An Optimal Model Predictive Control Method for Five-Level Active NPC Inverter

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Abstract

Finite Control Set Model Predictive Control (FCS-MPC) can improve the control performance of Five-level Active NPC (5L-ANPC) inverter effectively. However, with the increasing of the levels of inverter, the traditional FCS-MPC method has many problems, such as large amount of rolling optimization calculation and difficulty in weight coefficient design. In order to solve those problems, an Optimal Model Predictive Control (O-MPC) method is proposed. First, an optimal control method based on level jump limitation is proposed to reduce the number of switch states. Second, in order to solve the conflict problem of multiple control objectives and reduce the design difficulty of weight factors, a satisfactory optimal control method based on hierarchy is proposed. After the optimization, the calculation time of the controller is greatly reduced and the control performance of the multi-objective control system will be significantly improved. At last, the effectiveness and feasibility of the proposed O-MPC are validated by the experimental results.

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Liu, Z., Xia, Z., Li, D., Wang, Y., & Li, F. (2020). An Optimal Model Predictive Control Method for Five-Level Active NPC Inverter. IEEE Access, 8, 221414–221423. https://doi.org/10.1109/ACCESS.2020.3043604

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