文献类型：期刊文献

英文题名：Distributed Adaptive Fixed-Time Formation Control for Uav-Usv Heterogeneous Multi-Agent Systems

作者：Liu, Haitao[1,2]; Weng, Peijun[1]; Mai, Qingqun[1,2]; Tian, Xuehong[1,2]

机构：[1] School of Mechanical and Power Engineering, Guangdong Ocean University, Zhanjiang, 524088, China; [2] Shenzhen Institute, Guangdong Ocean University, Shenzhen, 518120, China

年份：2022

外文期刊名：SSRN

收录：EI(收录号：20220380130)

语种：英文

外文关键词：Adaptive control systems - Aircraft control - Antennas - Directed graphs - Multi agent systems - Radial basis function networks - Recurrent neural networks - Uncertainty analysis - Unmanned aerial vehicles (UAV) - Unmanned surface vehicles

外文摘要：This paper investigates formation trajectory tracking control for heterogeneous multi-agent systems with external disturbances, model uncertainties and input saturation. The considered system 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 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 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. ? 2022, The Authors. All rights reserved.