Logical Operation-Based Model Predictive Control for Quasi-Z-Source Inverter Without Weighting Factor
Yuhao Xu, Yuyao He, Shengchao Li
Abstract
In the model predictive control (MPC), proper weighting factors in the cost function must be designed to obtain the expected performance of the system. However, the design of weighting factors is not a trivial task since the weighting factors are normally tuned by the trial-and-error method. To solve the problem, a new MPC method named logical operation-based model predictive control (LOMPC) is proposed for the quasi-Z-source inverter (qZSI) in this article. The inductor current, capacitor voltage, and output current of the qZSI are separately controlled in the two special logic blocks, i.e., the control logic and judgment logic. As the inductor current is independently controlled in the control logic, its weighting factor is eliminated. In the judgment logic, the optimal switching state that can balance the control performance of the capacitor voltage and output current is selected by the ranking algorithm which can avoid using the weighting factors. In this way, good performance of the qZSI can be obtained by the proposed method without tedious tuning work of the weighting factors. The effectiveness and advantages of the proposed method are verified experimentally.