基于蚁群算法的永磁同步电机模糊PI控制策略研究

Research on Fuzzy PI Control Strategy of Permanent Magnet Synchronous Motor Based on Ant Colony Algorithm

摘要: 在三相永磁同步电机的矢量控制中，传统PI控制由于其参数的固定，在变化的动态系统中表现不佳，易出现超调、失真等影响，使用模糊PI控制可以有效改善传统PI控制中例如无法较好地适应不同转矩的缺陷。但模糊PI控制中的量化因子与比例因子的选择过于依赖经验，由此本文提出一种基于蚁群算法优化的模糊PI控制器，使用MATLAB/Simulink软件进行仿真，分析了优化后的转速、电磁转矩与三相电流在不同控制方式下的图像，最终得到了蚁群算法优化下的模糊PI控制器与传统PI控制器相比具有良好的仿真效果，满足了三相永磁同步电机精度需求高、响应需求快以及输出需要稳定的要求。

Abstract: In the vector control of the three permanent magnet synchronous motors, the traditional PI control performs poorly in the changing dynamic system due to the fixation of its parameters, and is prone to overshoot, distortion and other effects, and the use of fuzzy PI control can effectively improve the defects in the traditional PI control, such as the inability to adapt to different torques. However, the selection of quantization factor and scale factor in fuzzy PI control is too dependent on experience, so this paper proposes a fuzzy PI controller based on ant colony algorithm optimization, and uses MATLAB/Simulink software to simulate, analyzes the images of the optimized speed, electromagnetic torque and three currents under different control modes, and finally obtains that the fuzzy PI controller optimized by ant colony algorithm has good simulation effect compared with the traditional PI controller, and meets the high accuracy requirements of the three permanent magnet synchronous motors, responding quickly to demand and the need for stable output.