Predictive control based on ranking multi-objective optimization approaches for a quasi-Z source inverter

In power converter control, predictive control has several merits, such as simple concept and fast response. However, the necessity to use the weighting factor inside the cost function makes the control design complex in the case of regulating multivariables where the value of the weighting factor is obtained by a nontrivial process. Also, it primarily depends on the system parameters and operating points of the control system. This paper aims to enhance the model predictive algorithm of the singlestage topology of a quasi-Z Source Inverter (qZSI). The concept of a multi-objective optimization approach is used in addition to the sub-cost function definition to remove the weighting factors. By using the sub-cost function definition, the inductor current is pushed away from the main loop of the predictive algorithm. Thus, no weighting factor is needed to manage the priority of the inductor current. The other two control targets, which are the capacitor voltage and load currents, will be controlled by the multi-objective optimization approach without using any weighting factors. A detailed theoretical analysis of the proposed technique will be given and validated based on simulation results.