具有外部干扰和障碍物的无人机编队分布式博弈策略

袁洋; 邓亦敏; 罗斯达; 段海滨

doi:10.1631/FITEE.2100559

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具有外部干扰和障碍物的无人机编队分布式博弈策略

多智能体系统的体系化和组织化博弈专题 | Updated：2022-09-08

- 具有外部干扰和障碍物的无人机编队分布式博弈策略
- Distributed game strategy for unmanned aerial vehicle formation with external disturbances and obstacles
- 信息与电子工程前沿(英文版) 2022年23卷第7期页码：1020-1031
- Affiliations：
  
  1.State Key Laboratory of Virtual Reality Technology and Systems, School of Autonomous Science and Electrical Engineering, Beihang University, Beijing100083, China
  2.School of Mechanical Engineering & Automation, Beihang University, Beijing100191, China
  3.Peng Cheng Laboratory, Shenzhen518000, China
- Author bio：
  
  E-mail: yyuan@buaa.edu.cn;
  E-mail: ymdeng@buaa.edu.cn;
  E-mail: s.luo@buaa.edu.cn;
  ‡Corresponding authors
- Funds：
  
  the Science and Technology Innovation 2030 Key Project of “New Generation Artificial Intelligence,” China(2018AAA0100803);the National Natural Science Foundation of China(T2121003;U1913602;U20B2071;91948204;U19B2033)
- DOI：10.1631/FITEE.2100559
  中图分类号： TP242.6
- 收稿：2021-12-02，
  
  修回：2022-05-04，
  
  网络出版：2022-07-12，
  
  纸质出版：2022-07-23
- Accepted：
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袁洋, 邓亦敏, 罗斯达, 等. 具有外部干扰和障碍物的无人机编队分布式博弈策略[J]. 信息与电子工程前沿(英文版), 2022,23(7):1020-1031.

Yang YUAN, Yimin DENG, Sida LUO, et al. Distributed game strategy for unmanned aerial vehicle formation with external disturbances and obstacles[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(7): 1020-1031.
袁洋, 邓亦敏, 罗斯达, 等. 具有外部干扰和障碍物的无人机编队分布式博弈策略[J]. 信息与电子工程前沿(英文版), 2022,23(7):1020-1031. DOI： 10.1631/FITEE.2100559.

Yang YUAN, Yimin DENG, Sida LUO, et al. Distributed game strategy for unmanned aerial vehicle formation with external disturbances and obstacles[J]. Frontiers of Information Technology & Electronic Engineering, 2022, 23(7): 1020-1031. DOI： 10.1631/FITEE.2100559.

摘要

本文研究了具有外部干扰和障碍物的无人机编队分布式博弈策略，该策略基于分布式模型预测控制（MPC）框架和基于Levy飞行的鸽群优化算法（LFPIO）。首先，提出一种非奇异快速终端滑模观测器（NFTSMO）估计无人机受扰动的影响，并利用Lyapunov函数证明该观测器在固定时间内收敛。其次，设计一种基于拓扑重构的避障策略，使无人机能够以较小能量消耗安全通过障碍物。然后，建立一个分布式MPC框架，该框架中每架无人机仅与邻居交换消息，通过设计分布式MPC代价函数，将无人机编队问题转化为博弈问题，并利用基于Levy飞行的鸽群优化算法求解纳什均衡。最后，利用数值仿真对比实验验证所提策略的有效性。

Abstract

We investigate a distributed game strategy for unmanned aerial vehicle (UAV) formations with external disturbances and obstacles. The strategy is based on a distributed model predictive control (MPC) framework and Levy flight based pigeon inspired optimization (LFPIO). First

we propose a non-singular fast terminal sliding mode observer (NFTSMO) to estimate the influence of a disturbance

and prove that the observer converges in fixed time using a Lyapunov function. Second

we design an obstacle avoidance strategy based on topology reconstruction

by which the UAV can save energy and safely pass obstacles. Third

we establish a distributed MPC framework where each UAV exchanges messages only with its neighbors. Further

the cost function of each UAV is designed

by which the UAV formation problem is transformed into a game problem. Finally

we develop LFPIO and use it to solve the Nash equilibrium. Numerical simulations are conducted

and the efficiency of LFPIO based distributed MPC is verified through comparative simulations.

关键词

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references

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