Cascaded H-Bridge Multilevel Inverter with Reduced Number of Power Components

This paper deals Cascaded H-bridge multilevel inverter with reduced number of power components using artificial neural network technique. This topology consists of lower blocking voltage on switches and it requires less number of dc voltage sources, power switches which results in decrease the complexity and total cost of the inverter. A new algorithm is used to determine the magnitude of dc voltage sources for the generation of all voltage levels. Artificial Neural Network (ANN) is trained by the back-propagation algorithm of the Mean Square Error between the output and the desired value. The performances of the proposed topology using artificial neural network technique are simulated using MATLAB simulink and hardware implementation also done.