基于字典序优化方法的T型三相三电平逆变器容错序列模型预测控制

Due to the existence of the neutral point (NP) voltage, controlling the three-level inverters has essentially become a multiobjective optimization problem (MOOP) that needs to provide stable output voltages for the load and maintain the NP voltage simultaneously. Traditionally, this MOOP is converted into a single-objective optimization problem by weighting factors. However, since the physical dimensions of the two control objectives are usually different, it is challenging to choose proper weighting factors to obtain a satisfactory performance according to a specific theory. To address this issue, a tolerant sequential model predictive control (TSMPC) utilizing a lexicographic optimization method is proposed in this article. This method establishes two distinct layers for the output voltage and NP voltage, arranging them in sequence according to the importance of control objectives to evaluate all voltage vectors. By using an explainable tolerance value rather than conventional weighting factors, the proposed TSMPC algorithm presents superior performance over traditional MPC approaches. Finally, the feasibility and effectiveness of the proposed TSMPC algorithm have been verified through relevant experiments and the stability of this algorithm has also been analyzed.