吉林大学学报(工学版) ›› 2023, Vol. 53 ›› Issue (3): 871-882.doi: 10.13229/j.cnki.jdxbgxb20221034

• 通信与控制工程 • 上一篇    

基于状态观测器的多四旋翼无人机时变编队控制

于雅静1(),郭健1,王荣浩2,秦伟3,4,宋明武4,向峥嵘1()   

  1. 1.南京理工大学 自动化学院，南京 210094
    2.陆军工程大学 国防工程学院，南京 210007
    3.军事科学院 国防科技创新研究院，北京 100091
    4.天津（滨海）人工智能创新中心，天津 300450
  • 收稿日期:2022-08-15 出版日期:2023-03-01 发布日期:2023-03-29
  • 通讯作者: 向峥嵘 E-mail:yajing.yu@njust.edu.cn;xiangzr@njust.edu.cn
  • 作者简介:于雅静（1990-），女，博士研究生. 研究方向：多智能体、无人机编队控制. E-mail：yajing.yu@njust.edu.cn
  • 基金资助:
    国家自然科学基金项目(61873128);江苏省重点研发计划重点项目(BE2021016);江苏省“六大人才高峰”高层次人才项目(GDZB-027)

Time⁃varying formation control of multi⁃quadrotor unmanned aerial vehicles based on state observer

Ya-jing YU1(),Jian GUO1,Rong-hao WANG2,Wei QIN3,4,Ming-wu SONG4,Zheng-rong XIANG1()   

  1. 1.School of Automation，Nanjing University of Science and Technology，Nanjing 210094，China
    2.Academy of National Defense Engineering，Army Engineering University，Nanjing 210007，China
    3.Defense Innovation Institute，Academy of Military Sciences，Beijing 100091，China
    4.Tianjin Artificial Intelligence Innovation Center，Tianjin 300450，China
  • Received:2022-08-15 Online:2023-03-01 Published:2023-03-29
  • Contact: Zheng-rong XIANG E-mail:yajing.yu@njust.edu.cn;xiangzr@njust.edu.cn

RICH HTML

 8   

PDF (PC)

456

摘要：

针对有向切换通信网络下多四旋翼无人机系统存在的部分信息不可测问题，基于神经网络状态观测器方法，提出了分布式自适应滑模时变编队控制方案。首先，通过设计分布式时变编队控制协议，使无人机仅需邻居状态信息便可实现通信，摆脱了对全局信息的依赖。其次，由于欠驱动特性的存在，设计了位置辅助控制器，解算出姿态目标信息和控制推力。同时，通过设计神经网络状态观测器，对系统不可测信息进行观测，并将观测值反馈到自适应滑模控制器中，提高了无人机系统的鲁棒性。最后，通过Lyapunov定理对四旋翼无人机编队系统进行分析，证明了多无人机编队追踪误差有界且可收敛到零点邻域内。仿真结果表明，本文控制方法可以使多无人机系统实现时变编队控制，验证了理论结果的有效性。

关键词: 无人机系统, 有向切换通信网络, 神经网络状态观测器, 时变编队控制, 自适应滑模控制

Abstract:

A distributed adaptive sliding mode time-varying formation control scheme based on neural network state observer was proposed to solve the problem of unmeasurable information of multi-quadrotor unmanned aerial vehicles （UAVs） system in directed switching communication network. Firstly， by designing a distributed time-varying formation control protocol， UAVS can communicate with each other only by the status information of their neighbors， which is free from the dependence on global information. Due to the underdrive characteristic， a position-assisted controller was designed to solve the target information of two attitude angles and control thrust. At the same time， a neural network state observer was designed to observe the unmeasurable information of the system， and the observed values were feedback to the adaptive sliding mode controller in real time， which improves the robustness of the UAV system. The quadrotor UAV formation system is analyzed by Lyapunov's theorem， and it proved that the multi-UAV formation error is bounded and converges to near zero. The simulation results show that the proposed control method can realize the time-varying formation control of the multi-UAV system and verify the validity of the theoretical results.

Key words: unmanned aerial vehicles system, directed switching communications network, neural network state observer, time-varying formation control, adaptive sliding mode control

中图分类号: 

  • V249.121

图1

四旋翼无人机结构图"

图2

双环控制系统结构图"

图3

可能的通信网络结构"

表1

无人机初始状态"

名称位置/m速度/（m·s-1）姿态角/（°）
UAV1（-50，50，0）（1.5，1.5，1.5）（0，0，0）
UAV2（-55，75，0）（1.2，1.2，1.2）（0，0，0）
UAV3（75，30，0）（1.6，1.6，1.6）（0，0，0）
UAV4（150，10，0）（1.2，1.2，1.2）（0，0，0）

图4

无人机时变编队3D轨迹图"

图5

控制输入"

图6

自适应律"

图7

四架无人机位置、速度和姿态曲线及其观测误差"

图8

四架无人机追踪误差"

图9

不同算法无人机2位置、速度和姿态观测误差曲线"

图10

两种不同算法无人机2追踪误差曲线"

1 黄文华. 未来智能无人对抗的机遇与挑战[J]. 现代应用物理, 2019, 10(4): 18-22.
Huang Wen-hua. Opportunities and challenges in future intelligent and unmanned countermeasures[J]. Modern Applied Physics, 2019, 10(4): 18-22.
2 喻煌超, 牛轶峰, 王祥科. 无人机系统发展阶段和智能化趋势[J]. 国防科技, 2021, 42(3): 18-24.
Yu Huang-chao, Niu Yi-feng, Wang Xiang-ke. Development stages and intelligent trends of UAV systems[J]. National Defense Technology, 2021, 42(3): 18-24.
3 Dong X, Hua Y, Zhou Y, et al. Theory and experiment on formation-containment control of multiple multirotor unmanned aerial vehicle systems[J]. IEEE Transactions on Automation Science and Engineering, 2019, 16(1): 229-240.
4 张邦楚, 廖剑, 匡宇, 等. 美国无人机集群作战的研究现状与发展趋势[J]. 航空兵器, 2020, 27(6): 7-12.
Zhang Bang-chu, Liao Jian, Kuang Yu, et al. Research status and development trend of the united states UAV swarm battlefield[J]. Aero Weaponry, 2020, 27(6): 7-12.
5 谷旭平, 唐大全, 唐管政. 无人机集群关键技术研究综述[J]. 自动化与仪器仪表, 2021(4): 21-26, 30.
Gu Xu-ping, Tang Da-quan, Tang Guan-zheng. Summary of research on key technologies of UAV Swarms[J]. Automation and Instrumentation, 2021(4): 21-26, 30.
6 朱旭, 张逊逊, 闫茂德, 等. 基于一致性的无人机编队控制策略[J]. 计算机仿真, 2016, 33(8): 30-34.
Zhu Xu, Zhang Xun-xun, Yan Mao-de, et al. UAV formation control strategy based on consensus[J]. Computer Simulation, 2016, 33(8): 30-34.
7 王品, 姚佩阳. 多无人机系统分布式编队控制[J]. 计算机工程与应用, 2016, 52(16): 1-6.
Wang Pin, Yao Pei-yang. Method of distributed UAV formation control[J]. Computer Engineering and Applications, 2016, 52(16): 1-6.
8 王祥科, 陈浩, 赵述龙. 大规模固定翼无人机集群编队控制方法[J]. 控制与决策, 2021, 36(9): 2063-2073.
Wang Xiang-ke, Chen Hao, Zhao Shu-long. Formation control of large-scale fixed-wing unmanned aerial vehicle swarms[J]. Control and Decision, 2021, 36(9): 2063-2073.
9 鲜斌, 李宏图. 分布式多无人机的时变编队非线性控制设计[J]. 控制与决策, 2021, 36(10): 2490-2496.
Xian Bin, Li Hong-tu. Time-varying formation nonlinear control of distributed multiple UAVs[J]. Control and Decision, 2021, 36(10): 2490-2496.
10 董朝阳, 张文强, 王青.复杂不确定性下多无人机的抗扰时变编队控制[J].宇航学报,2020,41(3): 319-328.
Dong Chao-yang, Zhang Wen-qiang, Wang Qing. Time-varying anti-disturbance formation control for multi-UAV systems with complex uncertainties[J]. Journal of Astronautics, 2020, 41(3): 319-328.
11 周绍磊, 祁亚辉, 张雷, 等. 切换拓扑下无人机集群系统时变编队控制[J]. 航空学报, 2017, 38(4): 264-272.
Zhou Shao-lei, Qi Ya-hui, Zhang Lei, et al. Time-varying formation control of UAV swarm systems with switching topologies[J]. Acta Aeronautica et Astronautica Sinica, 2017, 38(4): 264-272.
12 赵学远, 周绍磊, 王帅磊, 等. 切换拓扑条件下的多无人机系统编队包含控制[J]. 计算机科学, 2020, 47(S1): 577-582.
Zhao Xue-yuan, Zhou Shao-lei, Wang Shuai-lei, et al. Formation containment control of multi-UAV system under switching topology[J]. Computer Science, 2020, 47(S1): 577-582.
13 刘流, 梁晓龙, 张佳强, 等. 切换通信拓扑条件下的无人机集群构型变换控制[J]. 兵工学报, 2019, 40(5): 996-1002.
Liu Liu, Liang Xiao-long, Zhang Jia-qiang, et al. UAV swarm formation reconfiguration control with switching interaction topologies[J]. Acta Armamentarii, 2019, 40(5): 996-1002.
14 王琳, 张庆杰, 陈宏伟. 有向拓扑下多无人机系统编队跟踪控制[J/OL].[2022-06-13].. c n k i . n e t /kcms/detail/41.1227.TN.20220511.1725.002.html
15 Dong X, Li Y, Lu C, et al. Time-varying formation tracking for UAV swarm systems with switching directed topologies[J]. IEEE Transactions on Neural Networks and Learning Systems, 2019, 30(12): 3674-3685.
16 刘伟, 周绍磊, 祁亚辉, 等. 有向切换通信拓扑下多无人机分布式编队控制[J]. 控制理论与应用, 2015, 32(10): 1422-1427.
Liu Wei, Zhou Shao-lei, Qi Ya-hui, et al. Distributed formation control for multiple unmanned aerial vehicles with directed switching communication topologies[J]. Control Theory and Applications, 2015, 32(10): 1422-1427.
17 Chris G, Gordon F R. Algebraic Graph Theory[M]. New York, NY: Springer Science & Business Media, 2013.
18 Chen F, Jiang R, Zhang K, et al. Robust backstepping sliding-mode control and observer-based fault estimation for a quadrotor UAV[J]. IEEE Transactions on Industrial Electronics. 2016, 63(8): 5044-5056.
19 Zhang C, Yang G. Event-Triggered adaptive output feedback control for a class of uncertain nonlinear systems with actuator failures[J]. IEEE Transactions on Cybernetics.2020, 50(1): 201-210.
20 Zou W, Zhou C, Guo J, et al. Global adaptive leaderfollowing consensus for second-order nonlinear multiagent systems with switching topologies[J]. IEEE Transactions on Circuits and Systems II: Express Briefs, 2021, 68(2): 702-706.
21 徐振, 李胜, 陈庆伟, 等. 采用时延状态观测器的旋翼无人机自适应编队控制[J].西安交通大学学报,2019, 53(12): 161-169.
Xu Zhen, Li Sheng, Chen Qing-wei, et al. An adaptive formation control method of rotorcrafts based on delay state observers[J]. Journal of Xi'an Jiaotong University, 2019, 53(12): 161-169.
22 熊志豪, 邓涛, 郑宇惟, 等. 基于状态观测器的四旋翼无人机轨迹跟踪控制[J/OL]. [2022-06-08].
23 窦立谦, 杨闯, 王丹丹, 等. 基于状态观测器的多无人机编队跟踪控制[J].天津大学学报: 自然科学与工程技术版, 2019, 52(1): 90-97.
Dou Li-qian, Yang Chuang, Wang Dan-dan, et al. State observer-based formation tracking control for multiple quadrotors[J]. Journal of Tianjin University(Science and Technology), 2019, 52(1): 90-97.
[1] 徐勇军, 李元春, 赵晓晖. 基于期望关节角补偿的车载液压刚柔机械臂建模及轨迹跟踪控制[J]. 吉林大学学报(工学版), 2013, 43(05): 1367-1374.
[2] 刘姝阳, 刘克平, 李元春. 基于耦合滑模面的机械臂操作柔性负载系统分布参数控制[J]. 吉林大学学报(工学版), 2013, 43(01): 267-272.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
版权所有 © 《吉林大学学报(工学版)》编辑部
地址：长春市人民大街5988号　电话：+86-431-85095297　传真：+86-431-85094074　E-mail: xbgxb@jlu.edu.cn
本系统由北京玛格泰克科技发展有限公司设计开发