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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Bibliographic Details
Published in:Chinese Control Conference pp. 3060 - 3065
Main Authors: Chen, Qianqian, Li, Shaoyuan
Format: Conference Proceeding
Language:English
Published: Technical Committee on Control Theory, Chinese Association of Automation 28.07.2025
Subjects:
Global coupled constraints
Linear systems
Optimal control
Prediction algorithms
Predictive control
Robust DMPC
Self-triggered DMPC
Simulation
Stability analysis
Sufficient conditions
ISSN:1934-1768
Online Access:Get full text
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Summary: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.
ISSN:1934-1768
DOI:10.23919/CCC64809.2025.11179172