Modeling of Induction Heating Inverter Using System Identification

In this paper, Auto Regressive eXogenous input (ARX), Auto Regressive Moving Average eXogenous input (ARMAX), Output error and BJ models of class D voltage-source half-bridge series-resonant inverter used for induction heating are identified and studied based on prior knowledge and measured data from PSIM simulation Environment. The output data are generated by applying Pseudo-Random-Binary-sequence (PRBS) as an input through the inverter MOSFET gate in the PSIM software. PRBS signal is generated using standard components such as flip-flops or XOR gates to approximate the white noise in the PSIM software. The generated output and input data are loaded in the MATLAB to identify the unknown system parameters of induction heating inverter by using MATLAB system identification toolbox. Estimation of models with pre-selected structures can be performed using system identification toolbox. To validate the models and their limitations, the fitness properties of the models based on percentage best fit and their resonant frequencies are examined.