Robust model predictive control for constrained linear system based on a sliding mode disturbance observer
Robust model predictive control for constrained linear system based on a sliding mode disturbance observer
For perturbed continuous-time systems, this paper proposes a robust model predictive control (RMPC) strategy for the regulation problem, exploiting a sliding mode disturbance observer. The main advantage is that it effectively enables the RMPC to be designed based on a model with reduced uncertainties. The proposed sliding mode observer (SMO) is finite-time convergent allowing the estimation error of the additive disturbance to be explicitly bounded by a predictable and decreasing limit. Due to the compensation of the estimated disturbance, the uncertainty that the RMPC has to handle is reduced from the original disturbance to the estimation error of the disturbance. This ensures all the admissible state trajectories are limited within a shrinking neighborhood of the origin and the steady-state error is therefore reduced. Simulation results show the effectiveness of the proposed method.
Disturbance observer, Linear systems, Robust model predictive control (RMPC), Sliding mode observer (SMO)
Zhang, Yao
a4f30318-ab42-4b38-a60d-f7199ff3a02a
Edwards, Christopher
e25335e9-57a8-4941-ab3d-04ffb36ffee5
Belmont, Mike
a29b6feb-1e0f-445c-be1a-cc3c5c09f9e0
Li, Guang
eb550424-a1ac-4ded-8128-ab184b551f88
August 2023
Zhang, Yao
a4f30318-ab42-4b38-a60d-f7199ff3a02a
Edwards, Christopher
e25335e9-57a8-4941-ab3d-04ffb36ffee5
Belmont, Mike
a29b6feb-1e0f-445c-be1a-cc3c5c09f9e0
Li, Guang
eb550424-a1ac-4ded-8128-ab184b551f88
Zhang, Yao, Edwards, Christopher, Belmont, Mike and Li, Guang
(2023)
Robust model predictive control for constrained linear system based on a sliding mode disturbance observer.
Automatica, 154, [111101].
(doi:10.1016/j.automatica.2023.111101).
Abstract
For perturbed continuous-time systems, this paper proposes a robust model predictive control (RMPC) strategy for the regulation problem, exploiting a sliding mode disturbance observer. The main advantage is that it effectively enables the RMPC to be designed based on a model with reduced uncertainties. The proposed sliding mode observer (SMO) is finite-time convergent allowing the estimation error of the additive disturbance to be explicitly bounded by a predictable and decreasing limit. Due to the compensation of the estimated disturbance, the uncertainty that the RMPC has to handle is reduced from the original disturbance to the estimation error of the disturbance. This ensures all the admissible state trajectories are limited within a shrinking neighborhood of the origin and the steady-state error is therefore reduced. Simulation results show the effectiveness of the proposed method.
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22-0933_03_MS
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Accepted/In Press date: 20 April 2023
e-pub ahead of print date: 26 May 2023
Published date: August 2023
Additional Information:
Funding Information:
This work was supported by EPSRC, United Kingdom grants (no. EP/P022952/1 and no. EP/P023002/1 ) and IEC-NSFC ( 223485 ). The material in this paper was not presented at any conference. This paper was recommended for publication in revised form by Associate Editor Michael V. Basin under the direction of Editor André L. Tits.
Publisher Copyright:
© 2023 Elsevier Ltd
Keywords:
Disturbance observer, Linear systems, Robust model predictive control (RMPC), Sliding mode observer (SMO)
Identifiers
Local EPrints ID: 477640
URI: http://eprints.soton.ac.uk/id/eprint/477640
ISSN: 0005-1098
PURE UUID: cd5503fd-40dd-468d-acda-0d2d5ca86f63
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Date deposited: 12 Jun 2023 16:36
Last modified: 17 Mar 2024 04:14
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Contributors
Author:
Yao Zhang
Author:
Christopher Edwards
Author:
Mike Belmont
Author:
Guang Li
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