Unknown Input Kalman Filtering for Linear Discrete-Time Fractional Order Systems With Direct Feedthrough
Unknown Input Kalman Filtering for Linear Discrete-Time Fractional Order Systems With Direct Feedthrough
复制标题
DOI：
10.23919/ecc.2019.8795817
复制
发表时间：
2019-06
期刊：
影响因子：
--
通讯作者：
Martin Kupper;M. Pfeifer;Stefan Krebs;S. Hohmann
中科院分区：
文献类型：
--
作者：
Martin Kupper;M. Pfeifer;Stefan Krebs;S. Hohmann
本文提出一种分数阶系统伪状态和未知输入的联合估计算法。考虑了未知输入与输出之间存在直接馈通的特殊情况。给出了伪状态和输入估计无偏的充要条件。分数阶卡尔曼滤波器的预测步骤使用近似，因为它在实践中不能精确计算。因此，估计过程是次优的。尽管如此，该方法仍能对伪状态和未知输入进行准确的估计，并通过一个学术例子说明了这一点。
This paper presents an algorithm for a joint estimation of pseudo states and unknown inputs of a fractional order system. The special case where the unknown inputs have direct feedthrough to the outputs is considered. Necessary and sufficient conditions are given under which an unbiased pseudo state and input estimation is possible. The prediction step of the fractional Kalman filter uses an approximation as it can not be calculated exactly in practice. Therefore, the estimation procedure is suboptimal. Nevertheless, the method yields accurate estimates of pseudo states and unknown inputs which is illustrated by means of an academic example.