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Discrete Kalman Filter Design for Kuramoto-Sivashinsky Equation

机译:Kuramoto-Sivashinsky方程的离散Kalman滤波器设计

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Kuramoto-Sivashinsky partial differential equation (KSE) has attracted a lot of attention from academia and industry due to its ability to describe various physical phenomena associated with both wave and propagation wave front dynamics. This work addresses infinite-dimensional discrete-time Kalman filter design for KSE by applying a state-of-the-art Crank-Nicolson discretization framework which does not account for spatial approximation or order reduction of the underlying model. A novel infinite-dimensional discrete-time Crank-Nicolson discretization is provided and utilized for KSE discretization in time, which is amenable to the ensuing discrete Kalman filter design. In addition, a two-step infinite-dimensional discrete-time Kalman filter is developed for the state estimation of KSE model augmented with the state and measurement noises. Finally, the effectiveness of the presented discrete-time Kalman filter is investigated and validated by simulations.
机译:Kuramoto-Sivashinsky偏微分方程(KSE)由于能够描述与波和传播波前动力学相关的各种物理现象而备受学术界和工业界的关注。这项工作通过应用最新的Crank-Nicolson离散化框架解决了KSE的无限维离散时间卡尔曼滤波器设计,该框架不考虑基础模型的空间近似或阶数缩减。提供了一种新颖的无限维离散时间Crank-Nicolson离散化方法,并将其用于KSE的时间离散化,这适用于随后的离散卡尔曼滤波器设计。此外,针对状态和测量噪声增加的KSE模型的状态估计,开发了两步无限维离散时间卡尔曼滤波器。最后,通过仿真研究和验证了提出的离散时间卡尔曼滤波器的有效性。

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