对于具有初始化非重复性的分数顺序系统的分数顺序代学习控制
Xiaofeng Xu1, Jinshui Chen1, Jiangang Lu1
1State Key Laboratory of Industrial Control Technology, College of Control Science and Engineering, Zhejiang University, Hangzhou, 310027, China.
ISA transactions
|October 12, 2023
概括
本研究涉及使用代学习控制的分数顺序系统中的初始化非重复性. 一种新的预先调节策略确保了跟踪错误的融合,改善了控制性能.
科学领域:
- 控制工程 控制工程 控制工程
- 非线性系统是非线性系统.
- 分数微积分的计算.
背景情况:
- 初始化非重复性是分数顺序系统的代学习控制 (ILC) 中的一个关键问题.
- 这种缺陷破坏了理论分析和实际应用中的完美跟踪.
- 现有的ILC方法往往忽视了分数顺序系统中初始条件的复杂性.
研究的目的:
- 调查初始化不可重复性对分数顺序系统的ILC性能的影响.
- 提出一种新的ILC方案,以减轻不可重复的初始化效应.
- 为拟议的控制战略建立严格的趋同条件.
主要方法:
- 开发一个Dα型的开闭循环代学习控制方案.
- 基于短内存原则的系统预条件的应用.
- 控制系统的两个严格的趋同条件的推导.
主要成果:
- 提出的预条件化策略有效地减少了由初始化不重复引起的跟踪错误.
- 追踪错误可以在开发的控制方案下汇聚到任何所需的范围.
- 该方法解释了分数顺序系统中初始条件的复杂性.
结论:
- 新的ILC方案成功地解决了分数顺序系统中的初始化非重复性问题.
- 系统预调提供了一种实际的方法来提高跟踪效率和性能.
- 这些发现为ILC在复杂的分数顺序非线性系统中提供了强大的框架.
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