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输入受限下多无人机三维协同路径跟踪控制

刘荣华 刘树光 张博洋 王欢 李伟

刘荣华, 刘树光, 张博洋, 等 . 输入受限下多无人机三维协同路径跟踪控制[J]. 北京航空航天大学学报, 2022, 48(6): 1038-1049. doi: 10.13700/j.bh.1001-5965.2020.0701
引用本文: 刘荣华, 刘树光, 张博洋, 等 . 输入受限下多无人机三维协同路径跟踪控制[J]. 北京航空航天大学学报, 2022, 48(6): 1038-1049. doi: 10.13700/j.bh.1001-5965.2020.0701
LIU Ronghua, LIU Shuguang, ZHANG Boyang, et al. 3D cooperative path following control of multi-UAVs with input saturation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(6): 1038-1049. doi: 10.13700/j.bh.1001-5965.2020.0701(in Chinese)
Citation: LIU Ronghua, LIU Shuguang, ZHANG Boyang, et al. 3D cooperative path following control of multi-UAVs with input saturation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2022, 48(6): 1038-1049. doi: 10.13700/j.bh.1001-5965.2020.0701(in Chinese)

输入受限下多无人机三维协同路径跟踪控制

doi: 10.13700/j.bh.1001-5965.2020.0701
基金项目: 

国家自然科学基金 61973253

国防科技重点实验室基金 6142219200301

航空科学基金 20155896025

详细信息
    通讯作者:

    刘树光,E-mail: dawny418@126.com

  • 中图分类号: V221+.3

3D cooperative path following control of multi-UAVs with input saturation

Funds: 

National Natural Science Foundation of China 61973253

National Defense Science and Technology Key Laboratory Foundation of China 6142219200301

Aeronautical Science Foundation of China 20155896025

More Information
  • 摘要:

    针对多无人机在三维空间的协同路径跟踪问题,设计了基于反步法的协同控制器。考虑无人机在飞行过程中的输入饱和问题,加入辅助控制系统,以确保系统在输入受限下仍能保持良好的控制性能。将无人机六自由度非线性模型反馈线性化处理,同时考虑无人机飞行时受到的外界不确定扰动及自身模型存在的未建模动态,利用径向基函数在线估计补偿,提高了系统的鲁棒性和抗干扰能力。为了解决反步法需要对虚拟控制量求导导致的控制器复杂问题,引入一阶滤波器,避免对虚拟控制量的求导。利用图论解决无人机机间通信问题,基于一致性理论实现了多无人机的协同控制。基于Lyapunov稳定性理论,证明了系统的稳定性,仿真结果表明,所设计的路径跟踪协同控制器能够达到良好的协同跟踪控制效果。

     

  • 图 1  无人机模型

    Figure 1.  UAV model

    图 2  控制结构

    Figure 2.  Control architecture

    图 3  无人机编队通信网络

    Figure 3.  Graph induced by communication network of UAVs

    图 4  考虑外界扰动后2类控制器控制效果对比

    Figure 4.  Comparison of control effects of two kinds of controllers after considering external disturbance

    图 5  考虑外界扰动后2类控制器路径跟踪误差

    Figure 5.  Two kinds of controller path tracking errors after external disturbance are considered

    图 6  神经网络对不确定项逼近效果

    Figure 6.  Neural network approximation performance to uncertain terms

    图 7  考虑输入受限前后控制输入对比

    Figure 7.  Comparison of control input before and after considering input saturation

    图 8  协同跟踪控制效果

    Figure 8.  Cooperative path following result

    图 9  协同误差

    Figure 9.  Path variables coordination errors

    图 10  编队协同飞行速度

    Figure 10.  Cooperative speed of each UAV on each axis

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出版历程
  • 收稿日期:  2020-12-18
  • 录用日期:  2021-03-05
  • 网络出版日期:  2022-06-20
  • 整期出版日期:  2022-06-20

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