Implementation of a Full Bridge Series-Parallel Resonant DC-DC Converter Using Artificial Neural Networks and Sequential State Machine Controllers

In this paper, two methods of control for high-voltage Full Bridge Series-Parallel Resonant (FBSPR) DC-DC converter are proposed and the results are compared. Soft switching operation using Zero Current Switching (ZCS) and Zero Voltage Switching (ZVS) technologies is employed to decrease the losses and optimize the efficiency of converter. The way of obtaining small-signal model of FBSPR converter using the generalized averaging method is discussed. Then two control methods using Artificial Neural Networks (ANN) and Sequential State Machine (SSM) are explained and the experimental results are compared. The ANN controller is trained according to the small signal model of the converter and operating points and the SSM controller operates on base of a finite number of states, actions and functions and determines transition from one state to another according to FBSPR converter conduction status. To compare the performances of two controllers, a prototype is designed and implemented. The prototype is tested for step changes in both output load and reference voltage at steady state and under transient conditions. Comparison between experimental results for both ANN and SSM controllers show better speed performances for SSM controller in small changes in load and more reliability for ANN controller in case of large variations.