新型SMA基于Elmanspiking神经网络模拟的模糊PI控制器用于PMSM的转速扭矩调节
Lakshmipriya Natarajan1, Mamdooh Alwetaishi2, Chu Liang Lee3
1Department of Electrical and Electronics Engineering, Jai Shriram Enginnering College, Tirupur, Tamilnadu, India. lakshmipriyame09@gmail.com.
Scientific reports
|August 6, 2025
概括
本研究介绍了一种用于永久磁铁同步电机 (PMSM) 驱动器的新型软计算控制器. 开发的控制器有效调节转速和扭矩,证明了PMSM应用的有效性.
科学领域:
- 电气工程 电气工程
- 控制系统 控制系统
- 人工智能的人工智能
背景情况:
- 永磁同步电机 (PMSM) 在工业,机器人和医疗应用中至关重要.
- 由于固有的流量和扭矩合,PMSM控制具有挑战性.
- 现有的控制方法经常与PMSM复杂的动态作斗争.
研究的目的:
- 设计和验证一种用于PMSM转速和扭矩调节的新型软计算控制器.
- 为了解决PMSM中合流量和扭矩引起的控制困难.
- 为了提高PMSM驱动器的性能和适用性.
主要方法:
- 开发一种混合控制器,将基于粘液模具算法的Elman尖端神经网络 (ESNN) 与模糊推理比例积分 (PI) 控制器相结合.
- 实施软计算方法,在权重更新和增益确定中具有固有的随机性.
- 使用MATLAB进行性能分析的拟议控制器的模拟.
主要成果:
- 新型混合控制器在调节PMSM转速和扭矩方面表现出有效性.
- 统计分析证实了软计算控制器的有效性和适用性.
- 分析了控制器在体重更新和增益确定中的随机元素.
结论:
- 拟议的基于粘液模具算法的ESNN与模糊PI控制器混合,是PMSM驱动控制的有效和有效模型.
- 软计算方法为管理PMSM固有的控制挑战提供了强大的解决方案.
- 该控制器对需要精确调节转速和扭矩的先进应用具有前景.
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