Event-Based Fuzzy Asynchronous Consensus for UAV Swarm Under Jointly Connected Digraphs

Abstract

An adaptive fuzzy dynamic event-triggered control approach is proposed for a fleet of fixed-wing unmanned aerial vehicles (UAVs) operating under jointly connected switching topologies. The primary challenge lies in addressing asynchronous switching topologies caused by topology identification delays. To tackle this, asynchronous distributed observers are constructed, and topological switching rules are designed, ensuring that all follower UAVs can estimate the leader UAV’s state by leveraging asynchronous distributed state errors. In addition, a novel dynamic event-triggering mechanism is introduced. Compared to state-of-the-art methods, the proposed triggering function directly couples the external state variable with the last triggered value, dynamically regulates the triggered interval based on the control performance, and minimizes the number of occurrences while maintaining the system performance. An adaptive fuzzy translational and rotational controller is further developed to enable the follower UAVs to accurately track the state of the leader UAV while ensuring that all closed-loop states remain globally uniformly ultimately bounded. The proposed strategies are validated for effectiveness and superiority through a semiphysical simulation platform.