A Low Computational Cost Model Predictive Controller for Grid Connected Three Phase Four Wire Multilevel Inverter

The evolving industry applications of neutral point clamped multilevel inverters have motivated the researchers to improve its controllability and performance. Finite control set model predictive controller (FCSMPC) dominates over the conventional controllers because of its unconditional stability and ease in digital implementation. However, computational burden is an issue which needs to be addressed in FCSMPC for higher level inverters. This paper reports two novel methods which employ three-dimensional natural coordinate space vector geometry of grid connected neutral point clamped three phase three level four wire multilevel inverters to lower the computation burden in FCSMPC. One of the methods is dedicated for controlling only the grid currents. In this method, The coordinates of optimal switching state is obtained directly without evaluating any objective function. Whereas, in the other method, the grid currents and neutral point voltage, both are controlled simultneously. This method evaluates eight objective functions to get the optimal switching state. MATLAB simulation results are provided to compare the performance of the proposed controller with the conventional FCSMPC.