旋翼无人机航迹控制半实物仿真系统设计
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摘要
研究旋翼无人机控制半实物仿真的问题,将旋翼无人机飞控接入仿真计算机,遥控器控制或设置自主飞行模拟户外实验时旋翼无人机飞行性能,但是目前较少考虑旋翼无人机个体具体参数结合航迹仿真。针对小型旋翼无人机从起飞到降落过程中的关键动力学和运动学问题,建立了无人机运动过程中的六自由度动力学模型和运动学模型,构造了小型旋翼无人机半实物仿真框架。结合小型旋翼无人机飞行环境因素和无人机GPS信息等传感器信息模拟,对小型旋翼无人机建立了基于JMAVSim的可视化半实物仿真模型。实验通过地面站预先设置小型旋翼无人机航迹,设置无人机自主飞行,对比小型旋翼无人机半实物仿真航迹,两者高度吻合。上述旋翼无人机半实物仿真系统使用真实飞行源码,结合地面站QGroundControl提供的仿真模型,与真实飞行高度相似,具有操作便捷,适用性广的特点。
Research hardware-in-loop simulation of rotor UAV control problem, access flight control unit to the simulation computer, the remote control or set up autonomous flight simulation of outdoor experiment rotor UAV flight performance. But at present, the specific parameters of the rotor uav are combined with the flight trace simulation. Focusing on the key dynamics and kinematics problems of the small rotor unmanned aerial vehicle from takeoff to land, the detail six degrees of freedom dynamics model and kinematics model in view of the motion process of the small rotor unmanned aerial vehicle were built in this article. The simulation framework of the small rotor unmanned aerial vehicle was constructed. In addition, a visual semi-physical simulation model based on JMAVSim was established for the small rotor unmanned aerial vehicle based on the flight environment factor and sensor information simulation such as GPS information. By preseting the track of the small rotor unmanned aerial vehicle in the ground station, the experiment set up the UAV autonomous flight. Contrast of the small rotor unmanned aerial vehicle simulation track shows that they are highly consistent. Combining the real flying source code with the ground the simulation model of station QGroundControl, the hardware-in-the-loop simulation is similar to the real flight altitude, and it has the characteristics of convenient operation and wide applicability.
Research hardware-in-loop simulation of rotor UAV control problem, access flight control unit to the simulation computer, the remote control or set up autonomous flight simulation of outdoor experiment rotor UAV flight performance. But at present, the specific parameters of the rotor uav are combined with the flight trace simulation. Focusing on the key dynamics and kinematics problems of the small rotor unmanned aerial vehicle from takeoff to land, the detail six degrees of freedom dynamics model and kinematics model in view of the motion process of the small rotor unmanned aerial vehicle were built in this article. The simulation framework of the small rotor unmanned aerial vehicle was constructed. In addition, a visual semi-physical simulation model based on JMAVSim was established for the small rotor unmanned aerial vehicle based on the flight environment factor and sensor information simulation such as GPS information. By preseting the track of the small rotor unmanned aerial vehicle in the ground station, the experiment set up the UAV autonomous flight. Contrast of the small rotor unmanned aerial vehicle simulation track shows that they are highly consistent. Combining the real flying source code with the ground the simulation model of station QGroundControl, the hardware-in-the-loop simulation is similar to the real flight altitude, and it has the characteristics of convenient operation and wide applicability.
引文
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[20] 何湘智,王荣春,周伟. 基于MATLAB的无人机六自由度仿真与研究[J]. 机械工程与自动化, 2010,(4):32-34.
[2] 刘延斌,金光. 半实物仿真技术的发展现状[J ]. 光机电信息, 2003,(1): 27-32.
[3] 刘亮亮,等. 无人机半实物仿真系统研究[J]. 兵工自动化, 2008,27(3):44-45.
[4] S Hanford, L Long, J Horn. A Small Semi-Autonomous Rotary-Wing Unmanned Air Vehicle(UAV)[J]. The Pennsylvania State University, University Park, PA, 16802, 2005:2005-7077.
[5] J Cooper, M A Goodrich. Towards combining UAV and sensor operator roles in UAV-enabled visual search[C]. ACM/IEEE International Conference on Human Robot Interaction, 2008:351-358.
[6] M T Hyland, et al. Simulation-Based Performance Evaluation of Mobile Ad Hoc Routing Protocols in a Swarm of Unmanned Aerial Vehicles[C]. International Conference on Advanced Information NETWORKING and Applications Workshops, 2007:249-256.
[7] P J Bristeau. The Navigation and Control Technology Inside the AR.Drone Micro UAV[C]. World Congress, 2011:1477-1484.
[8] A Mancini, et al. A Framework for Simulation and Testing of UAVs in Cooperative Scenarios[J]. Journal of Intelligent & Robotic Systems, 2009,54(1-3): 307-329.
[9] Aiaa. UAV Flight Simulation: Credibility of Linear Decoupled vs. Nonlinear Coupled Equations of Motion[C]. AIAA Modeling and Simulation Technologies Conference and Exhibit, 2005.
[10] M Selig. Modeling Propeller Aerodynamics and Slipstream Effects on Small UAVs in Realtime[C]. AIAA Atmospheric Flight Mechanics Conference, 2010.
[11] 李会敏,等. 无人机自动着舰半实物仿真系统设计[C]. 中国仿真大会, 2014.
[12] 苏继杰,等. 无人机模拟训练系统的半实物仿真设计[J]. 火力与指挥控制, 2009,34(10):153-155.
[13] 薛鹏,肖前贵,高艳辉. 某无人机飞控系统半实物仿真平台设计[J]. 现代电子技术, 2012,35(13):111-114.
[14] 张凯,等. 基于VC的某型无人机半实物仿真器设计[J]. 仪表技术, 2015,(3):35-37.
[15] 张垚,等. 四旋翼无人机可视化半实物仿真平台研究[J]. 仪器仪表学报, 2012,33(11): 2572-2578.
[16] 臧皖晋. 基于FlightGear的四旋翼无人机半实物仿真系统[J]. 工业控制计算机, 2016,29(8):12-14.
[17] 张翠萍,王宏伦. 一种无人机飞行控制半实物仿真系统[C]. 中国航空学会中俄无人机学术会议, 2007.
[18] 姜杨,魏再民. 某型无人机半实物仿真系统设计与实现[J]. 宇航计测技术, 2014,(6): 42-44.
[19] 王德爽,李刚,杨宁. 某型自转旋翼无人机半实物仿真系统[J]. 兵工自动化, 2014,(4): 22-25.
[20] 何湘智,王荣春,周伟. 基于MATLAB的无人机六自由度仿真与研究[J]. 机械工程与自动化, 2010,(4):32-34.