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Real-time capable nonlinear pantograph models using local model networks in state-space configuration

机译:在状态空间配置中使用局部模型网络的实时非线性受电弓模型

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Abstract: Modern pantograph current collectors for high-speed trains are mechatronic systems that are increasingly equipped with active control to maximize their dynamic performance. To realize a high-quality contact, decrease wear, and increase speed, it is necessary to use high-fidelity co-simulation and hardware-in-the-loop (HiL) testing tools, as well as modern model-based control (MBC) concepts. In all these areas, efficient, real-time-capable and accurate models of the pantograph dynamics are required. This paper proposes two different real-time-capable nonlinear pantograph models based on the local model network (LMN) methodology, intended for utilization in co-simulation and control design. They are identifiable by measurement data and applicable for different pantograph geometries. The proposed model structures attain significant improvements in accuracy compared to classical models via global linearization, and they are highly computationally efficient.
机译:摘要:用于高速列车的现代受电弓集电器是机电一体化系统,越来越多地配备主动控制以最大化其动态性能。为了实现高质量的接触,减少磨损并提高速度,必须使用高保真协同仿真和硬件在环(HiL)测试工具,以及现代的基于模型的控制(MBC) )的概念。在所有这些领域中,都需要高效,实时且精确的受电弓动力学模型。本文基于局部模型网络(LMN)方法,提出了两种不同的具有实时能力的非线性缩放模型,旨在用于协同仿真和控制设计中。它们可以通过测量数据识别,并适用于不同的受电弓几何形状。与通过全局线性化的经典模型相比,所提出的模型结构在准确性上有显着提高,并且计算效率很高。

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