永久磁铁同步电机的动态自调节系统使用改进的超扭曲滑动模式观察器
Yanguo Huang1,2, Yingmin Xie1,2, Weilong Han1,2
1School of Electrical Engineering and Automation, Jiangxi University of Science and Technology, Ganzhou 341000, China.
Sensors (Basel, Switzerland)
|June 27, 2025
概括
这项研究引入了一种新的滑动模式观察器 (SMO),用于对永磁同步电机 (PMSM) 进行强大的无传感器控制. 这种新的方法自动调整误差因子,以改善转子位置估计和减少设计复杂性.
科学领域:
- 电气工程 电气工程
- 控制系统 控制系统
- 机器人技术 机器人技术 机器人技术
背景情况:
- 永磁同步电机 (PMSM) 的无感应控制对于需要精确的运动控制的应用至关重要.
- 在PMSM中的参数不匹配可以显著降低现有的无传感器控制策略的性能和稳定性.
- 传统的滑动模式观察器 (SMO) 通常需要低通波器 (LPF) 来缓解聊天,增加复杂性并可能影响动态响应.
研究的目的:
- 开发一种新的滑动模式观察器 (SMO),用于对PMSM进行强大的无传感器控制,以解决参数不匹配问题.
- 为了提高旋转器位置估计的精度,同时抑制观察员的喋喋不休.
- 简化PMSM无传感器控制系统的设计和实施.
主要方法:
- 设计一个包含可调节的误差因子的SMO,以减少聊天和消除对低通波器 (LPF) 的需求.
- 在SMO框架内分析错误因子对当前,速度和位置估计的影响.
- 开发一个神经网络算法,以确定最佳的错误系数,平衡聊抑制和控制精度.
- 基于神经网络的自我调整SMO模型的建议,用于自动调整错误系数以适应变化的电机操作条件.
主要成果:
- 拟议的可调节的错误系数SMO有效地减少了聊天,而不需要LPF.
- 这种基于神经网络的方法成功地平衡了聊抑制与对旋转器位置,速度和电流的高估计准确性.
- 模拟和实验结果验证了自调整SMO方法的可行性和有效性.
结论:
- 这种新型的自调整SMO提供了一个强大而简单的解决方案,用于在参数变化下无传感器控制PMSM.
- 适应性错误因子机制显著提高了观察员性能和系统可靠性.
- 这种方法有望提高PMSM驱动器在各种工业应用中的性能.
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