| 引用本文: | 周 立,李京明,周越鹏,尚治博.基于GPIO的永磁同步电机模型预测转矩控制[J].电力系统保护与控制,2023,51(6):145-153.[点击复制] |
| ZHOU Li,LI Jingming,ZHOU Yuepeng,SHANG Zhibo.Model predictive torque control of permanent magnet synchronous motor based on GPIO[J].Power System Protection and Control,2023,51(6):145-153[点击复制] |
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| 摘要: |
| 在永磁同步电机模型预测转矩控制(model predictive torque control,MPTC)中，由于目标函数控制变量的量纲不同，为了在代价函数中选取最优的权重系数，提出一种改进高斯变异鸽群算法(Gaussian mutation pigeon-inspired optimization algorithm, GPIO)实现权重系数自整定。首先，基于代价函数最小化原则设计PIO的目标函数，用电流id、iq脉动误差均方根评价权重系数。其次，在传统高斯变异算子的基础上引入自适应调整动态参数实现变异。仿真和实验结果表明，将改进后的算法应用于永磁同步电机模型预测转矩系统，能在较少的迭代次数内整定出最优的权重系数，极大地降低了转矩误差和电流谐波畸变率。 |
| 关键词: 模型预测转矩控制 代价函数 权重系数 高斯变异鸽群算法 高斯变异算子 |
| DOI：10.19783/j.cnki.pspc.220708 |
| 投稿时间：2022-05-12修订日期：2022-06-29 |
| 基金项目:国家自然科学基金项目资助(51177067) |
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| Model predictive torque control of permanent magnet synchronous motor based on GPIO |
| ZHOU Li1,LI Jingming1,ZHOU Yuepeng2,SHANG Zhibo1 |
| (1. Faculty of Electrical and Control Engineering, Liaoning Technical University, Huludao 125105, China;
2. Shanxi Yangguang Power Generation Responsibility Company, Yangquan 045200, China) |
| Abstract: |
| In the model predictive torque control (MPTC) of permanent magnet synchronous motor (PMSM), due to the different dimensions of control variables in the objective function, in order to select the optimal weight coefficient in the cost function, an improved Gaussian mutation pigeon-inspired optimization algorithm (GPIO) is proposed to realize the self-tuning of the weight coefficient. First, the objective function of PIO is designed based on the principle of cost function minimization, and the weight coefficient is evaluated by the root mean square of current id and iq pulse error. Second, based on the traditional Gaussian mutation operator, adaptive dynamic parameters are introduced to realize mutation. The simulation and experimental results show that the improved algorithm is applied to the model predictive torque system of permanent magnet synchronous motor, and the optimal weight coefficient can be set within less iterations, it reduces the torque error and current harmonic distortion rate. |
| Key words: model predictive torque control cost function weight coefficient Gaussian mutation pigeon-inspired optimization algorithm Gaussian mutation operator |
