Feasibility Study for a Python-Based Embedded Real-Time Control System

Author:

Cho Se Yeon1ORCID,Delgado Raimarius2ORCID,Choi Byoung Wook1ORCID

Affiliation:

1. Department of Electrical and Information Engineering, Seoul National University of Science and Technology, Seoul 01811, Republic of Korea

2. Center for Intelligent & Interactive Robotics, Korea Institute of Science and Technology, Seoul 02792, Republic of Korea

Abstract

Because of its simplicity and the support of numerous useful libraries, Python has become one of the most popular programming languages for application development, even in embedded systems. However, in existing control systems where specific tasks must meet specific temporal deadlines and support schedulability with proper priority assignments, the Python interpreter may not satisfy real-time requirements, owing to features such as the global interpreter lock and garbage collector. This paper addresses these constraints with an approach that executes periodic real-time tasks under the fixed-priority preemptible scheduler of RT-Preempt. First, we implemented a Python real-time module that allows users to create and execute periodic tasks with fixed priorities based on Python. Then, we conducted experiments on an open embedded system, in this case, a Raspberry Pi 4. We evaluated the real-time performance, focusing on test metrics for control systems, such as task periodicity, responsiveness, and interrupt response. The results were then compared to those of conventional real-time tasks developed using the C language to validate the feasibility of the proposed method. Finally, we performed experimental validation by tracking the position of EtherCAT servo motors to demonstrate the feasibility of a Python-based real-time control system in a practical application.

Funder

SeoulTech

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Hardware and Architecture,Signal Processing,Control and Systems Engineering

Reference25 articles.

1. Guaranteeing That Multilevel Prioritized DNN Models on an Embedded GPU Have Inference Performance Proportional to Respective Priorities;Kim;IEEE Embed. Syst. Lett.,2022

2. Taming an Autonomous Surface Vehicle for Path Following and Collision Avoidance Using Deep Reinforcement Learning;Meyer;IEEE Access,2020

3. (2023, February 10). Stephen Cass Top Programming Languages 2021. Available online: https://spectrum.ieee.org/top-programming-languages-2021.

4. (2023, February 10). Ian Skerrett Profile of an Iot Developer: Results of the Iot Developer Survey. Available online: https://ianskerrett.wordpress.com/2016/04/14/profile-of-an-iot-developer-results-of-the-iot-developer-survey.

5. The Real-Time Linux Kernel: A Survey on PREEMPT_RT;Reghenzani;ACM Comput. Surv.,2019

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3