Full Text:   <266>

Summary:  <10>

CLC number: TP242.6

On-line Access: 2022-07-21

Received: 2021-12-02

Revision Accepted: 2022-05-04

Crosschecked: 2022-07-21

Cited: 0

Clicked: 155

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Hai-bin Duan

https://orcid.org/0000-0002-4926-3202

Yang YUAN

https://orcid.?org/0000-0002-0715-987X

Yimin DENG

https://orcid.?org/0000-0003-1533-3839

Sida LUO

https://orcid.?org/0000-0002-5673-6100

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Frontiers of Information Technology & Electronic Engineering  2022 Vol.23 No.7 P.1020-1031

http://doi.org/10.1631/FITEE.2100559


Distributed game strategy for unmanned aerial vehicle formation with external disturbances and obstacles


Author(s):  Yang YUAN, Yimin DENG, Sida LUO, Haibin DUAN

Affiliation(s):  State Key Laboratory of Virtual Reality Technology and Systems, School of Autonomous Science and Electrical Engineering, Beihang University, Beijing100083, China; more

Corresponding email(s):   yyuan@buaa.edu.cn, ymdeng@buaa.edu.cn, s.luo@buaa.edu.cn, hbduan@buaa.edu.cn

Key Words:  Distributed game strategy, Unmanned aerial vehicle (UAV), Distributed model predictive control (MPC), Levy flight based pigeon inspired optimization (LFPIO), Non-singular fast terminal sliding mode observer (NFTSMO), Obstacle avoidance strategy


Yang YUAN, Yimin DENG, Sida LUO, Haibin DUAN. 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.

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doi="10.1631/FITEE.2100559"
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%A Yang YUAN
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A1 - Yang YUAN
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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.

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1,邓亦敏1,罗斯达2,段海滨1,3
1北京航空航天大学自动化科学与电气工程学院虚拟现实技术与系统国家重点实验室,中国北京市,100083
2北京航空航天大学机械工程及自动化学院,中国北京市,100191
3鹏城实验室,中国深圳市,518000
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。

关键词:分布式博弈策略;无人机;分布式模型预测控制;基于Levy飞行的鸽群优化算法;非奇异快速终端滑模观测器;避障策略

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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