文献类型：会议论文

英文题名：Time-Varying Formation Control of?Drones Using Consensus Theory

作者：Shi, Xinhao[1,3,4]; Yang, Tao[1]; Zeng, Qinghan[3,4]; Yang, Yulin[3,4]; Liu, Hongzhe[1,2]; Xu, Cheng[1,2]; Xu, Bingxin[1,2]

第一作者：Shi, Xinhao

机构：[1] Beijing Key Laboratory of Information Service Engineering, Beijing Union University, Beijing, China; [2] Institute for Brain and Cognitive Sciences, College of Robotics, Beijing Union University, Beijing, China; [3] Scientific and Technical Center for Innovation, Unit 32178 of the PLA Beijing, Beijing, 100012, China; [4] Unit 32381 of the PLA Beijing, Beijing, 100012, China

第一机构：北京联合大学北京市信息服务工程重点实验室

通讯机构：[3]Scientific and Technical Center for Innovation, Unit 32178 of the PLA Beijing, Beijing, 100012, China

会议论文集：Proceedings of 2023 7th Chinese Conference on Swarm Intelligence and Cooperative Control - Swarm Control Technologies

会议日期：November 24, 2023 - November 27, 2023

会议地点：Nanjing, China

语种：英文

外文关键词：Aircraft control - Antennas - Control theory - Time varying control systems

摘要：This study introduces a novel time-varying formation control strategy for Unmanned Aerial Vehicles (UAVs), based on consistency theory. The primary objective is to achieve and maintain consistency among UAVs in formation tasks, allowing them to complete complex maneuvers seamlessly. Initially, we design the time-varying formation control laws and elaborate on the cluster topology relationships. Subsequently, we validate the consistency of the time-varying formation using consistency theory, ensuring uniformity among UAVs within the formation. To assess the effectiveness of the proposed method, we conduct extensive simulation experiments on UAV formations of varying scales, specifically 9, 33, and 100 UAV formations. Our results demonstrate that the proposed method can successfully complete UAV formation tasks, including transitioning from a wedge formation to a circular formation during flight. Our findings suggest that the proposed method is both practical and feasible, offering an efficient solution for UAV formation tasks. ? The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.