A continuous control set model predictive speed control (CCS-MPSC) strategy based on the particle swarm optimization (PSO) algorithm is proposed, where the cost function of model predictive speed control (MPSC) is regarded as the objective function to evaluate the fitness of the particles. During this process, all particles are ordered to conduct optimization under the hexagonal sector composed of voltage space vectors. At the end, the particles coverage to the optimal value through keeping updating particle positions. As the feedback, the system obtains the optimal voltage vector without the derivation of error model and realizes CCS-MPSC. According to the simulation results, the effectiveness, and the robustness of speed control with mutative work conditions.