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Fault tolerant margins of an UAV at uncertain environment

机译:在不确定环境下无人机的容错边缘

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In fault tolerant control, the damaged and healthy states of a sensor output or a control input are captured by using an uncertain parameter. For instance, the control input u(t) resulting from an actuator is modeled au(t) and the healthy and damaged conditions are inferred from a which takes the values ??=1 and ?? in [0, 1), respectively [1-3]. Given a stabilizing controller, a range of ??-values in the interval [0,1) for which the closed loop system would remain stable is referred as the fault-tolerant margin. In this paper, several of these margins are presented when aerodynamic parameter variations due to an uncertain atmospheric condition in an unmanned aerial vehicle (UAV) are present. It is shown that the fault tolerant margins are extremely sensitive to these parameter perturbations. Some perturbation locations can significantly reduce the stable range for parameter values as well as for the fault tolerant margins. An UAV model is considered to illustrate the fault tolerant margins and admissible parameter variations. Secondly, the algorithm applied to compute the fault tolerant margins is used to solve the examples of Professor Ross B Barmish et al [29] and hence the exact stability margins for a two parameter system are illustrated. However, when the number of parameters increases, the algorithm becomes computationally intensive.
机译:在容错控制中,通过使用不确定参数捕获传感器输出的损坏和健康状态或控制输入。例如,由致动器产生的控制输入U(t)被建模Au(t),并且从Au(T)推断出效果的健康和损坏的条件?? = 1和??在[0,1)中,分别[1-3]。给定稳定控制器,闭环系统保持稳定的间隔内的一系列 - 值是稳定的,称为容错余量。在本文中,当存在由于无人驾驶飞行器(UAV)中的不确定大气状况导致的空气动力学参数变化时,呈现了几个这些边距。结果表明,容错的边缘对这些参数扰动非常敏感。一些扰动位置可以显着降低参数值以及容错边距的稳定范围。 UAV模型被认为是为了说明容错的边距和可允许的参数变化。其次,应用于计算容错边缘的算法用于解决罗斯B Barmish等[29]的示例,因此示出了两个参数系统的精确稳定性边缘。但是,当参数的数量增加时,算法变得计算密集。

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