Dynamic event-driven optimal consensus control for state-constrained multiagent zero-sum differential graphical games

Siyu Guo, Yingnan Pan and Hongyi Li

Applied Mathematics and Computation, 2025, vol. 484, issue C

Abstract: In this paper, a dynamic event-driven optimal control scheme is proposed for the zero-sum differential graphical games in nonlinear multiagent systems with full-state constraints. Initially, to address the dual demands of optimality and state constraints, a set of system transformation functions are introduced to satisfy the state constraints of the agents. Then, by applying the principle of differential game theory, the distributed optimal control problem affected by external disturbances is formulated as a zero-sum differential graphical game, and the performance index function related to neighbor informations and disturbances is designed for each follower. Afterwards, to enhance the utilization of communication resource, a novel dynamic event-triggered mechanism characterized by a dynamic threshold parameter and an auxiliary dynamic variable is developed, which not only exhibits greater flexibility but also diminishes the frequency of triggers. Furthermore, the approximate optimal control strategies are obtained by employing an event-driven adaptive dynamic programming algorithm. Ultimately, a simulation example is presented to verify the applicability of the proposed control approach.

Keywords: Adaptive dynamic programming; Dynamic event-triggered mechanism; Full-state constraints; Zero-sum differential graphical games (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:apmaco:v:484:y:2025:i:c:s0096300324004405

DOI: 10.1016/j.amc.2024.128979

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