Model Predictive Control of Energy-Stored Quasi-Z-Source Inverter Without Weighting Factor

When the quasi-Z-source inverter with energy storage (ES-qZSI) by model predictive control (MPC), an appropriate weighting factor is designed in the cost function to achieve the best possible performance from the system. However, adding weighting factors directly to a cost function produces both numerical instability and computational complexity, in addition to the inability to distinguish between the role of weighting factors and system dynamics in the performance of the relevant system. This paper proposes an improved MPC algorithm without weighting factors for the ES-qZSI system. The computational cost of MPC is significantly reduced by the voltage vector control method without affecting the control performance. Moreover, the inductance current term in the control logic is considered individually, thus eliminating its weighting factor. Compared with conventional MPC, computational efficiency and control performance are demonstrated via numerical simulation. The simulation results show a good dynamic and static performance for the improved algorithm.