迭代学习及其在励磁控制系统中的应用研究的开题报告.docx

迭代学习及其在励磁控制系统中的应用研究的开题报告 摘要： 本文介绍了迭代学习控制（ILC）的基本概念和原理，并讨论了ILC在励磁控制中的应用。ILC是一种针对重复执行的任务或系统，通过对上一次执行过程的反馈信息进行学习和调整来提高控制精度的控制方法。在励磁控制中，ILC的应用可以提高励磁系统的跟踪精度和稳定性，从而提升整个电力系统的可靠性和效率。本文将基于先前的研究成果，结合具体的应用场景，设计和实现一种基于ILC的励磁控制系统，并评估其性能和有效性。研究结果表明，ILC技术在励磁控制中的应用是可行的和有效的。 关键词：迭代学习控制，励磁控制，跟踪精度，稳定性，电力系统 Abstract: This paper introduces the basic concepts and principles of iterative learning control (ILC), and discusses the application of ILC in excitation control. ILC is a control method for tasks or systems that are repeatedly executed. It improves control accuracy by learning and adjusting the feedback information from the previous execution process. In excitation control, the application of ILC can improve the tracking accuracy and stability of the excitation system, thereby enhancing the reliability and efficiency of the entire power system. Based on previous research results and specific application scenarios, this paper designs and implements an ILC-based excitation control system and evaluates its performance and effectiveness. The study results show that the application of ILC technology in excitation control is feasible and effective. Keywords: Iterative learning control, excitation control, tracking accuracy, stability, power system.