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Fault tolerant attitude sensing and force feedback control for unmanned aerial vehicles.

机译:无人机的容错姿态感测和力反馈控制。

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Two aspects of an unmanned aerial vehicle are studied in this work. One is fault tolerant attitude determination and the other is to provide force feedback to the joy-stick of the UAV so as to prevent faulty inputs from the pilot. Determination of attitude plays an important role in control of aerial vehicles. One way of defining the attitude is through Euler angles. These angles can be determined based on the measurements of the projections of the gravity and earth magnetic fields on the three body axes of the vehicle. Attitude determination in unmanned aerial vehicles poses additional challenges due to limitations of space, payload, power and cost. Therefore it provides for almost no room for any bulky sensors or extra sensor hardware for backup and as such leaves no room for sensor fault issues either. In the face of these limitations, this study proposes a fault tolerant computing of Euler angles by utilizing multiple different computation methods, with each method utilizing a different subset of the available sensor measurement data. Twenty-five such methods have been presented in this document. The capability of computing the Euler angles in multiple ways provides a diversified redundancy required for fault tolerance. The proposed approach can identify certain sets of sensor failures and even separate the reference fields from the disturbances. A bank-to-turn maneuver of the NASA GTM UAV is used to demonstrate the fault tolerance provided by the proposed method as well as to demonstrate the method of determining the correct Euler angles despite interferences by inertial acceleration disturbances.;Attitude computation is essential for stability. But as of today most UAVs are commanded remotely by human pilots. While basic stability control is entrusted to machine or the on-board automatic controller, overall guidance is usually with humans. It is therefore the pilot who sets the command/references through a joy-stick. While this is a good compromise between complete automation and complete human control, it still poses some unique challenges.;Pilots of manned aircraft are present inside the cockpit of the aircraft they fly and thus have a better feel of the flying environment and also the limitations of the flight. The same might not be true for UAV pilots stationed on the ground. A major handicap is that visual feedback is the only one available for the UAV pilot. An additional parameter like force feedback on the remote control joy-stick can help the UAV pilot to physically feel the limitation of the safe flight envelope. This can make the flying itself easier and safer. A method proposed here is to design a joy-stick assembly with an additional actuator. This actuator is controlled so as to generate a force feedback on the joy-stick. The control developed for this system is such that the actuator allows free movement for the pilot as long as the UAV is within the safe flight envelope. On the other hand, if it is outside this safe range, the actuator opposes the pilot's applied torque and prevents him/her from giving erroneous commands to the UAV.
机译:在这项工作中研究了无人机的两个方面。一种是容错姿态确定,另一种是向无人机的操纵杆提供力反馈,以防止飞行员输入错误。姿态的确定在飞行器的控制中起着重要的作用。定义姿态的一种方法是通过欧拉角。这些角度可以基于重力和地磁场在车辆的三个车身轴线上的投影的测量值来确定。由于空间,有效载荷,功率和成本的限制,无人飞行器中的姿态确定提出了另外的挑战。因此,它几乎没有空间容纳任何笨重的传感器或额外的传感器硬件用于备份,因此也没有留出任何空间解决传感器故障问题。面对这些局限性,这项研究提出了一种利用多种不同的计算方法对欧拉角进行容错计算的方法,每种方法都利用了可用传感器测量数据的不同子集。在该文件中已经提出了二十五个这样的方法。以多种方式计算欧拉角的能力提供了容错所需的多样化冗余。所提出的方法可以识别出某些传感器故障集,甚至可以将参考场与干扰区分开。 NASA GTM UAV的转弯操作被用来证明所提出的方法提供的容错能力,并证明了尽管受到惯性加速度干扰的干扰也能确定正确的欧拉角的方法。稳定性。但是到目前为止,大多数无人机都是由飞行员远程指挥的。虽然将基本的稳定性控制委托给机器或机载自动控制器,但总体指导通常由人工完成。因此,是飞行员通过操纵杆设置命令/参考。虽然这是完全自动化和完全人为控制之间的良好折衷,但仍然提出了一些独特的挑战。;有人驾驶飞机的飞行员位于他们飞行的飞机驾驶舱内,因此对飞行环境和局限性有更好的感觉飞行的对于驻扎在地面的无人机飞行员而言,情况可能并非如此。一个主要的障碍是视觉反馈是无人机飞行员唯一可用的反馈。诸如遥控操纵杆上的力反馈之类的附加参数可以帮助无人机飞行员实际感受到安全飞行范围的局限性。这样可以使飞行本身更轻松,更安全。这里提出的一种方法是设计带有附加致动器的操纵杆组件。控制该致动器以便在操纵杆上产生力反馈。为此系统开发的控制系统是,只要无人机在安全飞行范围之内,执行器就可以让飞行员自由运动。另一方面,如果超出该安全范围,则执行器会对抗飞行员施加的扭矩,并防止其向无人机发出错误的命令。

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