Making the wireless critical control safe and resilient
- Reference number
- APR20-0023
- Project leader
- Pang, Zhibo
- Start and end dates
- 210501-270430
- Amount granted
- 1 500 000 SEK
- Administrative organization
- KTH - Royal Institute of Technology
- Research area
- Information, Communication and Systems Technology
Summary
This project is to support Zhibo Pang from ABB to spend 20% time as Adjunct Professor at KTH on interdisciplinary education and research to enable the adoption of wireless networks such as 5G in the automation systems which are both safety critical and time critical. The objective is to deliver the benefits of wireless control to industrial users without compromising the functional safety and uptime even under intentional jamming. Machine learning based tools will be exploited to model the delay and error patterns of wireless network, model the downtime caused by the delay and errors, reduce the latency and increase reliability of wireless by optimizing the large amount of parameters, protect against jamming by agile beamforming and intelligent reflecting surface, and develop systematic approaches to maximize the overall availability by dynamic safety association and active risk avoidance. The applicant will involve a large group of experts from ABB and KTH with broad research backgrounds, exploit the lab facilities at ABB and KTH, and contribute to the strategic collaboration with Ericsson on industrial 5G. In both short term and long term, the results will benefit the Swedish automation industry, telecom industry and many other industries that are using the critical control systems. This project will elevate the existing collaborations between ABB and KTH to next level by solving grand challenges, two-way knowledge transfer, education, and personnel exchange.
Popular science description
This project is to support the applicant, Dr. Zhibo Pang who is Senior Principal Scientist at ABB Corporate Research Sweden, to serve as Adjunct Professor at KTH. The plan is to carry out interdisciplinary education and research to enable the adoption of wireless networks such as the 5G and beyond in the automation systems which are both safety critical and time critical. The objective is to deliver the benefits of the wireless communications to industrial users without compromising the functional safety and uptime of the wireless control systems, even under intentional jamming. The machine learning based tools will be exploited to model the delay and error patterns of wireless network, model the downtime caused by the delay and errors, reduce the latency and increase reliability of wireless by optimizing the large amount of parameters, protect against jamming by agile beamforming and intelligent reflecting surface, and develop systematic approaches to maximize the overall availability by dynamic safety association and active risk avoidance. The applicant will involve a large group of experts from ABB and KTH with broad research backgrounds, exploit the lab facilities at ABB and KTH, and contribute to the strategic collaboration with Ericsson on industrial 5G. In both short term and long term, the results will benefit the Swedish automation industry, telecom industry and many other industries that are using the critical control systems. This project will elevate the existing collaborations between ABB and KTH to next level by solving grand challenges, two-way knowledge transfer, education, and personnel exchange.