Optimal Leader-Following Consensus of Fractional-Order Multi-Agent Systems Based on Actor-Critic Algorithm

Aimed at the optimal leader-following consensus problem of fractional-order multi-agent systems, an reinforcement learning strategy was designed based on the intermittent event trigger. With the periodic intermittent strategy as the basic mechanism, the event trigger and the actor-critic algorithm in reinforcement learning were organically integrated. According to the 1st-order approximation of the fractional differential, the reinforcement learning algorithm structure based on the periodic intermittent event trigger strategy was proposed. Finally, the feasibility and effectiveness of the algorithm was proved through numerical simulation experiments.