ECE Department Seminar 

 

Resolve Contentions Through Realtime Control and Scheduling for Cyber Physical Human Systems 

 

Ningshi Yao 

Postdoctoral Research Fellow 

School of Electrical and Computer Engineering 

Georgia Institute of Technology 

 

Thursday, March 4, 2021 

10:30 am 11:30 am 

Zoom Meeting Link: 

https://gmu.zoom.us/j/96669668766 

 

 

 

Abstract: Shared resources, such as cloud computing and communication networks, are widely used in large-scaled real-time systems to increase modularity and flexibility. When multiple systems need to access a shared resource at the same time and the demands exceed the total supply, a contention occurs. A scheduling strategy is needed to determine which systems can access the resource first to resolve contentions. However, such scheduling mechanism inevitably introduces time-varying delays and may degrade the system performance or even sabotage the stability of control systems.  

 

Considering the coupling between the scheduling and control, this talk presents a novel sample-based method to co-design scheduling strategies and control laws for coupled control systems with shared resources, which aims to minimize the overall performance degradation caused by contentions. The co-design problem is formulated as a mixed integer optimization problem with a very large search space, rendering difficulty in computing the optimal solution. To solve this challenge, we develop a contention resolving model predictive control (CRMPC) method to dynamically design optimal scheduling and control in real-time. With fundamental assumptions in scheduling theory, the solution computed by CRMPC can be proved globally optimal. CRMPC is a theoretical framework that is general and can be applied to many applications in Cyber-Physical-Human systems. The effectiveness of CRMPC has been verified in many real-world applications, such as networked control systems, traffic intersection management systems, and human multi-robot collaboration systems. The performance of CRMPC was compared with well-known scheduling methods and demonstrated significant improvements.   

 

 

Bio: Ningshi Yao is currently a Postdoctoral Research Fellow in the School of Electrical and Computer Engineering at Georgia Institute of Technology, Atlanta, GA, USA. She received her Ph.D. degree from the School of Electrical and Computer Engineering at Georgia Institute of Technology in 2020. She obtained a B.S. degree in Automatic Control from Zhejiang University, China, in 2014. Her research interests include control theory, real-time scheduling, robotics, cyber physical system, human robot interaction and machine learning.