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Comments on "Neural network‐based continuous finite‐time tracking control for uncertain robotic systems with actuator saturation".

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Title: Comments on "Neural network‐based continuous finite‐time tracking control for uncertain robotic systems with actuator saturation".
Authors: Su, Yuxin1 (AUTHOR) yxsu@mail.xidian.edu.cn
Source: Asian Journal of Control. May2026, Vol. 28 Issue 3, p1597-1599. 3p.
Subjects: Robot control systems, Tracking control systems, Artificial neural networks, Control theory (Engineering)
Abstract: This brief paper points out a serious flaw in the proofs of Theorems 1 and 2 of [Neural network‐based continuous finite‐time tracking control for uncertain robotic systems with actuator saturation, Asian J. Control 24 (2022), 3475–3493], making the proposed controllers therein untenable. It also points out several flaws in the proposed approach of the above paper and presents the corrections. [ABSTRACT FROM AUTHOR]
Copyright of Asian Journal of Control 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.)
Database: Engineering Source
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Header DbId: egs
DbLabel: Engineering Source
An: 193710614
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PubType: Academic Journal
PubTypeId: academicJournal
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  Data: Comments on "Neural network‐based continuous finite‐time tracking control for uncertain robotic systems with actuator saturation".
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  Data: <searchLink fieldCode="AR" term="%22Su%2C+Yuxin%22">Su, Yuxin</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> yxsu@mail.xidian.edu.cn</i>
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  Data: <searchLink fieldCode="JN" term="%22Asian+Journal+of+Control%22">Asian Journal of Control</searchLink>. May2026, Vol. 28 Issue 3, p1597-1599. 3p.
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  Data: <searchLink fieldCode="DE" term="%22Robot+control+systems%22">Robot control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Tracking+control+systems%22">Tracking control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Control+theory+%28Engineering%29%22">Control theory (Engineering)</searchLink>
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  Data: This brief paper points out a serious flaw in the proofs of Theorems 1 and 2 of [Neural network‐based continuous finite‐time tracking control for uncertain robotic systems with actuator saturation, Asian J. Control 24 (2022), 3475–3493], making the proposed controllers therein untenable. It also points out several flaws in the proposed approach of the above paper and presents the corrections. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Asian Journal of Control 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: 10.1002/asjc.3714
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      – Code: eng
        Text: English
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        PageCount: 3
        StartPage: 1597
    Subjects:
      – SubjectFull: Robot control systems
        Type: general
      – SubjectFull: Tracking control systems
        Type: general
      – SubjectFull: Artificial neural networks
        Type: general
      – SubjectFull: Control theory (Engineering)
        Type: general
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      – TitleFull: Comments on "Neural network‐based continuous finite‐time tracking control for uncertain robotic systems with actuator saturation".
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            NameFull: Su, Yuxin
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            – D: 01
              M: 05
              Text: May2026
              Type: published
              Y: 2026
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              Value: 28
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