Surrounding Control Based on Optimal Targets Assignment and Dynamic Graph Game

In this article, the distributed surrounding control problem is addressed for the linear multi-agent systems, in which a hierarchical strategy framework is constructed consisting of optimal target assignment and game-driven surrounding control. Aiming at fulfilling the multiple targets surrounding task with high efficiency and balanced mission load, an optimal target assignment mechanism is developed with the assistance of the cross entropy method (CEM) and twin delayed deep deterministic policy gradient algorithm (TD3), where an evaluation function related to the arrival time from each agent to capture the target is proposed. Considering the high degree of autonomy of the targets, a surrounding control protocol driven by the dynamic graph game is proposed afterward. To find the equilibrium solution of the pursuit-escape game, the coupled Hamilton–Jacobi–Bellman (HJB) equation is solved by a delicately designed model based value iteration algorithm, whose stability is demonstrated by the rigorous theoretical analysis. Finally, we undertake numerical experiments to ascertain the efficacy of the introduced game-driven surrounding control strategy.