Exploring Edge Computing for Multitier Industrial Control

被引:18
|
作者
Ma, Yehan [1 ]
Lu, Chenyang [1 ]
Sinopoli, Bruno [2 ]
Zeng, Shen [2 ]
机构
[1] Washington Univ St Louis, Dept Comp Sci & Engn, St Louis, MO 63130 USA
[2] Washington Univ St Louis, Dept Elect & Syst Engn, St Louis, MO 63130 USA
基金
美国国家科学基金会;
关键词
Cyber-physical systems; edge computing; machine learning; wireless networked control system (NCS); NETWORKED CONTROL-SYSTEMS; LINEAR-SYSTEMS; DESIGN; STABILITY; THINGS; SIMULATION; PARAMETERS; INTERNET;
D O I
10.1109/TCAD.2020.3012648
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Industrial automation traditionally relies on local controllers implemented on microcontrollers or programmable logic controllers. With the emergence of edge computing, however, industrial automation evolves into a distributed two-tier computing architecture comprising local controllers and edge servers that communicate over wireless networks. Compared to local controllers, edge servers provide larger computing capacity at the cost of data loss over wireless networks. This article presents switching multitier control (SMC) to exploit edge computing for industrial control. SMC dynamically optimizes control performance by switching between local and edge controllers in response to changing network conditions. SMC employs a data-driven approach to derive switching policies based on classification models trained based on simulations while guaranteeing system stability based on an extended Simplex approach tailored for two-tier platforms. To evaluate the performance of industrial control over edge computing platforms, we have developed WCPS-EC, a real-time hybrid simulator that integrates simulated plants, real computing platforms, and real or simulated wireless networks. In a case study of an industrial robotic control system, SMC significantly outperformed both a local controller and an edge controller in face of varying data loss in a wireless network.
引用
收藏
页码:3506 / 3518
页数:13
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