With the development of 3D printing technology, its application areas have been extended to clinical medicine, and 3D biotechnologybased additive printing of skin tissue, cellular scaffolds and other tissues and organs has been realized.3D bioprinter generally use permanent magnet synchronous motors as their mobile platform drive motors. Traditional methods usually use multiple algorithms such as genetic particle swarm optimization fuzzy rules to adjust PI parameters to achieve control. However, the mechanical superposition algorithm increases the complexity of the algorithm and seriously affects the performance of the motor control effect. Therefore, this paper adopts fractionalorder PI control instead of traditional PI control, and uses particle swarm optimization to optimize the gain, the number of fractional orders and the adaptive mechanism in the model reference adaptive system in fractionalorder PI to finally obtain the optimal solution. Simulink simulation shows that compared with traditional PI control and methods such as genetic particle swarm optimized fuzzy PI control, the particle swarm optimized fractional order PI improves the motor response speed by 106% and 56%, and the stability by 813% and 60%, respectively, and is suitable for 3D bioprinter mobile platform with high control accuracy.