Yao To Receive NSF CAREER Award
Ningshi Yao, Assistant Professor, Electrical and Computer Engineering, College of Engineering and Computing (CEC), is set to receive funding for: “CAREER: A Unified Event-triggered Real-Time Scheduling and Control Co-Design Framework for Networked Safety-critical Control Systems.”
Yao aims to ensure the safety, reliability, and efficiency of modern interconnected autonomous systems, such as robot swarms, intelligent transportation networks, and smart manufacturing. Through this research, she will bring transformative change to how these complex systems share limited resources, including communication networks, computer processors, and shared physical space, by preventing the traffic jams of data or physical collision that cause catastrophic physical accidents or energy waste.
She will do this by creating new mathematical methods that allow networked systems to schedule actions and design controls that compensate for time delays in real time.
Yao will establish a unified theoretical framework that links complex timing delays with physical stability guarantees, enabling safe resource management for large-scale autonomous technologies.
She will contribute to national prosperity through potential economic savings from mitigated traffic congestion and improved manufacturing efficiency. Furthermore, she will help cultivate a highly skilled engineering workforce by integrating these research concepts into the Airborne Robotics Competition, an accessible, low-cost national robotic blimp competition where K-12 students gain hands-on experience with the critical importance of networked real-time robotic systems.
The fundamental technical challenge in large-scale networked control systems is correlated resource contention, where simultaneous demands for shared resources create complex non-linear timing dynamics. Traditional periodic or centralized methods fail to predict when these unpredictable scheduling delays will destabilize the physical system or determine how to scale up safely. To resolve these issues, Yao will develop a decentralized real-time scheduling and control co-design framework.
First, novel models are formulated to accurately capture timing dynamics caused by multi-layered resource competition.
Next, the project designs timing-aware event-triggered control mechanisms that only consume network resources when necessary. A key contribution of this work is establishing rigorous analytical tools to certify schedu-stability, which is a joint guarantee of scheduling deadline feasibility and control system stability.
Finally, the project creates a computationally efficient decentralized optimization framework to solve previously intractable co-design problems for large-scale systems.
Yao anticipates the optimal solutions and verified timing models resulting from this framework will be used to generate high-quality training data for methods such as imitation learning or reinforcement learning, for even larger system scales, where real-time computation of optimality is infeasible. All theoretical advancements will be integrated into an open-source software toolbox, lowering the barrier for researchers to analyze complex timing behaviors in cyber-physical systems.
Yao will receive $628,260 from the National Science Foundation for this award. Funding will begin in June 2026 and will end in late May 2031.
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