Distributed adaptive fixed-time formation control for UAV-USV heterogeneous multi-agent systems

Abstract

This paper investigates formation trajectory tracking control for heterogeneous multi-agent systems with external disturbances, model uncertainties and input saturation. The system that is considered comprises one unmanned aerial vehicle (UAV) and multiple unmanned surface vessels (USVs). First, based on directed graph theory, a distributed formation control protocol is proposed for the UAV-USV heterogeneous multi-agent system. Second, combining the advantages of the adaptive technique and radial basis function (RBF) neural networks, a global fixed-time adaptive neural network nonsingular fast terminal sliding formation control protocol is designed to ensure tracking of the desired trajectory and form the predetermined formation configuration within a fixed time in the presence of various uncertainties. Through the proposed adaptive neural network (NN) control technology, the lumped uncertainty can be estimated, and the number of update parameters can be reduced, thereby relieving the calculation burden of the controllers. In addition, a dynamic event-triggered mechanism is incorporated into the controllers, which can reduce the update frequency of controllers, thereby decreasing the communication number of controllers. A saturation function is introduced simultaneously to solve the problem of input saturation. Finally, the simulation results are given to indicate the feasibility of the proposed formation control protocol.