TY - JOUR
T1 - Exploring Edge Computing for Multitier Industrial Control
AU - Ma, Yehan
AU - Lu, Chenyang
AU - Sinopoli, Bruno
AU - Zeng, Shen
N1 - Publisher Copyright:
© 1982-2012 IEEE.
PY - 2020/11
Y1 - 2020/11
N2 - 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.
AB - 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.
KW - Cyber-physical systems
KW - edge computing
KW - machine learning
KW - wireless networked control system (NCS)
UR - https://www.scopus.com/pages/publications/85096033800
U2 - 10.1109/TCAD.2020.3012648
DO - 10.1109/TCAD.2020.3012648
M3 - Article
AN - SCOPUS:85096033800
SN - 0278-0070
VL - 39
SP - 3506
EP - 3518
JO - IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
JF - IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
IS - 11
M1 - 9211472
ER -