Estimating the UAV moments of inertia directly from its flight data

J. Muliadi, Rizki Langit, B. Kusumoputro
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引用次数: 4

Abstract

This article proposes a practical new method to obtain the moment of inertia of UAV, named ARES. The ARES method simultaneously determined all the elements of UAV's Tensor of Inertia, i.e. the moments and the products of inertia through algebraic solving. The ARES method directly uses the UAV Flight Data to accommodate accuracy issues of modeling such as vehicle's geometrical imperfection; manufacturing defect, any non-symmetrical due component placement, etc. This proposed method was applicable for various purposes of UAV modeling e.g. flight control design, flight dynamics analysis, etc. Conventionally, UAV moments of inertia were estimated by tabulating, CAD-based, or pendulum method. Since these existing methods were constrained by the accuracy and practical issues, we develop the ARES method which using the UAV's flight data to resolve both issues. After undergone appropriate mathematical strategies, the ARES produce a linear construction for algebraic solving technique. The implementation the proposed method in the quadrotor flight data showing that ARES are successfully measured the asymmetrical terms which important for nonlinear controlling, that previously neglected by the conventional methods. Thus, the ARES estimates the UAV Tensor of Inertia in holistic, sophisticated and practical fashion.
直接从飞行数据估计无人机的转动惯量
本文提出了一种实用的获取无人机惯性矩的新方法——ARES。ARES方法通过代数求解,同时确定了无人机惯性张量的所有要素,即惯性矩和惯性积。ARES方法直接使用无人机飞行数据来适应建模精度问题,如飞行器的几何缺陷;制造缺陷,任何不对称的组件放置等。该方法适用于无人机的飞行控制设计、飞行动力学分析等多种建模目的。传统上,无人机的惯性矩是通过制表、基于cad或摆锤方法估计的。针对现有方法存在的精度和实用性问题,提出了利用无人机飞行数据的ARES方法。在经过适当的数学策略后,ARES产生了一种线性构造的代数求解技术。在四旋翼飞行数据中的应用表明,该方法成功地测量了非对称项,而非对称项对非线性控制非常重要,而传统方法忽略了这些项。因此,ARES对无人机惯性张量进行了全面、精密和实用的估计。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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