Design and Implementation of SEPIC Converter Based Nine-Level MLI Fed IM with PI, FLC, and ANN Controller

Abstract

In recent year, the field of power converters has experienced a large growth due to confluence of several factors. Moreover, these advances in semiconductor fabrication technology have made it possible to significantly improve the voltage and current handling capabilities and the switching speeds of power semiconductor devices, which make up the converter to design for many applications. Whereas industrial sectors are facing many difficulties to convert the fixed voltage into variable voltage. For that reason, a DC-to-DC conversion process is established from conventional methods like voltage divider, potentiometer to get output voltage less than the input supply; in that case, this will lead to power losses. The DC-to-DC converter topologies can be divided into two major types, depending on whether or not they have galvanic isolation between the input supply and the output circuitry. DC-to-DC converters are used in portable electronic devices such as mobile application and laptop computers, which are supplied with power from batteries primarily. Such electronic devices often contain several sub-circuits, each with its own voltage level requirement different from that supplied by the battery or an external supply. Additionally, the battery voltage declines as its stored energy is drained. Switched DC-to-DC converters offers a method to increase voltage from a partially lowered battery voltage, thereby saving space instead of using multiple batteries to accomplish the same thing. This research work is focused on a performance analysis of SEPIC converter fed nine-level inverter with artificial neural network for induction motor; the performance analysis is carried out for Boost–SEPIC converter fed multilevel inverter IM drive system. Comparison is made with PI, Fuzzy logic, and ANN controllers. The simulation and experimental results validate the various time domain parameters.