论文标题
使用具有自适应步长的多变量极值寻求的飞行内范围优化多次驱动器
In-flight range optimization of multicopters using multivariable extremum seeking with adaptive step size
论文作者
论文摘要
有限的飞行范围是多跨人的常见问题。为了减轻这个问题，我们提出了一种方法，可以在飞行给定路径达到最长飞行范围时找到多功能器的最佳速度和标题。基于具有自适应步长大小的新型多变量超级寻求控制器，方法（a）不需要车辆的任何功耗模型，（b）可以适应未知的干扰，（c）可以在线执行，并且（d）比标准极点寻求控制器的收敛速度更快。我们进行了室内实验，以在不同的有效载荷和初始条件下验证该方法的有效性，并表明它能够比标准的超级寻求控制器快30％以上。此方法对于诸如包装交付等应用程序特别有用，在包装交付中，有效载荷的大小和重量因不同的交付而有所不同，而车辆的功耗很难建模。
Limited flight range is a common problem for multicopters. To alleviate this problem, we propose a method for finding the optimal speed and heading of a multicopter when flying a given path to achieve the longest flight range. Based on a novel multivariable extremum seeking controller with adaptive step size, the method (a) does not require any power consumption model of the vehicle, (b) can adapt to unknown disturbances, (c) can be executed online, and (d) converges faster than the standard extremum seeking controller with constant step size. We conducted indoor experiments to validate the effectiveness of this method under different payloads and initial conditions, and showed that it is able to converge more than 30% faster than the standard extremum seeking controller. This method is especially useful for applications such as package delivery, where the size and weight of the payload differ for different deliveries and the power consumption of the vehicle is hard to model.
