Self-Triggered MPC Design for Distributed Systems Subject to Global Coupled Constraints
This paper investigates a self-triggered distributed model predictive control (DMPC) approach for linear systems with external disturbances and global coupled constraints in communication-limited environments. To handle external disturbances, a robust constraint is imposed on the local system state,...
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| Published in: | Chinese Control Conference pp. 3060 - 3065 |
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| Main Authors: | , |
| Format: | Conference Proceeding |
| Language: | English |
| Published: |
Technical Committee on Control Theory, Chinese Association of Automation
28.07.2025
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| Subjects: | |
| ISSN: | 1934-1768 |
| Online Access: | Get full text |
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| Abstract | This paper investigates a self-triggered distributed model predictive control (DMPC) approach for linear systems with external disturbances and global coupled constraints in communication-limited environments. To handle external disturbances, a robust constraint is imposed on the local system state, and the global coupled constraint is accordingly tightened. Based on this, an optimal control problem (OCP) and a self-triggered mechanism are designed to regulate the system's state and decrease computational overhead, respectively. At each predetermined triggered instant, the OCP is solved via a consensusbased algorithm, followed by the re-calculation of the open-loop phase. Sufficient conditions guaranteeing recursive feasibility and closed-loop stability are presented. Simulation results illustrate the validity of the proposed algorithm. |
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| AbstractList | This paper investigates a self-triggered distributed model predictive control (DMPC) approach for linear systems with external disturbances and global coupled constraints in communication-limited environments. To handle external disturbances, a robust constraint is imposed on the local system state, and the global coupled constraint is accordingly tightened. Based on this, an optimal control problem (OCP) and a self-triggered mechanism are designed to regulate the system's state and decrease computational overhead, respectively. At each predetermined triggered instant, the OCP is solved via a consensusbased algorithm, followed by the re-calculation of the open-loop phase. Sufficient conditions guaranteeing recursive feasibility and closed-loop stability are presented. Simulation results illustrate the validity of the proposed algorithm. |
| Author | Li, Shaoyuan Chen, Qianqian |
| Author_xml | – sequence: 1 givenname: Qianqian surname: Chen fullname: Chen, Qianqian organization: Shanghai Jiao Tong University,Department of Automation,Shanghai,China – sequence: 2 givenname: Shaoyuan surname: Li fullname: Li, Shaoyuan email: syli@sjtu.edu.cn organization: Shanghai Jiao Tong University,Department of Automation,Shanghai,China |
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| Snippet | This paper investigates a self-triggered distributed model predictive control (DMPC) approach for linear systems with external disturbances and global coupled... |
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| SubjectTerms | Global coupled constraints Linear systems Optimal control Prediction algorithms Predictive control Robust DMPC Self-triggered DMPC Simulation Stability analysis Sufficient conditions |
| Title | Self-Triggered MPC Design for Distributed Systems Subject to Global Coupled Constraints |
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