Distributed edge-based event-triggered optimal formation control for air-sea heterogeneous multiagent systems

Abstract

This paper addresses the optimal formation control problem for a class of air-sea heterogeneous multiagent systems with external disturbances and model uncertainties. Multiple unmanned aerial vehicles (UAVs) and multiple unmanned surface vessels (USVs) are considered in this system. First, a distributed adaptive state compensator is designed for each agent to estimate the state information of the virtual leader. This compensator is equipped with an edge-based event-triggered scheme to reduce the amount of communication for each edge. Second, a reinforcement learning-based optimal formation controller with the appointed-time prescribed performance is designed to obtain the formation configuration for an air-sea system. This method not only optimizes the formation controller but also ensures the steady-state accuracy and stabilization time. Additionally, an event-triggered mechanism is proposed to reduce the number of optimal formation controller communications. A self-structuring actor-critic neural network and a self-structuring radial basis function neural network are also proposed to solve the Hamilton-Jacobi-Bellman (HJB) equation and approximate the uncertainty, respectively. It can constantly adjust the number of neurons, eventually obtaining an optimal number. Finally, it is proven by Lyapunov theory that all signals are semiglobally uniform and eventually bounded, and the simulation results are provided to illustrate the effectiveness of the scheme.