使用储计算的动态系统的自适应控制
Swarnendu Mandal1, Swati Chauhan2, Umesh Kumar Verma2
1International Research Center for Neurointelligence (WPI-IRCN), The University of Tokyo, Tokyo, Japan.
Chaos (Woodbury, N.Y.)
|September 4, 2025
概括
本研究介绍了一种数据驱动的方法,使用储计算来进行动态系统的自适应控制. 它允许精确控制目标状态,使用最小的训练数据,在模拟和现实世界的电子电路中进行验证.
科学领域:
- 复杂的系统
- 非线性动力学
- 机器学习
背景情况:
- 动态系统通常需要适应性控制策略来实现所需状态.
- 储计算提供了一个强大的框架来处理来自复杂系统的时间序列数据.
研究的目的:
- 为动态系统开发和演示数据驱动的自适应控制技术.
- 利用储存器计算来预测系统参数和生成控制信号.
- 通过各种系统吸引力和初始条件验证控制方案的有效性.
主要方法:
- 使用储存器计算来训练从时间序列数据中预测系统参数的模型.
- 根据预测的系统参数开发反控制信号.
- 使用控制信号引导动态系统向目标状态.
- 通过数值模拟验证方法,并在物理Rössler系统电路上实现.
主要成果:
- 储计算方法成功地从时间序列数据中预测系统参数.
- 开发的控制信号有效地将动态系统驱动到任意的目标吸引器.
- 该方法在各种吸引器类型和初始条件中显示出强度.
- 在Rössler系统电子电路上成功实施证实了其实际可用性.
结论:
- 拟议的数据驱动的自适应控制方法,由储计算提供,为动态系统提供一种高效和多功能方法.
- 这种技术需要最少的训练数据,使其适用于现实世界.
- 通过机器学习为复杂系统的先进控制策略铺平了道路.
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