
FOLLOWUS
State Key Laboratory of Fluid Power & Mechatronic Systems, Zhejiang University, Hangzhou 310027, China
Yong LEI, E-mail: ylei@zju.edu.cn
收稿:2017-12-08,
修回:2019-;6-11,
纸质出版:2019-06
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张雷鸣, 孙毅超, 雷勇. 控制器局域网在错误状态下的报文延时分布研究[J]. 信息与电子工程前沿(英文), 2019,20(6):760-772.
Lei-ming ZHANG, Yi-chao SUN, Yong LEI. Message delay time distribution analysis for controller area network under errors[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(6): 760-772.
张雷鸣, 孙毅超, 雷勇. 控制器局域网在错误状态下的报文延时分布研究[J]. 信息与电子工程前沿(英文), 2019,20(6):760-772. DOI: 10.1631/FITEE.1700815.
Lei-ming ZHANG, Yi-chao SUN, Yong LEI. Message delay time distribution analysis for controller area network under errors[J]. Frontiers of Information Technology & Electronic Engineering, 2019, 20(6): 760-772. DOI: 10.1631/FITEE.1700815.
控制器局域网(CAN)是一种广泛应用于各类工业场景的现场总线协议。为深入理解错误发生时的网络行为并优化网络控制系统设计,需分析CAN网络报文响应时间。本文在考虑错误的基础上,提出一种新颖的CAN网络报文延时分布分析方法,将复杂报文序列分解为典型报文模式和情形。首先开发随机故障模型并定义概率因子计算错误的分布形式,其次基于错误分布分析单个子节点布局下报文的延时分布。然后基于典型报文模式和情形的延时分布,开发多子节点布局下报文延时分布的分析框架。最后搭建实验平台,在不同网络设置下进行多组实验,展示和验证该方法。结果表明该方法计算出的报文延时分布与实际观测值一致。
Controller area network (CAN) is a widely used fieldbus protocol in various industrial applications. To understand the network behavior under errors for the optimal design of networked control systems
the message response time of the CAN network needs to be analyzed. In this study
a novel delay time distribution analysis method for the response messages is proposed when considering errors. In this method the complex message queues are decomposed into typical message patterns and cases. First
a stochastic fault model is developed
and the probability factor is defined to calculate the error distribution. Then the message delay time distribution for the single slave node configuration is analyzed based on the error distribution. Next
based on the delay time distribution analysis of typical patterns and cases
an analysis framework of message delay time distribution for the master/slave configuration is developed. The testbed is constructed and case studies are conducted to demonstrate the proposed methodology under different network configurations. Experimental results show that the delay time distributions calculated by the proposed method agree well with the actual observations.
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