Tuned PI Controller for Enhanced Speed Regulation of PMSM Drives.
Authors: Ebrahim, Endris Hassen1 (AUTHOR), Kour, Gurpreet2 (AUTHOR), Khera, Preeti3 (AUTHOR), Kumar, Ashok4 (AUTHOR), Kapila, Rajat1 (AUTHOR) rajatkapila@su.edu.et, Mishra, Pramita (AUTHOR) pmishra@wiley.com
Source: Journal of Electrical & Computer Engineering. 7/30/2026, Vol. 2026, p1-19. 19p.
Subjects: Fuzzy logic, PID controllers, Dynamic models, MatLab (Computer software), Feedback control systems, Adaptive control systems, Permanent magnet motors, Pole assignment
Abstract: In permanent magnet synchronous motor (PMSM), proportional–integral (PI) controllers are used to control speed and modern‐day regulation. However, PI controllers are challenged due to existing speed variations, load turmoil, parameter changes, and manual control. A controller method using fuzzy logic for a PMSM is required that could dynamically adjust the PI controller gains based on real‐time motor performance and error conditions. Therefore, the carried research work proposed a design to automate PI controllers for dynamic modeling of motors by using the fuzzy logic controller (FLC) method with 49 rules. Furthermore, its gain is adjusted online using the pole assignment method. Dynamic modeling and characteristics of the PMSM drive are based on the d‐q reference coordinate transformation system. Using various external loads and MATLAB simulation conditions, it has been examined that the proposed controller is efficient not only for speed changes but also for rapid recovery from abrupt load torque. The simulation outcomes showed that fuzzy logic primarily based on self‐tuning PI controllers has improved outcomes such as minimum settling time, fast rise time, minimum overshoot, and reduced steady‐state error. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Electrical & Computer Engineering is the property of Wiley-Blackwell 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: Fuzzy Logic Driven Self‐Tuned PI Controller for Enhanced Speed Regulation of PMSM Drives.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Electrical+%26+Computer+Engineering%22">Journal of Electrical & Computer Engineering</searchLink>. 7/30/2026, Vol. 2026, p1-19. 19p.
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  Data: <searchLink fieldCode="DE" term="%22Fuzzy+logic%22">Fuzzy logic</searchLink><br /><searchLink fieldCode="DE" term="%22PID+controllers%22">PID controllers</searchLink><br /><searchLink fieldCode="DE" term="%22Dynamic+models%22">Dynamic models</searchLink><br /><searchLink fieldCode="DE" term="%22MatLab+%28Computer+software%29%22">MatLab (Computer software)</searchLink><br /><searchLink fieldCode="DE" term="%22Feedback+control+systems%22">Feedback control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+control+systems%22">Adaptive control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Permanent+magnet+motors%22">Permanent magnet motors</searchLink><br /><searchLink fieldCode="DE" term="%22Pole+assignment%22">Pole assignment</searchLink>
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  Data: In permanent magnet synchronous motor (PMSM), proportional–integral (PI) controllers are used to control speed and modern‐day regulation. However, PI controllers are challenged due to existing speed variations, load turmoil, parameter changes, and manual control. A controller method using fuzzy logic for a PMSM is required that could dynamically adjust the PI controller gains based on real‐time motor performance and error conditions. Therefore, the carried research work proposed a design to automate PI controllers for dynamic modeling of motors by using the fuzzy logic controller (FLC) method with 49 rules. Furthermore, its gain is adjusted online using the pole assignment method. Dynamic modeling and characteristics of the PMSM drive are based on the d‐q reference coordinate transformation system. Using various external loads and MATLAB simulation conditions, it has been examined that the proposed controller is efficient not only for speed changes but also for rapid recovery from abrupt load torque. The simulation outcomes showed that fuzzy logic primarily based on self‐tuning PI controllers has improved outcomes such as minimum settling time, fast rise time, minimum overshoot, and reduced steady‐state error. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Journal of Electrical & Computer Engineering is the property of Wiley-Blackwell 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: 10.1155/jece/7690514
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      – Code: eng
        Text: English
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      – SubjectFull: Fuzzy logic
        Type: general
      – SubjectFull: PID controllers
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      – SubjectFull: Dynamic models
        Type: general
      – SubjectFull: MatLab (Computer software)
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      – SubjectFull: Feedback control systems
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      – SubjectFull: Adaptive control systems
        Type: general
      – SubjectFull: Permanent magnet motors
        Type: general
      – SubjectFull: Pole assignment
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    Titles:
      – TitleFull: Fuzzy Logic Driven Self‐Tuned PI Controller for Enhanced Speed Regulation of PMSM Drives.
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            NameFull: Ebrahim, Endris Hassen
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            NameFull: Khera, Preeti
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            NameFull: Kumar, Ashok
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              M: 07
              Text: 7/30/2026
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              Y: 2026
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