Bayesian Network and Semidefinite Programming Based Wireless Power Transfer Manufacturing System State Estimation and Regulation

In order to supply energy to the smart objects such as electric vehicles and smart phones using wireless power transfer (WPT) framework, the internet of things (IoT) embedded sensors and actuators can play critical roles for sensing, monitoring and regulating the WPT system states. Specifically, the smart sensors are used to transmit sensing state information to the control center, where the state estimation program runs to know the operating and health conditions of WPT system. This study proposes a Bayesian network based WPT system state estimation algorithm. This scheme can estimate the WPT system states in a distributed way using the Bayesian tree structure. Afterwards, the semidefinite programming based optimal feedback control scheme is proposed to regulate the system states. Simulations results show that the proposed approach provides significant performance improvement compared with the existing scheme.