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无人机机载雷达作业的航线控制优化研究

Research on route control optimization of UAV airborne radar operation
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摘要 对无人机机载雷达作业的航线控制优化方案进行了研究,以山地多旋翼无人机作业航线的精准控制方法为例,设计了山地无人机作业整体流程。首先,设计了由测绘环节、三维航线生成模块、及山地航线控制环节组成的山地无人机作业整体流程;然后对关键环节即山地航线控制进行研究与设计,其中,基于拓展卡尔曼滤波高度融合位置估计采用RTK定位技术来获取无人机的GPS坐标数据,然后通过数据融合实现无人机位置估计;实时山地航线控制主要由内环模糊自整定PID参数控制器来实现对山地无人机作业的航线控制;最后,分别对关键环节的方法以及整体山地无人机作业航线机控制精度进行测试。测试结果表明:设计了高度位置估计与实时山地航线位置控制方法能够满足优化的需要,且上升航点与下降航点的平均误差相比于传统PID控制器产生的误差分别降低了0.6 m与0.2 m以上,大大提高了山地无人机作业航线的精准度。 In this paper,the route control optimization scheme of UAV airborne radar operation is studied,and the accurate control method of mountain multi-rotor plant protection UAV operation route is selected as an example to design the overall operation process of mountain UAV operation.Firstly,the overall operation process of mountain UAV is designed,which consists of surveying and mapping,3D route generation module,and mountain route control.Then,the key link,namely mountain route control,is studied and designed,among which,based on extended Kalman filter highly fused position estimation,RTK positioning technology is used to obtain the GPS coordinate data of the UAV,and then the UAV position estimation is realized through data fusion.Real-time mountain route control is mainly realized by the inner loop fuzzy autotuning PID parameter controller to realize the route control of mountain UAV operations.Finally,the methods of key links and the control accuracy of the overall mountain UAV operation route were tested respectively.The test results show that the height position estimation and real-time mountain route position control methods designed in this paper can meet the optimization needs of this paper,and the average error of the ascending and descending waypoints is reduced by more than 0.6m and 0.2m,respectively,compared with the errors generated by the traditional PID controller,which greatly improves the accuracy of the mountain UAV operation route.
作者 史佳豪 鲁健 黎娟 SHI Jiahao;LU Jian;LI Juan(Xi’an Aeronautical Polytechnic Institute,Xi’an 710089,China;Chinese People's Liberation Army 1001st Factory,Xi’an 710100,China)
出处 《自动化与仪器仪表》 2023年第8期150-154,共5页 Automation & Instrumentation
基金 陕西省十三五规划课题《基于企业实际生产任务为载体的产学研用一体化技术技能平台实践研究》(SGH20Y1648) 西安航空职业技术学院校级课题《无人机激光雷达技术实际场景应用研究》(21XHTD-05) 西安航空职业技术学院2021年度科技创新团队《无人机贴近摄影测量技术创新团队》(KJTD21-001)。
关键词 无人机 航线控制 卡尔曼滤波 PID控制器 drone route control kalman filter PID controller
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