Event-triggered distributed predictive control for multi-agent systems with stability constraints

doi:10.1016/j.automatica.2025.112358

Event-triggered distributed predictive control for multi-agent systems with stability constraints

2025-06-07

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DOI：10.1016/j.automatica.2025.112358

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This article investigates the event-triggered distributed predictive control problem for multi-agent systems, where each subsystem is subject to bounded disturbances and input constraints. Compared with existing works, we derive a less conservative event-triggering mechanism for each subsystem that does not involve neighbors' information by leveraging stability constraints. This approach alleviates energy consumption and communication load in resource-constrained multi-agent systems. In our proposed framework, each subsystem solves the distributed optimization problem and transmits its information to its neighbors only when a certain level of control performance cannot be guaranteed according to the designed triggering condition. Moreover, a dynamic event-triggering mechanism is introduced by relaxing the requirements for the Lyapunov function candidate, thereby achieving longer inter-execution times between successive triggering instants. Theoretical analyses are developed to guarantee feasibility and closed-loop stability. Finally, numerical simulation examples are provided to verify the effectiveness of the proposed algorithms. (c) 2025 Elsevier Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

Keywords:

Event-triggered control

Distributed predictive control

Multi-agent systems

Stability constraints

Event-triggered distributed predictive control for multi-agent systems with stability constraints

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