Adaptive power management for cyber-physical system

Abstract

The research work investigate the power management techniques for cyber-physical systems based on the model predictive control method. The work starts with a typical cyber-physical system: wireless sensor network. More specifically, we focus on the supercapacitor powered radar sensor network, which is designed to detect random events with guaranteed performance. Supercapacitor online state of charge prediction method is also proposed to support the power management method. Then a novel cyber-physical system, known as implantable device, is investigated. Adaptive power management framework is developed to optimize the application performance while maintaining a safe operating temperature and respecting system constraints. The developed framework can also be applied to more general cyber-physical systems by tailoring the framework formulation according to the system requirement. A black box modeling techniques, which is known as online multistep prediction method, is developed in the framework to capture the complicated thermal dynamics of implantable device. The developed method can also support online prediction of general slow time-varying system.