宇航学报 ›› 2020, Vol. 41 ›› Issue (3): 276-286.doi: 10.3873/j.issn.1000-1328.2020.03.004

• 飞行器设计与力学 • 上一篇    下一篇

凸优化算法在有人/无人机协同系统航迹规划中的应用

李樾,韩维,陈清阳,张勇   

  1. 1. 海军航空大学航空基础学院,烟台 264001;2. 国防科技大学空天科学学院,长沙 410073
  • 收稿日期:2019-01-27 修回日期:2019-06-10 出版日期:2020-03-15 发布日期:2020-03-25
  • 基金资助:
    国家自然科学基金(61703414);中国博士后科学基金(2014M562652)

Application of Convex Optimization Algorithm in Trajectory Planning of Manned/Unmanned Cooperative System#br#

LI Yue, HAN Wei, CHEN Qing yang, ZHANG Yong   

  1. 1. Aviation Foundation College, Naval Aviation University, Yantai 264001, China;2. College of Aerospace Science and Engineering, National University of Defense Technology, Changsha 410073, China
  • Received:2019-01-27 Revised:2019-06-10 Online:2020-03-15 Published:2020-03-25

摘要: 为更好地发挥多智能体在空战中的优势,以凸优化理论为基础,提出一种有人/无人机协同系统的航迹规划方法。首先,分析协同系统的体系结构和控制流程,建立系统的运动模型。其次,根据协同系统中有人机与无人机的任务特点,分别设计航迹规划器与编队规划器,并在编队规划器中引入协同时空约束条件,进而对两规划器模型进行近似与凸化,利用凸优化算法进行求解。最后,通过对比仿真,验证所提方法的可行性。结果表明,凸优化算法能有效求解航迹规划器与编队规划器的优化模型,并且通过协同时空约束,能有效提高系统的飞行安全性及航迹变换的灵活性。

关键词: 有人/无人机, 协同系统, 凸优化, 航迹规划, 时空约束

Abstract: To perform the advantages of multiple agents in air combat, a method of trajectory planning based on the convex optimization algorithm, for manned/unmanned cooperative system is proposed. Firstly, the architecture and control flow of the cooperative system are analyzed, and the motion model of the system is established. Secondly, the flight path planner and the formation planner are designed according to the characteristics of the manned aerial vehicle (MAV) and unmanned aerial vehicle (UAV) in the system, and the spatial-temporal constraints are introduced into the formation planner. Then the model of the two planners is approximated and convexified, and the convex optimization algorithm is chosen to solve the problem. Finally, the effectiveness of the proposed method is verified by numerical simulations. The results show that the model can be commendably solved by the convex optimization algorithm. Meanwhile the flight safety and transformation flexibility of the system can be improved by adding the synergetic spatial-temporal constraints.

Key words: MAV/UAV, Cooperative system, Convex optimization, Trajectory planning, Spatial-temporal constraints

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