基于PSO理论的PMSM无位置传感器低速控制系统研究

针对表贴式永磁同步电机在无位置控制系统中各种强耦合因素进行解耦分析，提出了永磁同步电机无位置传感器低速控制的一种新途径。通过搭建永磁同步电机的高频注入模型，优化了系统的拓扑结构。采用非线性状态观测器代替传统的观测器，提升了系统的估算精度和实时性。在参数整定方面，将粒子群算法引入控制系统，实现对于系统调节参数的动态整定，使系统可以适应多种复杂工况。并在硬件平台上验证基于无位置传感器的永磁同步电机低速控制系统整体功能，通过对于电机起动特性以及带载、转速跌落特性的整体验证。研究结果表明:基于PSO（粒子群优化算法）理论的永磁同步电机低速控制系统可以按照预定速度平稳运行，并且具有良好的抗扰动性能，满足实际应用中的控制需求。

Research on PMSM sensorless low speed control system based on PSO theory

According to the decoupling analysis of various strong coupling factors in the surface-mounted permanent magnet synchronous motor in the positionless control system, a new method of position sensorless low-speed control of the permanent magnet synchronous motor is proposed. By building a high-frequency injection model of a permanent magnet synchronous motor, the topology of the system is optimized. The non-linear state observer is used to replace the traditional observer, which improves the estimation accuracy and real-time performance of the system. In terms of parameter tuning, particle swarm algorithm is introduced into the control system to realize the dynamic tuning of system adjustment parameters, so that the system can adapt to a variety of complex working conditions. And verify the overall function of the permanent magnet synchronous motor low-speed control system based on the sensorless position on the hardware platform, and pass the overall verification of the motor start-up characteristics, load and speed drop characteristics. The research results show that the low-speed control system of permanent magnet synchronous motor based on PSO(Particle Swarm Optimization) theory can run smoothly according to the predetermined speed, and has good anti-disturbance performance, which can meet the control requirements in practical applications.