Hybrid Control Tools for Power Management and Optimization in Cyber-Physical Systems
Abstract:
This project strikes a balance between performance considerations and power consumption in cyber-‐physical systems through algorithms that switch among different modes of operation (e.g., low-‐power/high-‐power, on/off, or mobile/static) in response to environmental conditions. The computational contribution is a hybrid optimal control framework that is connected to a number of relevant target applications where physical modeling, control design, and software architectures all constitute important components. The fundamental research in this program advances the state-‐of-‐the-‐art along four different dimensions, namely (1) real-‐time hybrid optimal control algorithms for power management, (2) power management in mobile sensor networks, (3) distributed power-‐aware architectures for infrastructure management, and (4) power management in embedded multi-‐core processors. This work enables low-‐power devices to be deployed in a more effective manner, and has implications across a number of application domains, including distributed sensor and communication networks, and intelligent and efficient buildings. The team behind this project represents both a research university (Georgia Institute of Technology) and an undergraduate teaching university (York College of Pennsylvania) in order to ensure that the educational components are far-‐ reaching and cut across traditional educational boundaries. The project involves novel, inductive-‐based learning modules, where graduate students team with undergraduate researchers.