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Accurate Modeling and Robust Hovering Control for a Quad-rotor VTOL Aircraft

机译:四旋翼垂直起降飞机的精确建模和鲁棒悬停控制

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摘要

Quad-robot type (QRT) unmanned aerial vehicles (UAVs) have been developed for quick detection and observation of the circumstances under calamity environment such as indoor fire spots. The UAV is equipped with four propellers driven by each electric motor, an embedded controller, an Inertial Navigation System (INS) using three rate gyros and accelerometers, a CCD (Charge Coupled Device) camera with wireless communication transmitter for observation, and an ultrasonic range sensor for height control. Accurate modeling and robust flight control of QRT UAVs are mainly discussed in this work. Rigorous dynamic model of a QRT UAV is obtained both in the reference and body frame coordinate systems. A disturbance observer (DOB) based controller using the derived dynamic models is also proposed for robust hovering control. The control input induced by DOB is helpful to use simple equations of motion satisfying accurately derived dynamics. The developed hovering robot shows stable flying performances under the adoption of DOB and the vision based localization method. Although a model is incorrect, DOB method can design a controller by regarding the inaccurate part of the model and sensor noises as disturbances. The UAV can also avoid obstacles using eight IR (Infrared) and four ultrasonic range sensors. This kind of micro UAV can be widely used in various calamity observation fields without danger of human beings under harmful environment. The experimental results show the performance of the proposed control algorithm.
机译:已经开发出四机器人(QRT)无人机(UAV),用于快速检测和观察灾难环境下的情况,例如室内火点。该无人机配备有由每个电动机驱动的四个螺旋桨,一个嵌入式控制器,一个使用三个速率陀螺仪和加速度计的惯性导航系统(INS),一个带有无线通信发射器的CCD(电荷耦合器件)摄像机以及用于观察的超声波范围高度控制传感器。这项工作主要讨论QRT无人机的精确建模和鲁棒飞行控制。在参考坐标系和车架坐标系中均获得了QRT无人机的严格动态模型。还提出了使用派生的动态模型的基于干扰观测器(DOB)的控制器进行鲁棒悬停控制。 DOB引发的控制输入有助于使用满足精确导出的动力学的简单运动方程。在采用DOB和基于视觉的定位方法的情况下,开发的悬停机器人表现出稳定的飞行性能。尽管模型不正确,但是DOB方法可以通过将模型的不准确部分和传感器噪声视为干扰来设计控制器。无人机还可以使用八个IR(红外)和四个超声距离传感器避开障碍物。这种微型无人机可广泛用于各种灾害观测领域,而在有害环境下不会对人类造成危害。实验结果表明了该控制算法的性能。

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