Affiliation:
1. School of Equipment Management and Unmanned Aerial Vehicle Engineering, Air Force Engineering University, Xi’an 710043, China
Abstract
The use of affine maneuver control to maintain the desired configuration of unmanned aerial vehicle (UAV) swarms has been widely practiced. Nevertheless, the lack of capability to interact with obstacles and navigate autonomously could potentially limit its extension. To address this problem, we present an innovative formation flight system featuring a virtual leader that seamlessly integrates global control and local control, effectively addressing the limitations of existing methods that rely on fixed configuration changes to accommodate real-world constraints. To enhance the elasticity of an algorithm for configuration change in an obstacle-laden environment, this paper introduces a second-order differentiable virtual force-based metric for planning local trajectories. The virtual field comprises several artificial potential field (APF) forces that adaptively adjust the formation compared to the existing following control. Then, a distributed and decoupled trajectory optimization framework that considers obstacle avoidance and dynamic feasibility is designed. This novel multi-agent agreement strategy can efficiently coordinate the global planning and local trajectory optimizations of the formation compared to a single method. Finally, an affine-based maneuver approach is employed to validate an optimal formation control law for ensuring closed-loop system stability. The simulation results demonstrate that the proposed scheme improves track accuracy by 32.92% compared to the traditional method, while also preserving formation and avoiding obstacles simultaneously.
Reference36 articles.
1. A Testbed for Investigating the UAV Swarm Command and Control Problem Using DDDAS;Purta;Procedia Comput. Sci.,2013
2. Quan, L., Yin, L., Zhang, T., Wang, M., Wang, R., Zhong, S., Cao, Y., Xu, C., and Gao, F. (2022). Formation Flight in Dense Environments. arXiv.
3. A survey of multi-agent formation control;Oh;Automatica,2015
4. Bearing Rigidity and Almost Global Bearing-Only Formation Stabilization (Vol.);Zhao;IEEE Trans. Autom. Control,2016
5. Rigid Graph Control Architectures for Autonomous Formations;Anderson;IEEE Control Syst.,2008
Cited by
1 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