[Objective] Aiming at the problem of unfixed switching frequency when finite control set model predictive control (FCS-MPC) is applied to neutral-point-clamped (NPC) inverters

this paper proposes a fixed switching frequency three-vector optimal sequence model predictive control (FSF-TOS-MPC) strategy. [Methods] Firstly

spatial sector division was used to simplify the optimization algorithm

narrowing the range of basic voltage vector involved in model predictive optimization

thus reducing the amount of computation. Then

through the polarity discrimination of the neutral-point potential of the DC side and the three-phase currents of the load side

the three-vector optimal switching sequence partition pre-selection was carried out. And the Karush-Kuhn-Tucker condition was introduced to solve the duration of each voltage vector in the switching sequence

to ensure that the duration of each vector was constant greater than zero

and the switching frequency was fixed. Finally

multi-objective control was carried out by constructing a cost function to achieve reference current tracking and DC side neutral-point potential balancing. [Results] The conventional FCS-MPC

optimized FCS-MPC and the FSF-TOS-MPC proposed in this paper were compared under different operating conditions by simulation. Simulation results showed that the FSF-TOS-MPC strategy can ensure the stable operation of the inverter with fixed switching frequency

thus effectively suppressing the total harmonic distortion of the output current

improving the dynamic response characteristics of the system

and achieving the neutral-point potential balance. [Conclusion] The FSF-TOS-MPC strategy proposed in this paper has superior control performance

and provides an effective solution to the problem of unfixed switching frequency in the model predictive control of NPC inverters.