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Model-Free Predictive Current Control Method for High-Speed Switched Reluctance Generator.

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Title: Model-Free Predictive Current Control Method for High-Speed Switched Reluctance Generator.
Authors: Li, Zixin1,2 (AUTHOR), Wang, Shuanghong1,2 (AUTHOR) wshfj@mail.hust.edu.cn, Zhou, Libing1,2 (AUTHOR)
Source: Energies (19961073). Oct2025, Vol. 18 Issue 20, p5501. 21p.
Subjects: Predictive control systems, Electric generators, Adaptive control systems, Current fluctuations, Observability (Control theory), Statistical models
Abstract: To address the issues of excessive current ripple and poor dynamic response in conventional angle position control (APC) for high-speed switched reluctance generator (SRG), this paper proposes an online parameter identification-based model-free predictive control (MFPC) strategy. First, the system dynamics are represented as an ultra-local model (ULM), enabling the design of an extended state observer (ESO) for two-step current prediction to compensate for control delays. Second, an improved Recursive Least Squares (RLS) algorithm with covariance resetting and error clearance is implemented to accurately identify dynamic inductance online, thereby enhancing the prediction accuracy of the ESO. Third, a bus current estimation-based adaptive feedforward compensation (AFC) technique is introduced to accelerate DC-bus voltage regulation and system dynamic response. Finally, simulations conducted on a 250 kW SRG platform demonstrate that the proposed method achieves superior dynamic performance and significantly reduced current ripple compared to conventional APC method. [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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DbLabel: Engineering Source
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  Data: Model-Free Predictive Current Control Method for High-Speed Switched Reluctance Generator.
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  Data: <searchLink fieldCode="AR" term="%22Li%2C+Zixin%22">Li, Zixin</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wang%2C+Shuanghong%22">Wang, Shuanghong</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<i> wshfj@mail.hust.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Zhou%2C+Libing%22">Zhou, Libing</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Energies+%2819961073%29%22">Energies (19961073)</searchLink>. Oct2025, Vol. 18 Issue 20, p5501. 21p.
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  Data: <searchLink fieldCode="DE" term="%22Predictive+control+systems%22">Predictive control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Electric+generators%22">Electric generators</searchLink><br /><searchLink fieldCode="DE" term="%22Adaptive+control+systems%22">Adaptive control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Current+fluctuations%22">Current fluctuations</searchLink><br /><searchLink fieldCode="DE" term="%22Observability+%28Control+theory%29%22">Observability (Control theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Statistical+models%22">Statistical models</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: To address the issues of excessive current ripple and poor dynamic response in conventional angle position control (APC) for high-speed switched reluctance generator (SRG), this paper proposes an online parameter identification-based model-free predictive control (MFPC) strategy. First, the system dynamics are represented as an ultra-local model (ULM), enabling the design of an extended state observer (ESO) for two-step current prediction to compensate for control delays. Second, an improved Recursive Least Squares (RLS) algorithm with covariance resetting and error clearance is implemented to accurately identify dynamic inductance online, thereby enhancing the prediction accuracy of the ESO. Third, a bus current estimation-based adaptive feedforward compensation (AFC) technique is introduced to accelerate DC-bus voltage regulation and system dynamic response. Finally, simulations conducted on a 250 kW SRG platform demonstrate that the proposed method achieves superior dynamic performance and significantly reduced current ripple compared to conventional APC method. [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/en18205501
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      – Code: eng
        Text: English
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        PageCount: 21
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        Type: general
      – SubjectFull: Electric generators
        Type: general
      – SubjectFull: Adaptive control systems
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      – SubjectFull: Current fluctuations
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      – SubjectFull: Observability (Control theory)
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      – SubjectFull: Statistical models
        Type: general
    Titles:
      – TitleFull: Model-Free Predictive Current Control Method for High-Speed Switched Reluctance Generator.
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            NameFull: Li, Zixin
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            NameFull: Wang, Shuanghong
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            NameFull: Zhou, Libing
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            – D: 15
              M: 10
              Text: Oct2025
              Type: published
              Y: 2025
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            – TitleFull: Energies (19961073)
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