基于拉格朗日方程的高空救援梯柔性多体系统建模

IF 1.8 4区 数学 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Mathematical and Computer Modelling of Dynamical Systems Pub Date : 2021-01-02 DOI:10.1080/13873954.2021.1918175
Simon Densborn, O. Sawodny
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引用次数: 5

摘要

摘要由于重量和刚度有限,大型机器人在运行过程中容易受到结构振荡的影响。在本出版物中,基于拉格朗日形式推导了一个空中救援梯的垂直动力学模型,作为大型柔性机器人的应用实例。该模型由五个柔性段组成,每个段使用任意数量的柔性模式。由于伸缩元件之间的互连类型而产生的运动回路通过所选择的假定模式隐式求解。线性化的系统矩阵直接且非常有效地从模型中提取。在最终的建模过程中,机械手仅通过其位置和方向运动学来描述,因此适应不同类型的机械手是简单的。根据真实世界的测量数据进行验证,证实了导出模型的高精度。
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Flexible multibody system modelling of an aerial rescue ladder using Lagrange’s equations
ABSTRACT Due to limited weight and stiffness, large-scale robots are susceptible to structural oscillations during operation. In this publication, a model for the vertical dynamics of an aerial rescue ladder as an application example for large scale flexible robots is derived based on the Lagrange formalism. The model consists of five flexible segments, each using an arbitrary number of flexible modes. Kinematic loops occurring due to the type of interconnection between the telescopic elements are implicitly solved by the chosen assumed modes. Linearized system matrices are extracted from the model directly and very efficiently. In the resulting modelling process, the manipulator is solely described by its position and orientation kinematics and thus an adaption to different kinds of manipulators is straightforward. A validation against real world measurement data confirms the high accuracy of the derived model.
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来源期刊
CiteScore
3.80
自引率
5.30%
发文量
7
审稿时长
>12 weeks
期刊介绍: Mathematical and Computer Modelling of Dynamical Systems (MCMDS) publishes high quality international research that presents new ideas and approaches in the derivation, simplification, and validation of models and sub-models of relevance to complex (real-world) dynamical systems. The journal brings together engineers and scientists working in different areas of application and/or theory where researchers can learn about recent developments across engineering, environmental systems, and biotechnology amongst other fields. As MCMDS covers a wide range of application areas, papers aim to be accessible to readers who are not necessarily experts in the specific area of application. MCMDS welcomes original articles on a range of topics including: -methods of modelling and simulation- automation of modelling- qualitative and modular modelling- data-based and learning-based modelling- uncertainties and the effects of modelling errors on system performance- application of modelling to complex real-world systems.
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