Zero-Sum-Game-Based Distributed Fuzzy Adaptive Self-Triggered Control of Swarm UAVs Under Intermittent Communication and DoS Attacks

This article addresses the distributed zero-sum differential game adaptive control problem of six-rotor unmanned aerial vehicles under denial-of-service attacks based on the self-triggered mechanism. First, a fuzzy-logic-system-based identifier-critic framework is structured to obtain the alternative approximate solution with fewer learning parameters. Then, a novel optimal value function, considering the optimal control signal, worst disturbance signal, steady-state, and dynamic performances, is designed. Subsequently, an improved self-triggered strategy, featuring negative feedback adjustment between the threshold and system consensus error, is proposed to reduce the communication resource loss and decrease the influence of introducing the self-triggered mechanism on the system performance. Unlike the event-triggered strategy, the next trigger moment of the self-triggered strategy is determined by the current information, eliminating the need for continuous monitoring of the trigger state, which is more convenient for the physical implementation. Moreover, the connectivity-broken denial-of-service attacks on the information transmission process among unmanned aerial vehicles are considered. Next, through the transformation between stabilization control and cooperative control, the difficulty of realizing cooperative control caused by the temporarily disrupted topological relationships due to denial-of-service attacks is solved effectively. Using Lyapunov stability theory, it is proved that all signals of six-rotor unmanned aerial vehicles are bounded, and the consensus control performance is achieved. Finally, the rationality of the designed zero-sum differential game adaptive control scheme is verified by some simulation results.