Dynamic Bandwidth Allocation Algorithms of Networked Motion Control Systems Based on CAN

doi:10.3969/j.issn.1000-565X.2010.10.012

Journal of South China University of Technology (Natural Science Edition) ›› 2010, Vol. 38 ›› Issue (10): 61-67.doi: 10.3969/j.issn.1000-565X.2010.10.012

• Electronics, Communication & Automation Technology • Previous Articles Next Articles

Dynamic Bandwidth Allocation Algorithms of Networked Motion Control Systems Based on CAN

Zhao Wei-quan Li Di

School of Mechanical and Automotive Engineering,South China University of Technology,Guangzhou 510640,Guangdong,China

Received:2009-12-28 Revised:2010-02-13 Online:2010-10-25 Published:2010-10-25
Contact: 赵维俭（1972-），男，博士，东莞理工学院副教授，主要从事网络化运动控制系统、嵌入式控制系统设计研究． E-mail:zhaowq@dgut．edu．cn
About author:赵维俭（1972-），男，博士，东莞理工学院副教授，主要从事网络化运动控制系统、嵌入式控制系统设计研究．
Supported by:
国家自然科学基金资助项目（50875090）; 东莞市科技计划项目（2008108101019）

Abstract

Abstract:

As the existing static bandwidth allocation algorithms cannot effectively utilize the limited bandwidth in networked motion control systems based on CAN,two dynamic bandwidth allocation algorithms based on feedback control are proposed.In these algorithms,bandwidth is reasonably allocated in accordance with the actual network state and control requirements through adjusting the sampling period.Moreover,as the wide fluctuation of sampling period may result in system instability and excessive resource consumption,three typical sampling periods are preset to realize the bandwidth allocation by switching.Simulated results show that the proposed dynamic bandwidth allocation algorithm is superior to the fixed one.

Key words: networked motion control system, bandwidth allocation, scheduling, sampling period

Zhao Wei-quan Li Di . Dynamic Bandwidth Allocation Algorithms of Networked Motion Control Systems Based on CAN[J]. Journal of South China University of Technology (Natural Science Edition), 2010, 38(10): 61-67.

[1]	LU Yiqin, XIE Wenjing, WANG Haihan, et al. Security-Aware Scheduling Method for Time-Sensitive Networking [J]. Journal of South China University of Technology(Natural Science Edition), 2023, 51(5): 1-12.
[2]	LU Qingchang, XU Biao, CUI Xin . Research on the Non-linear Relationship Between Built Environment and Bike-sharing Flow Rate [J]. Journal of South China University of Technology(Natural Science Edition), 2023, 51(2): 100-110.
[3]	Lu Yiqin, Xiong Xin, Wang Meng, et al. Bandwidth Allocation of AVB Traffic Based on Link Load Balancing in TSN [J]. Journal of South China University of Technology(Natural Science Edition), 2023, 51(11): 1-9.
[4]	BIE Yiming, ZHU Aoze, CONG Yuan. Electric Bus Scheduling Method Considering Differences in the State of Health of Batteries [J]. Journal of South China University of Technology(Natural Science Edition), 2023, 51(10): 11-21.
[5]	YANG Min, CHEN Shantao, JIANG Ruiyu, et al. Flexible Bus Scheduling Optimization for Integrated Hub Connections in the Context of MaaS [J]. Journal of South China University of Technology(Natural Science Edition), 2023, 51(10): 22-30.
[6]	WENG Jiancheng, WANG Maolin, LIN Pengfei, et al. Cross-line Combined Bus Scheduling Optimization Method Based on Passenger Flow Characteristic Identification [J]. Journal of South China University of Technology(Natural Science Edition), 2022, 50(9): 39-48.
[7]	XIA Qinxiang, LI Kai, MA Jun, et al. Die Electrode Scheduling Problem Solution Based on Genetic Algorithm [J]. Journal of South China University of Technology(Natural Science Edition), 2022, 50(3): 80-87.
[8]	TAN Guang LI Changhao ZHAN Zhaohuan. Adaptive Scheduling Algorithm for Object Detection and Tracking Based on Device-Cloud Collaboration [J]. Journal of South China University of Technology (Natural Science Edition), 2021, 49(7): 86-93.
[9]	QUAN Yanming HE Yiming. Research on Clonal Selection Algorithm for Multi-Robot Task Allocation and Scheduling [J]. Journal of South China University of Technology (Natural Science Edition), 2021, 49(5): 102-110.
[10]	HAN Wanli, DU Bangshen, ZHAO Jianyou, et al. Optimization of Urban and Rural Public Transport Operation and Scheduling Considering Small Piece Express [J]. Journal of South China University of Technology (Natural Science Edition), 2021, 49(5): 28-37.
[11]	JIN Wenzhou, HU Weiyang, DENG Jiayi, et al. Flexible Scheduling Model of Demand Ｒesponse Transit Based on Hybrid Algorithm [J]. Journal of South China University of Technology (Natural Science Edition), 2021, 49(1): 123-133.
[12]	YAO Enjian LU Muyang LIU Yuhuan YUAN Ling. Electric Bus Area Driving Plan Preparation Considering Charging Constraints [J]. Journal of South China University of Technology (Natural Science Edition), 2019, 47(9): 68-73.
[13]	LIN Shunjiang YANG Zhibin LU Yuan LIU Mingbo HE Sen JIANG Hao. Optimal Energy Scheduling of Photovoltaic Natural Gas，Cooling， Heating and Power Co-supply Park Micro-network [J]. Journal of South China University of Technology (Natural Science Edition), 2019, 47(3): 9-19.
[14]	LIN Weiwei WANG Zetao . Docker Cluster Scheduling Strategy Based on Genetic Algorithm [J]. Journal of South China University of Technology (Natural Science Edition), 2018, 46(3): 127-133.
[15]	ZHAO Jian-dong DUAN Xiao-hong SONG Shou-xin. Emergency Vehicle Scheduling and Reallocation on the Basis of Non-Cooperative Game [J]. Journal of South China University of Technology (Natural Science Edition), 2016, 44(3): 110-117.

Dynamic Bandwidth Allocation Algorithms of Networked Motion Control Systems Based on CAN

PDF

Knowledge

Abstract

Cite this article

share this article

References

Related Articles 15

Recommended Articles

Metrics

Comments