基于改进鲸鱼优化算法的永磁同步电机控制策略OA
Control Strategy of Permanent Magnet Synchronous Motor Based on Improved Whale Optimization Algorithm
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.
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.
陈德海;陈志文;李志远;张吉祥
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江西理工大学 电气工程与自动化学院,江西赣州 341411
动力与电气工程
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
PMSMIWOAnonlinear inertia weightlearning strategy
《无线电工程》 2024 (006)
1529-1535 / 7
国家自然科学基金(52067008)National Natural Science Foundation of China(52067008)
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