Optimal leader-following consensus under switching topologies based on event-triggered NN-based observer

Abstract

This paper proposes a novel control strategy for multi-agent systems (MASs) to achieve optimal leader-following consensus under jointly connected topologies. The devised approach incorporates two key components: an event-triggered neural network (NN)-based leader observer and an NN-based optimal controller. The proposed leader observer allows followers to locally reconstruct the leader’s dynamics, even in scenarios where the communication topology is jointly connected. The implementation of an event-triggered communication protocol significantly reduces the communication burden, enhancing the overall efficiency of information exchange. As the observer’s state converges to the actual leader’s state, the simplification of achieving leader-follower consensus becomes evident by directly setting the state of the leader observer as the tracking goal. An NN-based optimal controller is utilized to approximate the solution to the Hamilton–Jacobi–Bellman (HJB) equation, thus enabling optimal tracking of the leader by followers. Finally, the performance of the proposed control strategy is verified by simulations.