Fractional-order Kalman filters for continuous-time fractional-order systems involving correlated and uncorrelated process and measurement noises

被引：6

作者：

Liu, Fanghui ^{[1
]}

Gao, Zhe ^{[2
]}

Yang, Chao ^{[1
]}

Ma, Ruicheng ^{[1
]}

机构：

[1] Liaoning Univ, Sch Math, Shenyang, Liaoning, Peoples R China

[2] Liaoning Univ, Coll Light Ind, Shenyang 110036, Liaoning, Peoples R China

来源：

TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL | 2019年 / 41卷 / 07期

基金：

中国国家自然科学基金;

关键词：

Fractional-order system; Kalman filter; state estimation; fractional-order average derivative; correlated noise; STATE; CONTROLLER; OBSERVER;

D O I：

10.1177/0142331218790786

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This paper presents fractional-order Kalman filters using the fractional-order average derivative method for linear fractional-order systems involving process and measurement noises. By using the fractional-order average derivative method, a difference equation model is obtained by discretizing the investigated continuous-time fractional-order system, and the accuracy of state estimation is improved. Meanwhile, compared with the Tustin generating function, the fractional-order average derivative method proposed in this paper can reduce computation load and save calculation time. Two kinds of fractional-order Kalman filters are given, for the correlated and uncorrelated cases, in terms of the process and measurement noises for linear fractional-order systems, respectively. Finally, simulation results are illustrated to verify the effectiveness of the proposed Kalman filters using the fractional-order average derivative method.

引用

页码：1933 / 1947

页数：15

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