Faculty of Mechatronics and Mechanical Engineering, Kielce University of Technology, Aleja Tysiąclecia Państwa Polskiego 7, 25-314 Kielce, Poland.
Sensors (Basel). 2022 Feb 21;22(4):1677. doi: 10.3390/s22041677.
The most common filters used to determine the angular position of quadrotors are the Kalman filter and the complementary filter. The problem of angular position estimation consist is a result of the absence of direct data. The most common sensors on board UAVs are micro electro mechanical system (MEMS) type sensors. The data acquired from the sensors are processed using digital filters. In the literature, the results of research conducted on the effectiveness of Kalman and complementary filters are known. A significant problem in evaluating the performance of the studied filters was the lack of an arbitrarily determined UAV position. The authors of this paper undertook the task of determining the best filter for a real object. The main objective of this research was to improve the stability of the physical quadrotor. For this purpose, we developed a research method using a laboratory station for testing quadrotor drones. Moreover, using the MATLAB environment, they determined the optimal parameters for the real filter applied using the PX4 software, which is new and has not been considered before in the available scientific literature. It should be mentioned that the authors of this work focused on the analysis of filters most commonly used for flight stabilization, without modifying the structure of these filters. By not modifying the filter structure, it is possible to optimize the existing flight controllers. The main contribution of this study lies in finding the most optimal filter, among those available in flight controllers, for angular position estimation. The special emphasis of our work was to develop a procedure for selecting the filter coefficients for a real object. The algorithm was designed so that other researchers could use it, provided they collected arbitrary data for their objects. Selected results of the research are presented in graphical form. The proposed procedure for improving the embedded filter can be used by other researchers on their subjects.
用于确定四旋翼飞行器角位置的最常用滤波器是卡尔曼滤波器和互补滤波器。角位置估计问题是由于缺乏直接数据而产生的。无人机上最常见的传感器是微机电系统 (MEMS) 类型的传感器。从传感器获取的数据使用数字滤波器进行处理。在文献中，已知对卡尔曼和互补滤波器的有效性进行研究的结果。评估所研究滤波器性能的一个重大问题是缺乏任意确定的无人机位置。本文的作者承担了为实际对象确定最佳滤波器的任务。本研究的主要目标是提高物理四旋翼的稳定性。为此，我们开发了一种使用实验室站测试四旋翼无人机的研究方法。此外，他们使用 MATLAB 环境确定了使用 PX4 软件应用的实际滤波器的最佳参数，该软件是新的，以前在可用的科学文献中没有考虑过。应该提到的是，这项工作的作者专注于分析最常用于飞行稳定的滤波器，而不修改这些滤波器的结构。通过不修改滤波器结构，可以优化现有的飞行控制器。本研究的主要贡献在于找到可用的飞行控制器中最适合角位置估计的滤波器。我们工作的重点特别在于为实际对象开发选择滤波器系数的过程。该算法的设计目的是使其他研究人员能够在为其对象收集任意数据的情况下使用它。以图形形式呈现了选定的研究结果。所提出的改进嵌入式滤波器的程序可以被其他研究人员在他们的课题上使用。
