基于改进樽海鞘群算法的PMSM变论域模糊控制

目的 为提高自动化包装流水线的生产效率，针对永磁同步电机PI控制器参数无法适时调整而引起的稳态误差较大、抗干扰性差等问题，提出一种基于改进樽海鞘群算法的新型变论域模糊控制器。方法 通过游走策略和变异分布策略对樽海鞘群智能算法的位置更新进行改进，同时加入过界个体的加权位置修正与劣势个体二次迁移，并将优化后的算法与变论域模糊PI控制器相结合，用于调节伸缩因子，以获得对永磁同步电机更好的控制效果。结果 仿真表明，文中改进后的控制器较传统PI控制器有效减小了静态误差;同时优化后的控制器令PMSM在变速和变载工况下响应更快，较改进前的樽海鞘群算法作用下PI控制器在变速和变载工况下的超调量分别降低约21.35%和62.85%。结论 算法优化伸缩因子后得到的变论域模糊控制与其他控制相比，更有效地提高了系统的鲁棒性，改善了系统的控制性能，减小了损耗。

Variable Universe Fuzzy Control of PMSM Based on Improved SSA

The work aims to propose a new variable universe fuzzy controller based on improved salp swarm algorithm to solve the problems of large steady-state error and poor anti-interference caused by the non-timely adjustment of PI controller parameters of permanent magnet synchronous motor, to improve the production efficiency of automatic packaging line. Through the migration strategy and variation distribution strategy, the position update of salp swarm intelligent algorithm was improved, and the weighted position correction of the crossing individuals and the secondary migration of the inferior individuals were introduced. The optimized algorithm was combined with variable universe fuzzy PI controller to adjust the contraction-expansion factor, so as to achieve better control effect of permanent magnet synchronous motor. The simulation results showed that the optimized controller had smaller offset than the traditional PI controller; meanwhile, it made PMSM respond faster in working conditions of variable speed and load. Compared with that before improvement, the overshoot of PI controller based on SSA was decreased by 21.35% and 62.85% respectively. Compared with other control, the variable universe fuzzy control obtained by the algorithm after optimizing the contraction-expansion factor can improve the robustness of the system more effectively, improve the control performance of the system, and reduce the loss in the process of variable speed.