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Hard real-time multibody simulations using ARM-based embedded systems

机译:使用基于ARM的嵌入式系统进行硬实时多体仿真

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The real-time simulation of multibody models on embedded systems is of particular interest for controllers and observers such as model predictive controllers and state observers, which rely on a dynamic model of the process and are customarily executed in electronic control units. This work first identifies the software techniques and tools required to easily write efficient code for multibody models to be simulated on ARM-based embedded systems. Automatic Programming and Source Code Translation are the two techniques that were chosen to generate source code for multibody models in different programming languages. Automatic Programming is used to generate procedural code in an intermediate representation from an object-oriented library and Source Code Translation is used to translate the intermediate representation automatically to an interpreted language or to a compiled language for efficiency purposes. An implementation of these techniques is proposed. It is based on a Python template engine and AST tree walkers for Source Code Generation and on a model-driven translator for the Source Code Translation. The code is translated from a metalanguage to any of the following four programming languages: Python-Numpy, Matlab, C++-Armadillo, C++-Eigen. Two examples of multibody models were simulated: a four-bar linkage with multiple loops and a 3D vehicle steering system. The code for these examples has been generated and executed on two ARM-based single-board computers. Using compiled languages, both models could be simulated faster than real-time despite the low resources and performance of these embedded systems. Finally, the real-time performance of both models was evaluated when executed in hard real-time on Xenomai for both embedded systems. This work shows through measurements that Automatic Programming and Source Code Translation are valuable techniques to develop real-time multibody models to be used in embedded observers and controllers.
机译:嵌入式系统上多体模型的实时仿真特别受控制器和观察者的关注,例如模型预测控制器和状态观察者,它们依赖于过程的动态模型,通常在电子控制单元中执行。这项工作首先确定了轻松编写用于在基于ARM的嵌入式系统上进行仿真的多实体模型的有效代码所需的软件技术和工具。自动编程和源代码转换是用来以不同编程语言为多体模型生成源代码的两种技术。自动编程用于从面向对象的库中生成中间表示形式的过程代码,而源代码转换则用于将中间表示形式自动转换为解释语言或编译后的语言,以提高效率。提出了这些技术的实现。它基于用于源代码生成的Python模板引擎和AST树遍历器,以及用于源代码转换的模型驱动的翻译器。代码从元语言翻译为以下四种编程语言中的任何一种:Python-Numpy,Matlab,C ++-Armadillo,C ++-Eigen。模拟了多体模型的两个示例:具有多个回路的四杆连杆机构和3D车辆转向系统。这些示例的代码已在两台基于ARM的单板计算机上生成并执行。尽管这些嵌入式系统的资源和性能较低,但使用编译语言,可以比实时模型更快地仿真这两种模型。最后,当在两个嵌入式系统的Xenomai上以硬实时执行时,评估了两个模型的实时性能。这项工作通过测量表明,自动编程和源代码转换是开发用于嵌入式观察器和控制器的实时多体模型的有价值的技术。

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