多旋翼无人机模型预测抗扰避障制导
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作者单位:

(南京航空航天大学 自动化学院, 江苏 南京 211100)

作者简介:

兰庆湘(1997—),男,河南南阳人,硕士研究生,E-mail:lanqx1003@qq.com; 陈谋(通信作者),男,教授,博士,博士生导师,E-mail:chenmou@nuaa.edu.cn

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中图分类号:

TP273

基金项目:

国家自然科学基金资助项目(61803207,U2013201,62103188);江苏省自然科学基金资助项目(BK20210284);江苏省博士后科研计划资助项目(2021K289B)


Model predictive based disturbance rejection and obstacle avoidance guidance for multi-rotor unmanned aerial vehicle
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(College of Automation Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211100, China)

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    摘要:

    多旋翼无人机的自主避障是完成复杂任务的基础,避障的效果直接影响无人机执行任务的效能。针对存在外部扰动的无人机避障问题,提出了一种基于模型预测的抗扰避障制导律设计方法。通过设计干扰观测器对系统动态中的外部干扰进行了估计,并基于李雅普诺夫函数方法设计辅助制导律用于建立稳定性约束条件。结合前两者与模型预测控制,在模型预测控制优化求解中考虑无人机与障碍物的关系,根据所设计的制导律求解水平线速度与偏航角速度指令实现无人机的避障。对所提出的避障制导律进行数值仿真和实物飞行验证,结果表明了所提方法的有效性。

    Abstract:

    The autonomous obstacle avoidance of UAV (unmanned aerial vehicle) is the basis of completing complex tasks, and the obstacle avoidance performance directly affects the efficiency of UAV performing tasks. Aiming at the obstacle avoidance problem of UAV with external disturbance, a design method of anti-disturbance and obstacle avoidance guidance law based on model prediction was proposed. The disturbance observer was designed to estimate the external disturbance in the system dynamics, and the auxiliary guidance law was designed based on Lyapunov function method to establish the stability constraints. Combining the first two with MPC (model predictive control), the relationship between UAV and obstacles was considered in the MPC optimization solution, and the horizontal linear velocity and yaw angular velocity commands were solved according to the designed guidance law to realize the obstacle avoidance of UAV. The numerical simulation and physical flight verification of the proposed obstacle avoidance guidance law show the effectiveness of the proposed method.

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兰庆湘,陈谋,雍可南.多旋翼无人机模型预测抗扰避障制导. Model predictive based disturbance rejection and obstacle avoidance guidance for multi-rotor unmanned aerial vehicle[J].国防科技大学学报,2022,44(4):32-42.

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  • 收稿日期:2021-11-01
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  • 在线发布日期: 2022-07-20
  • 出版日期: 2022-08-28
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