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性能约束下的四旋翼无人机协同吊挂系统分布式避碰跟踪控制

陈谋 刘伟 张鹏

陈谋, 刘伟, 张鹏. 性能约束下的四旋翼无人机协同吊挂系统分布式避碰跟踪控制. 自动化学报, 2024, 50(12): 1−15 doi: 10.16383/j.aas.c240349
引用本文: 陈谋, 刘伟, 张鹏. 性能约束下的四旋翼无人机协同吊挂系统分布式避碰跟踪控制. 自动化学报, 2024, 50(12): 1−15 doi: 10.16383/j.aas.c240349
Chen Mou, Liu Wei, Zhang Peng. Distributed collision avoidance tracking control for quadrotor cooperative suspension system under performance constraints. Acta Automatica Sinica, 2024, 50(12): 1−15 doi: 10.16383/j.aas.c240349
Citation: Chen Mou, Liu Wei, Zhang Peng. Distributed collision avoidance tracking control for quadrotor cooperative suspension system under performance constraints. Acta Automatica Sinica, 2024, 50(12): 1−15 doi: 10.16383/j.aas.c240349

性能约束下的四旋翼无人机协同吊挂系统分布式避碰跟踪控制

doi: 10.16383/j.aas.c240349 cstr: 32138.14.j.aas.c240349
基金项目: 国家自然科学基金(U2013201), 江苏省自然科学基金(BK20230883) 资助
详细信息
    作者简介:

    陈谋:南京航空航天大学自动化学院教授. 主要研究方向为非线性系统控制, 飞行控制和火力控制. E-mail: chenmou@nuaa.edu.cn

    刘伟:南京航空航天大学自动化学院博士研究生. 主要研究方向为非线性系统控制和四旋翼无人机吊挂控制. 本文通信作者. E-mail: wei-lau@nuaa.edu.cn

    张鹏:南京航空航天大学自动化学院讲师. 主要研究方向为自适应动态规划, 随机网络控制和博弈论控制及其在航天系统中的应用. E-mail: zpengll@nuaa.edu.cn

Distributed Collision Avoidance Tracking Control for Quadrotor Cooperative Suspension System Under Performance Constraints

Funds: Supported by National Natural Science Foundation of China (U2013201) and Jiangsu Province Natural Science Foundation (BK20230883)
More Information
    Author Bio:

    CHEN Mou Professor at the College of Automation Engineering, Nanjing University of Aeronautics and Astronautics. His research interest covers nonlinear system control, flight control, and fire control

    LIU Wei Ph.D. candidate at the College of Automation Engineering, Nanjing University of Aeronautics and Astronautics. His research interest covers nonlinear system control and QUAV suspension control. Corresponding author of this paper

    ZHANG Peng Lecturer at the College of Automation Engineering, Nanjing University of Aeronautics and Astronautics. His research interest covers adaptive dynamic programming, stochastic network control, and game-theoretic control and their applications in aerospace systems

  • 摘要: 针对存在未知扰动的多四旋翼无人机协同吊挂系统(Multi-quadrotor cooperative supension system, MQCSS), 提出一种具有避碰和性能约束的分布式自适应积分反步跟踪控制(Distributed adaptive integral backstepping tracking control, DAIBC)方法. 首先, 设计新型的有限时间性能函数和人工势函数分别用于处理负载的跟踪约束和四旋翼无人机(Quadrotor unmanned aerial vehicle, QUAV)之间的避碰问题. 然后, 构造一种积分型的辅助变量并结合动态面技术设计反步控制器, 实现四旋翼无人机的分布式编队运输负载. 同时, 将动态面技术与自适应调节机制相结合, 对系统存在的未知干扰进行抑制. 接着, 给出严格的Lyapunov稳定性分析, 证明闭环系统所有信号的最终一致有界. 最后, 通过数值对比仿真和实飞实验结果验证了所提方法的有效性.
  • 图  1  多四旋翼无人机协同吊挂系统示意图

    Fig.  1  The schematic diagram of MQCSS

    图  2  TPF和FTPF的时间响应曲线

    Fig.  2  The time response curves of TPF and FTPF

    图  3  多四旋翼无人机协同吊挂系统的通信拓扑结构

    Fig.  3  Communication topology structure for MQCSS

    图  4  数值仿真: 负载跟踪误差的性能约束

    Fig.  4  Numerical simulation: Performance constraint for load tracking error

    图  7  数值仿真: MQCSS的控制响应

    Fig.  7  Numerical simulation: Control response of MQCSS

    图  5  数值仿真: QUAV分布式编队跟踪误差的2范数和QUAV之间的欧氏距离 $ ||d_{ij}|| $

    Fig.  5  Numerical simulation: The 2-morm for QUAV distributed formation tracking errors and Euclidean distance $ ||d_{ij}|| $ between QUAVs

    图  6  数值仿真: 控制输入$ u_i $

    Fig.  6  Numerical simulation: Control inputs $ u_i $

    图  8  多四旋翼无人机协同吊挂系统的实验测试平台

    Fig.  8  Experimental testbed for MQCSS

    图  9  实验验证: 负载跟踪误差的性能约束

    Fig.  9  Experimental verification: Performance constraint for load tracking error

    图  13  实验验证: MQCSS的控制响应

    Fig.  13  Experimental verification: Control response of MQCSS

    图  10  实验验证: QUAV分布式编队跟踪误差的2范数

    Fig.  10  Experimental verification: The 2-norm for QUAV distributed formation tracking errors

    图  11  实验验证: QUAV之间的欧氏距离 $||d_{ij}||$

    Fig.  11  Experimental verification: Euclidean distance $||d_{ij}||$ between QUAVs

    图  12  实验验证: MQCSS的控制信号 $u_i$

    Fig.  12  Experimental verification: Control signals $u_i$ for MQCSS

    表  1  图1中符号的定义

    Table  1  The definitions of the symbols in Fig. 1

    符号 定义
    $ {{{P}}_i} = {\left[ {x_i,\;y_i,\;z_i} \right]^{\rm T}} $ 第$ i $架QUAV的位置
    $ {{{P}}_L} = {\left[ {x_L,\;y_L,\;z_L} \right]^{\rm T}} $ 负载的位置
    $ R_i $, $ R_L $ 第$ i $架QUAV和负载的旋转矩阵
    $ q_i $ 第$ i $根连接杆的单位方向向量
    $ r_i $ 负载质心到第$ i $个连接点的向量
    $ m_{i} $, $ m_L $ 第$ i $架QUAV和负载的质量
    $ J_L $ 负载的惯性矩阵
    $ l_i $ 第$ i $根连接杆的长度
    下载: 导出CSV

    表  2  数值仿真结果的定量分析

    Table  2  Quantitative analysis of numerical simulation results

    控制方法 TBC TBC-TPF DAIBC-FTPF
    $ \Upsilon_{e_{L}} $ 0.1602 0.1136 0.0912
    $ E $ $ 1.528\;3\times10^5 $ $ 1.527\;9\times10^5 $ $ 1.502\;9\times10^5 $
    下载: 导出CSV

    表  3  模型参数、控制器参数、初始条件以及参考轨迹

    Table  3  Model parameters, controller parameters, initial conditions, and reference trajectories

    参数项 数值
    模型参数 $ m_i=0.285\;({\rm kg}) $, $ m_L=0.245\;({\rm kg}), \;l_i=0.75\;({\rm m}) $, $ r_1=[0.75, \;0, \;0.1]^{\rm T}\;({\rm m}) $, $ r_2=[0, \;-0.75, \;0.1]^{\rm T}\;({\rm m}) $
    $ r_3=[-0.75, \;0, \;0.1]^{\rm T}\;({\rm m}) $, $ r_4=[0, \;0.75.0.1]^{\rm T}\;({\rm m}) $, $ J_L={\rm diag}\{1.5, \;4.6, \;0.08\}10^{-2}\;({\rm kg\cdot m^2}) $
    控制器参数 $ T=5 $, $ a=[0.75, \;0.75, \;0.75, \;0.75, \;0.75, \;0.75]^{\rm T} $, $ \rho_{L0}=[0.5, \;0.5, \;0.5, \;0.25, \;0.25, \;0.25]^{\rm T} $
    $ \rho_{L_\infty}=[0.1, \;0.1, \;0.1, \;0.1, \;0.1, \;0.1]^{\rm T} $, $ \Xi_{{\rm max}}=0.6 $, $ \Xi_{{\rm min}}=0.3 $, $ \sigma_{ij}=1 $, $ \beta_{id}^*=1 $
    $ k_L={\rm diag}\{1, \;1, \;1, \;1, \;1, \;1\} $, $ \beta_L={\rm diag}\{1, \;1, \;1, \;1, \;1, \;1\} $, $ K_1={\rm diag}\{5, \;5, \;5, \;5, \;5, \;5\} $, $ K_2={\rm diag}\{10, \;10, \;10, \;10, \;10, \;10\} $
    $ \gamma_{L}={\rm diag}\{0.1, \;0.1, \;0.1, \;0.1, \;0.1, \;0.1\} $, $ \gamma_{1i}=\gamma_{2i}={\rm diag}\{0.1, \;0.1, \;0.1\} $, $ \ell=0.01 $, $ \Upsilon_{L}=\Upsilon_{i}=1 $, $ \zeta_L=\zeta_i=2 $
    $ k_i={\rm diag}\{1, \;1, \;1\} $, $ \beta_i={\rm diag}\{1, \;1, \;1\} $, $ K_{1i}={\rm diag}\{5, \;5, \;5\} $, $ K_{2i}={\rm diag}\{10, \;10, \;10\} $
    初始条件 $ P_{L}(0)=[1.25, \;0.25, \;0.25]^{\rm T}\;({\rm m}) $, $ \Theta_{L}(0)=[0, \;0, \;0]^{\rm T}\;({\rm rad}) $, $ P_{i}(0)=P_L(0)+r_i-l_i[0, \;0, \;-1]^{\rm T}\;({\rm m}) $
    参考轨迹 $ P_{Ldx}=1.5-0.15t\; ({\rm m}) $, $ P_{Ldy}=0\; ({\rm m}) $, $ P_{Ldz}=0.5\; ({\rm m}) $, $ \Theta_{Ld}=[0, \;0, \;0]^{\rm T}\;({\rm rad}) $
    下载: 导出CSV
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  • 收稿日期:  2024-06-17
  • 录用日期:  2024-08-27
  • 网络出版日期:  2024-11-01

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