改进黏菌算法优化模糊PI在PMSM控制的应用  

Improvement of the slime mold algorithm for optimizing fuzzy PI control in PMSM applications

作　　者：贾立山 田学斌 许海军 JIA Lishan;TIAN Xuebin;XU Haijun(College of Electronic Information and Automation,Civil Aviation University of China,Tianjin 300300,China;College of Aeronautical Engineering,Civil Aviation University of China,Tianjin 300300,China)

机构地区：[1]中国民航大学电子信息与自动化学院,天津300300 [2]中国民航大学航空工程学院,天津300300

出　　处：《重庆理工大学学报(自然科学)》2025年第3期235-242,共8页Journal of Chongqing University of Technology:Natural Science

摘　　要：为了解决永磁同步电机模糊控制器仅凭人工经验很难获得全局最优模糊规则的问题,提出一种结合模拟退火和自适应变异的混沌黏菌优化算法。针对传统黏菌算法高维空间搜索能力弱和易陷入局部最优解的问题,引入改进Tent混沌映射,优化初始种群,采用非线性收敛因子策略,提高算法的探索和开发能力。引入模拟退火及自适应变异来规避陷入局部最优。仿真结果表明,所提ACSMA算法具有更高的计算精度和收敛速度,将其应用于PMSM控制,ACSMA优化后的模糊PI控制器调节时间缩短73%,超调量减少21%,控制性能得到有效提升。To address the challenge of obtaining globally optimal fuzzy rules for the fuzzy controller of a permanent magnet synchronous motor(PMSM)based solely on human expertise,we propose a chaotic slime mold optimization algorithm combined with simulated annealing and adaptive mutation.It aims to overcome the limitations of traditional slime mold algorithms,such as weak high-dimensional search capabilities and susceptibility to local optima.Our proposed algorithm introduces an improved Tent chaotic mapping to optimize the initial population,employs a nonlinear convergence factor strategy to enhance exploration and exploitation capabilities,and incorporates simulated annealing and adaptive mutation to avoid local optima.Our simulation results demonstrate our proposed ACSMA algorithm achieves higher computational accuracy and convergence speed.When applied to PMSM control,the ACSMA-optimized fuzzy PI controller reduces adjustment time by 73% and overshoot by 21%,significantly improving the control performance.

关 键 词：黏菌算法 永磁同步电机 模糊控制 转速控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]