加速代学习控制使用分数高阶更新规则用于LTI系统
IEEE transactions on cybernetics
|March 4, 2026
概括
本研究引入了分数高阶更新规则 (FHUR),用于在线性系统中更快的代学习控制. 这种新方法通过适应追踪错误来加速融合,优于传统方法.
科学领域:
- 控制系统工程 控制系统工程
- 非线性动力学是一种非线性动力学.
- 分数微积分的计算.
背景情况:
- 代学习控制 (ILC) 对于线性时间不变系统 (LTI) 中的重复性任务至关重要.
- 传统的ILC方法经常面临缓慢的融合率,这限制了它们的实际应用.
- 在ILC中实现高精度需要高效和强大的控制策略.
研究的目的:
- 为LTI系统开发一个加速代学习控制方案.
- 通过使用新的更新规则来提高跟踪错误的收率.
- 分析拟议控制方案的收性质.
主要方法:
- 实现一个分数高阶更新规则 (FHUR),用于跟踪错误的自适应功率术语.
- 为增益选择开发两个最佳学习机制.
- 扰乱复合非线性映射方法的应用用于收分析.
主要成果:
- 通过利用高和低级功率术语来管理大和小的跟踪错误,FHUR有效地加速了趋同.
- 收分析证明,跟踪错误会收到一个不变的集合或限制周期,这取决于学习机制.
- 拟议的FHUR在数值模拟中表现出优越的性能,与传统的比例类型更新规则相比.
结论:
- 分数高阶更新规则 (FHUR) 为加速代学习控制提供了一个有希望的方法.
- 开发的控制方案通过调整FHUR参数来实现所需的跟踪精度.
- 这项研究为提高LTI系统中的ILC性能提供了一个强大的框架.
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