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Dr. Yan Wan Awarded Three Grants

Dr. Yan Wan, Professor, Electrical Engineering, as Principal Investigator(PI) and co-PI, received three grants last year to develop fundamental intelligent control, cyber-physical systems, and optimization theories and to pursue their new applications in microgrids, multi-robot systems, and autonomous driving.


ONR


In this project, Wan will explore new analysis and design methods that have recently emerged in control theory for application in naval microgrid control systems that serve high-power pulsed missions with stringent time and performance guarantees. In particular, varying demands needs to be addressed within limited shipboard communication, computing, and energy resources. “Many new developments in control theory, such as those at the intersection of control, communication, and computing have not been taken advantage of to address the performance requirement of microgrids.” Wan and his collaborators from Stony Brook University and University of Virginia are developing new solutions, such as event-triggered distributed grid control solutions, for the robust operation of the grids to minimize manned operations. This project is funded under a new $7.36 million ONR program on University-Navy Research Collaboration on Energy Resiliency.


Toyota


Vehicle-to-Vehicle (V2V) and vehicle-to-Infrastructure (V2I) communication is critical to autonomous driving. In order to keep the safety of people from traffic hazards as well as natural disasters, sensor data are desired to be shared among vehicles in real time. To facilitate the high speed data transmission for vehicle-to-vehicle communication, millimeter wave (mmWave) is a promising solution. Wan received a grant from Toyota Motor North America InfoTech Labs to develop scheduling solutions of mmWave directional communication links. The solution is expected to maximize network throughput with performance guarantees on the delay. “With the close collaboration with Toyota researchers, we are working toward establishing V2V mmWave channel scheduling standards that can be widely adopted.”


ARO


Wan also received a ARO grant with colleagues Frank Lewis and Ali Davoudi. The project develops a formal mathematical framework that allow autonomous multi-agent systems to operate in complex dynamic networked environments with diverse threats generated by malicious attacks, functional failures, and human errors. The proposed solution features graphical games and reinforcement learning, which equip the agents with the intelligence to interact with other agents and the change of environment. “Our work will make robots more intelligent,” Wan said. “They can improve their decisions through interactions with their peers and the environments in which they are operating.”