Abstract
In this paper, we proposed a sliding mode control method for the bearingless permanent magnet slice motor for the blood pump based on the genetic particle swarm algorithm, which aims to solve the problems of strong coupling, strong interference, nonlinearity and uncertainty. Firstly, the mathematical model of rotor torque and suspension force of the bearingless permanent magnet slice motor is established. Secondly, the structure of sliding mode observer is deduced by designing sliding mode surface and control law. And, the performance parameters of sliding mode observer are optimized by the genetic particle swarm optimization algorithm. Thirdly, electromagnetic torque and suspension force control under this control method is studied by Simulink. Finally, the control method is applied to the control of the blood flow of the blood pump, and the rotation speed can effectively control the blood flow. The results indicate that compared with PID control and traditional sliding mode control methods, the sliding mode control method optimized by the genetic particle swarm optimization algorithm greatly improves the control performance of bearingless permanent magnet slice motor. The results show that the blood flow can meet expectations with a small error, which fully meets the blood perfusion requirements of the blood pump.