实时随机参考跟踪非线性模型预测控制:风力轮机的案例研究
Mohammad Soleymani1, Nooshin Bigdeli1, Mehdi Rahmani1
1Department of Control Engineering, Imam Khomeini International University, Qazvin, Iran.
ISA transactions
|July 11, 2025
概括
这项研究引入了强大的非线性模型预测控制,用于跟踪随机引用,提高风力轮机的性能. 与标准方法相比,新方法可以提高输出功率并减少负载.
科学领域:
- 控制系统工程 控制系统工程
- 可再生能源系统可再生能源系统
- 随机过程 随机过程
背景情况:
- 非线性模型预测控制 (NMPC) 越来越多地从设定点稳定到参考跟踪.
- 参考信号的不确定性和动态预测的需要,特别是在风力轮机控制中,突出了对稳健跟踪NMPC的需求.
研究的目的:
- 提出一种新的随机参考跟踪NMPC与随机参考的动态预测.
- 通过对跟踪阶段成本函数的额外约束来确保对稳定的不变量集的趋同.
- 为了提高预测方法的效率和适用性,使用并行牛顿式方法.
主要方法:
- 开发一个随机参考跟踪NMPC算法.
- 纳入动态预测用于随机参考.
- 使用平行牛顿式方法实现计算效率.
- 专为风力轮机控制而设计,考虑随机的风速参考.
主要成果:
- 与名义NMPC相比,拟议的控制器表现出更强大的性能.
- 控制器在风力轮机中实现了更好的最佳功率提取.
- 在极端和疲劳场景下观察到空气动力学负载的显著减少.
结论:
- 开发的随机参考跟踪NMPC有效地处理风力轮机控制等应用中的随机参考.
- 这种方法保证了趋同到一个强大的不变量集,确保了稳定性.
- 该方法在风能系统的功率优化和负载减轻方面提供了更好的性能.
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