系统工程与电子技术 ›› 2023, Vol. 45 ›› Issue (10): 3240-3248.doi: 10.12305/j.issn.1001-506X.2023.10.28

• 制导、导航与控制 • 上一篇    

基于改进狼群算法的无人直升机航迹规划

王黎文, 邵书义, 吴庆宪, 韩增亮   

  1. 南京航空航天大学自动化学院, 江苏 南京 211106
  • 收稿日期:2022-06-17 出版日期:2023-09-25 发布日期:2023-10-11
  • 通讯作者: 邵书义
  • 作者简介:王黎文 (1995—), 男, 硕士研究生, 主要研究方向为无人直升机航迹规划与轨迹跟踪控制
    邵书义 (1987—), 男, 副研究员, 博士, 主要研究方向为飞行控制
    吴庆宪 (1955—), 男, 教授, 博士, 主要研究方向为飞行器飞行控制、非线性系统的鲁棒自适应控制
    韩增亮 (1992—), 男, 博士研究生, 主要研究方向为无人自主飞行器航路规划、智能火力与指挥控制
  • 基金资助:
    江苏省自然科学基金青年基金(BK20200415);航空科学基金(201957052001);博士后科学基金面上项目(2020M681587);江苏省博士后基金(2020Z112)

Path planning of unmanned autonomous helicopter based on improved wolf pack algorithm

Liwen WANG, Shuyi SHAO, Qingxian WU, Zengliang HAN   

  1. College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
  • Received:2022-06-17 Online:2023-09-25 Published:2023-10-11
  • Contact: Shuyi SHAO

摘要:

针对无人直升机(unmanned autonomous helicopter, UAH)航迹规划中传统狼群算法(wolf pack algorithm, WPA)收敛速度慢和易陷入局部最优的问题, 提出了一种基于改进WPA的UAH三维航迹规划算法。首先, 对UAH飞行三维环境、约束条件及适应度函数进行数学建模; 然后,通过自适应步长的方式对传统WPA中游走、召唤及围攻3种主要行为的步长进行改进。同时, 采用莱维飞行与变方向游走相结合的策略调整游走行为中的搜索方向及范围, 从而提高算法的全局寻优能力和收敛速度;最后,给出了改进WPA在三维环境下航迹规划的仿真结果。仿真结果表明, 改进WPA收敛速度更快, 规划出的航迹质量更优, 验证了该算法在UAH航迹规划中的有效性。

关键词: 改进狼群算法, 自适应步长, 莱维飞行, 变方向游走

Abstract:

For the problems of traditional wolf pack algorithm (WPA) in the flight path planning for unmanned autonomous helicopters (UAH), including slower convergence speed and easy failing into local optimum solution, a three-dimensional flight path planning algorithm for UAH based on improved WPA is proposed. Firstly, the three-dimensional environment, constraints and fitness function of UAH flight are modeled. Secondly, the adaptive step-size method is used to improve the step size of the three main steps of wandering behavior, summoning behavior and siege behavior in the traditional WPA. At the same time, the strategy of combing Levy flight and changing direction migration are used for adjusting direction and scope of the search in walking behavior, so as to improve the global optimization ability and convergence speed of the algorithm. Finally, the simulation results show that the improved WPA has faster convergence and better track quality, which verifies the effectiveness of the proposed algorithm in the UAH flight path planning.

Key words: improved wolf pack algorithm (WPA), adaptive step-size, Levy flight, changing direction migration

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