Distributed formation tracking control of multiple autonomous surface vehicles: A hierarchical event-triggered approach

This paper proposes a hierarchical event-triggered approach for distributed formation tracking of multiple autonomous surface vehicles (ASVs). The kinematic and dynamic loops are developed to generate the guidance law and the control efforts respectively. In the kinematic loop, a surrogate model is developed for each ASV, so that the kinematic states of the ASV can be predicted by its neighbors. Only when a predefined event-triggering condition is satisfied, will the ASV's true states be broadcast for updating the corresponding surrogate model, which circumvents the continuous states exchanges between ASVs. Additionally, a distributed leader motion observer is constructed to estimate the virtual leader's velocities to avoid acquiring global information. In the dynamic loop, a novel event-triggered extended state observer is developed, by which the velocity tracking errors and the model uncertainties are estimated online and transmitted to a dynamic-inversion based controller only when necessary. The communication loads in sensor-to-controller and controller-to-actuator channels are thus simultaneously reduced. The stability of the closed-loop system is rigorously proved by the Lyapunov theory and cascade system theory. The Zeno behavior is also well excluded in multiple channels. Simulation results show that the proposed scheme has satisfactory control performances and distinct features of low communication burdens and energy consumption.