Research on Optimized Multi-Objective FCS-MPC Without Weighting Factors of NPC Three-Level Inverter

Abstract

To address a series of issues in the application of finite control set model predictive control (FCS-MPC) strategy for neutral point clamped (NPC) three-level inverters, such as large amount of rolling optimization calculation, poor midpoint voltage balance effect, high common mode voltage, and complex design of weighting coefficients, this paper proposes an optimized multi-objective FCS-MPC strategy without weighting factors. First, the method applies the idea of space vector region division, to obtain the optimal region based on Lyapunov function, and combines with delay compensation, reducing the system's optimization time and enhancing the control precision of the system. Second, aiming at the issue of multi-objective control for inverters, by constructing the objective function to control tracking reference current, midpoint voltage balance, and reduce common mode voltage, a hierarchical optimization control method is adopted. This approach eliminates the need to design complex weighting coefficients constrained in the objective function as constraints, thereby improving the accuracy of predicted currents. Finally, the optimized multi-objective FCS-MPC control strategy is validated through simulation and experimentation to achieve a better balance of midpoint voltage and reduce common mode voltage and harmonic content, thereby enhancing the control precision and dynamic/static performance of the system.