A UAV Formation Control Method Based on Sliding-Mode Control under Communication Constraints
Author:
Chen Qijie1ORCID, Wang Taoyu2, Jin Yuqiang1, Wang Yao1, Qian Bei1
Affiliation:
1. Coast Guard Academy, Naval Aviation University, Yantai 264000, China 2. Weapons Academy, Naval Engineering University, Wuhan 430000, China
Abstract
The problem of vision-based fixed-wing UAV formation control under communication limitations and the presence of measurement errors was investigated. In the first part of this paper, the single UAV motion model and the process of estimating the neighboring UAV states using the Extended Kalman Filter are introduced. The second part describes how we designed a sliding mode controller considering the sensor measurement errors and discusses the sufficient conditions for the stability and formation system in the presence of state transfer time delays in the formation. The main motivation of this paper was to develop a hierarchical, globally stable sliding mode controller that could enable the considered vision-based multiple fixed-wing UAVs to achieve and maintain formation in the presence of measurement errors. To this end, the selected problem was first transformed into a state-tracking problem for UAVs in the neighborhood, and then the stability criterion was established using the Lyapunov stability theory. Finally, the effectiveness of the proposed control method was illustrated using three numerical arithmetic examples.
Subject
Artificial Intelligence,Computer Science Applications,Aerospace Engineering,Information Systems,Control and Systems Engineering
Reference38 articles.
1. Alsamhi, S.H., Shvetsov, A.V., Kumar, S., Shvetsova, S.V., Alhartomi, M.A., Hawbani, A., Rajput, N.S., Srivastava, S., Saif, A., and Nyangaresi, V.O. (2022). UAV Computing-Assisted Search and Rescue Mission Framework for Disaster and Harsh Environment Mitigation. Drones, 6. 2. Flight formation of UAVs in presence of moving obstacles using fast-dynamic mixed integer linear programming;Radmanesh;Aerosp. Sci. Technol.,2016 3. Madyastha, V.K., and Caliset, A.J. (2005, January 8–10). An adaptive filtering approach to target tracking. Proceedings of the American Control Conference, Portland, OR, USA. 4. Alsamhi, S.H., Shvetsov, A.V., Kumar, S., Hassan, J., Alhartomi, M.A., Shvetsova, S.V., Sahal, R., and Hawbani, A. (2022). Computing in the Sky: A Survey on Intelligent Ubiquitous Computing for UAV-Assisted 6G Networks and Industry 4.0/5.0. Drones, 7. 5. Alsamhi, S.H., Ma, O., Ansari, M.S., and Gupta, S.K. (2019). Collaboration of Drone and Internet of Public Safety Things in Smart Cities: An Overview of QoS and Network Performance Optimization. Drones, 3.
Cited by
4 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
|
|