一种基于瞬间的卡尔曼过方法,用于集体系统中的估计
André Luiz P de Lima1, Jr-Shin Li1
1Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, Missouri 63130, USA.
Chaos (Woodbury, N.Y.)
|June 3, 2024
概括
本研究为大型动态系统引入了一种新的基于时刻的卡尔曼波器,通过将数据转换为时刻域来降低计算成本并提高状态估计的准确性.
科学领域:
- 动态系统和控制理论.
- 计算数学 计算数学 计算数学
- 数据科学数据科学数据科学
背景情况:
- 大规模的动态系统在状态估计和因高维数据而导致的错误减少方面存在计算挑战.
- 基于时刻的表示提供了一种总结集体状态和动态的方法,有助于数据处理.
- 现有的卡尔曼波器方法与大数据集固有的维度诅咒作斗争.
研究的目的:
- 为了重新塑造卡尔曼波器,以便在集体系统的时刻域中应用.
- 为了开发一个时刻合奏噪声过技术.
- 为了利用直角基础结构在瞬间表示中所带来的好处,以改进过.
主要方法:
- 卡尔曼波器被调整为在时刻域中运行,使用正常化的莱根德多项式.
- 定义了一个时刻系统,利用其直角基础来过高斯干扰.
- 该方法适用于和振荡器和飞机动力学模型的集合.
主要成果:
- 与状态空间表示相比,拟议的方法显著减少了问题的维度.
- 在累积绝对误差和共差方面取得了实质性的减少.
- 通过在当下框架内的操作来证明降低计算成本.
- 展示了与异常值和局部不准确性相对应的时刻数据的稳定性.
结论:
- 时刻域卡尔曼波器为大规模动态系统的状态估计提供了一个计算效率高,准确的方法.
- 使用直角矩阵基可以提高各种干扰类型的过性能.
- 这种方法为处理高维数据提供了强大的替代方案,优于传统的状态空间方法.
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