基于智能方法的增强直接扭矩控制,用于由三级逆变器供电的双输入感应机器
Abderrahmane Moussaoui1, Djilani Ben Attous2, Habib Benbouhenni1
1Department of Electrical Engineering, LAAS Laboratory, National Polytechnic School of Oran- Maurice Audin, BP 1523 Oran El M'naouer, Algeria.
这项研究介绍了一种适应性神经模糊推理系统 (ANFIS),用于双引力机器的直接扭矩控制 (DTC). 基于ANFIS的DTC显著降低了扭矩和流量波动以及定子电流波.
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:
- 在变速应用中,双输入感应机 (DFIM) 是至关重要的.
- 传统的直接扭矩控制 (DTC) 方法经常受到扭矩和流量波动以及波扭曲的影响.
- 提高DFIM驱动器的性能需要先进的控制策略来缓解这些问题.
研究的目的:
- 为DFIMs开发和评估基于24个部门的直接扭矩控制 (DTC) 的自适应性神经模糊推理系统 (ANFIS).
- 为了最大限度地减少扭矩和流量波动以及DFIM驱动器中的定子电流总波扭曲 (THD).
- 将拟议的ANFIS-DTC方法与传统的DTC方法的性能进行比较.
主要方法:
- 实施了24个部门的DTC战略,用于DFIM,使用3级中性点合逆变器.
- 用ANFIS控制器取代了传统的流量和扭矩的hysteresis控制器.
- 利用MATLAB模拟,在各种操作条件下测试拟议的ANFIS-DTC和传统DTC.
主要成果:
- 基于ANFIS的DTC显著降低了定子电流THD,高达81.43%.
- 与传统的DTC相比,扭矩波动减少了多达59.31%.
- 速度超速被最大限度地降低了98.83%,证明了卓越的动态性能.
结论:
- 拟议的24个部门DTC-ANFIS在最大限度地减少扭矩和流量波动以及DFIM驱动器的定子电流THD方面提供了卓越的性能.
- 基于ANFIS的控制策略在提高DFIM驱动特性方面被证明是非常有效和高效的.
- 这种先进的控制方法为需要高性能电机控制的电气应用提供了有希望的解决方案.
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