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Dual Estimation of Fractional Variable Order Based on the Unscented Fractional Order Kalman Filter for Direct and Networked Measurements

机译:基于无味分数阶卡尔曼滤波器的分数阶可变对偶估计,用于直接和网络测量

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摘要

The paper is devoted to variable order estimation process when measurements are obtained in two different ways: directly and by lossy network. Since the problem of fractional order estimation is highly nonlinear, dual estimation algorithm based on Unscented Fractional Order Kalman filter has been used. In dual estimation process, state variable and order estimation have been divided into two sub-processes. For estimation state variables and variable fractional order, the Fractional Kalman filter and the Unscented Fractional Kalman filter have been used, respectively. The order estimation algorithms were applied to numerical examples and to real fractional variable order inertial system realized as an analog circuit.
机译:当以两种不同的方式获得测量结果时,本文致力于变量阶估计过程:直接和有损网络。由于分数阶估计的问题是高度非线性的,因此使用了基于无味分数阶卡尔曼滤波器的双重估计算法。在双重估计过程中,状态变量和阶次估计已分为两个子过程。对于估计状态变量和可变分数阶,分别使用了分数阶卡尔曼滤波器和Unscented分数阶卡尔曼滤波器。将阶数估计算法应用于数值示例,以及应用于实现为模拟电路的实数分数阶可变惯性系统。

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