基于改进鲸鱼优化算法的永磁同步电机控制策略
Control Strategy of Permanent Magnet Synchronous Motor Based on Improved Whale Optimization Algorithm
陈德海 1陈志文 2李志远 2张吉祥2
作者信息
- 1. 江西理工大学 电气工程与自动化学院,江西赣州 341411;中国科学院赣江创新研究院,江西赣州 341411
- 2. 江西理工大学 电气工程与自动化学院,江西赣州 341411
- 折叠
摘要
永磁同步电机(Permanent Magnet Synchronous Motor,PMSM)调速系统中普遍存在转速超调不稳定和受负载干扰大等现象,对此提出一种改进鲸鱼优化算法(Improved Whale Optimization Algorithm,IWOA)对转速环的传统PI控制参数整定进行优化.在鲸鱼算法(Whale Algorithm,WOA)的基础上引入非线性惯性权重来平衡算法的局部和全局搜索能力.依据学习策略的思想,对鲸鱼种群中每个个体的位置进行优化.在Matlab/Simulink上搭建电机调速系统仿真模型并进行仿真实验,仿真结果表明,基于IWOA的控制策略相比于传统WOA控制超调率由3％减少到1.5％,而PI控制超调率为5％,进一步增强了系统抗负载扰动能力,显著地提高了 PMSM的各方面性能.
Abstract
In Permanent Magnet Synchronous Motor(PMSM)speed regulation system,there are common phenomena such as unstable speed overshoot and large load interference.Therefore,an Improved Whale Optimization Algorithm(IWOA)is proposed to optimize the traditional PI control parameter tuning of the speed loop.Firstly,based on the Whale Algorithm(WOA),nonlinear inertia weights are introduced to balance the local and global search capabilities of the algorithm.Secondly,based on the idea of learning strategies,the location of each individual in the whale population is optimized.Finally,a simulation model of the motor speed regulation system is built on Matlab/Simulink and simulation experiments are conducted.The simulation results show that The control strategy based on the IWOA reduces the overshoot rate from 3％to 1.5％compared to the traditional WOA,while the PI control overshoot rate is 5％,further enhancing the system's ability to resist load disturbances and significantly improving the performance of PMSM in all aspects.
关键词
永磁同步电机/改进鲸鱼优化算法/非线性惯性权重/学习策略Key words
PMSM/IWOA/nonlinear inertia weight/learning strategy引用本文复制引用
出版年
2024
国家科技期刊平台
NSTL
万方数据