FPGA HIL simulation of a linear system block for strongly coupled system applications

J. Arias-Garcia, A. Braga, C. Llanos, M. Ayala-Rincón, R. Pezzuol Jacobi, A. Foltran
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引用次数: 7

Abstract

This paper introduces a hardware simulation flow that is based on the Xilinx System Generator Tool (XSG), of an architecture for solving dense linear systems, presented as a strongly coupled system, which is in turn based on Gaussian Elimination using an FPGA. A functional verification process is achieved by taking advantage of the XSG, allowing both software and hardware-in-the-loop (HIL) simulations and using the respective results achieved in Matlab as a reference model. The linear system block embedded in the XSG can handle single, double and custom data precision, following the IEEE 754 floating point standard. The current architecture improves the use of internal RAM of the selected FPGA device (Virtex-5) through a special Memory Access Unit, reducing the data access among this RAM and the different modules in the architecture. Examples of systems of six equations, which are suitable for some robotics applications, have been used for comparing the performance of the Linear System block and Matlab, the latter used as a statistical estimator, in order to validate the data results.
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用于强耦合系统应用的线性系统块的FPGA HIL仿真
本文介绍了一种基于Xilinx System Generator Tool (XSG)的硬件仿真流程,该流程用于求解密集线性系统的体系结构,该体系结构以强耦合系统的形式呈现,并基于使用FPGA的高斯消去。利用XSG实现了功能验证过程,允许软件和硬件在环(HIL)仿真,并使用Matlab中获得的各自结果作为参考模型。嵌入在XSG中的线性系统块可以处理单、双和自定义数据精度,遵循IEEE 754浮点标准。当前的架构通过一个特殊的内存访问单元提高了所选FPGA器件(Virtex-5)的内部RAM的利用率,减少了该RAM与架构中不同模块之间的数据访问。本文以适合某些机器人应用的六方程系统为例,比较了线性系统模块和Matlab的性能,后者用作统计估计器,以验证数据结果。
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