[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.