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Disturbance‐Observer‐Based Tube Model Predictive Control for Constrained Systems.

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Title: Disturbance‐Observer‐Based Tube Model Predictive Control for Constrained Systems.
Authors: Jiang, Yonghua1,2 (AUTHOR), Xu, Jiali3 (AUTHOR), Liu, Siyu1,3,4 (AUTHOR) siyu.liu@zjnu.edu.cn, Pan, Zhichao5 (AUTHOR), Jiang, Hongkui1 (AUTHOR) jhk@zjnu.cn, Tang, Chao1 (AUTHOR), Jiao, Weidong3 (AUTHOR)
Source: Optimal Control - Applications & Methods. May2026, Vol. 47 Issue 3, p735-747. 13p.
Subjects: Predictive control systems, Continuous time systems, Robust stability analysis, Observability (Control theory), Feedback control systems, Optimal control theory
Abstract: This paper proposes a disturbance‐observer‐based tube model predictive control (DTMPC) strategy to address the regulation problem of continuous‐time linear systems with additive bounded disturbances. The strategy integrates two elements: disturbance compensation and optimal control inputs. The former is designed using the estimation information from the disturbance observer to actively compensate for disturbances. The latter employs the estimation error bound to calculate the disturbance invariant set, which is then incorporated into the DTMPC design to determine the optimal control input. By compensating for the disturbances, the system's uncertainty and steady‐state error are minimized. As the estimation error bound decreases and stabilizes, the disturbance invariant set reduces, thereby expanding the feasible set of the nominal state. Finally, recursive feasibility and robust stability of the system are analyzed. The performance of the proposed DTMPC is verified by applying it to a self‐balancing vehicle system and comparing it with the TMPC. [ABSTRACT FROM AUTHOR]
Copyright of Optimal Control - Applications & Methods 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: Disturbance‐Observer‐Based Tube Model Predictive Control for Constrained Systems.
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  Data: <searchLink fieldCode="AR" term="%22Jiang%2C+Yonghua%22">Jiang, Yonghua</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Xu%2C+Jiali%22">Xu, Jiali</searchLink><relatesTo>3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Liu%2C+Siyu%22">Liu, Siyu</searchLink><relatesTo>1,3,4</relatesTo> (AUTHOR)<i> siyu.liu@zjnu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Pan%2C+Zhichao%22">Pan, Zhichao</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jiang%2C+Hongkui%22">Jiang, Hongkui</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> jhk@zjnu.cn</i><br /><searchLink fieldCode="AR" term="%22Tang%2C+Chao%22">Tang, Chao</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Jiao%2C+Weidong%22">Jiao, Weidong</searchLink><relatesTo>3</relatesTo> (AUTHOR)
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  Data: <searchLink fieldCode="JN" term="%22Optimal+Control+-+Applications+%26+Methods%22">Optimal Control - Applications & Methods</searchLink>. May2026, Vol. 47 Issue 3, p735-747. 13p.
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  Data: <searchLink fieldCode="DE" term="%22Predictive+control+systems%22">Predictive control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Continuous+time+systems%22">Continuous time systems</searchLink><br /><searchLink fieldCode="DE" term="%22Robust+stability+analysis%22">Robust stability analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Observability+%28Control+theory%29%22">Observability (Control theory)</searchLink><br /><searchLink fieldCode="DE" term="%22Feedback+control+systems%22">Feedback control systems</searchLink><br /><searchLink fieldCode="DE" term="%22Optimal+control+theory%22">Optimal control theory</searchLink>
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  Data: This paper proposes a disturbance‐observer‐based tube model predictive control (DTMPC) strategy to address the regulation problem of continuous‐time linear systems with additive bounded disturbances. The strategy integrates two elements: disturbance compensation and optimal control inputs. The former is designed using the estimation information from the disturbance observer to actively compensate for disturbances. The latter employs the estimation error bound to calculate the disturbance invariant set, which is then incorporated into the DTMPC design to determine the optimal control input. By compensating for the disturbances, the system's uncertainty and steady‐state error are minimized. As the estimation error bound decreases and stabilizes, the disturbance invariant set reduces, thereby expanding the feasible set of the nominal state. Finally, recursive feasibility and robust stability of the system are analyzed. The performance of the proposed DTMPC is verified by applying it to a self‐balancing vehicle system and comparing it with the TMPC. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Optimal Control - Applications & Methods 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/oca.70077
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        Text: English
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        PageCount: 13
        StartPage: 735
    Subjects:
      – SubjectFull: Predictive control systems
        Type: general
      – SubjectFull: Continuous time systems
        Type: general
      – SubjectFull: Robust stability analysis
        Type: general
      – SubjectFull: Observability (Control theory)
        Type: general
      – SubjectFull: Feedback control systems
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      – SubjectFull: Optimal control theory
        Type: general
    Titles:
      – TitleFull: Disturbance‐Observer‐Based Tube Model Predictive Control for Constrained Systems.
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            NameFull: Jiang, Yonghua
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            NameFull: Xu, Jiali
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            NameFull: Liu, Siyu
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            NameFull: Jiang, Hongkui
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            NameFull: Tang, Chao
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              M: 05
              Text: May2026
              Type: published
              Y: 2026
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              Value: 47
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