Extended Kalman filters for nonlinear fractional-order systems perturbed by colored noises

被引：20
作者：
Yang, Chao [1 ]
Gao, Zhe [1 ,2 ]
Liu, Fanghui [1 ]
Ma, Ruicheng [1 ]
机构：
[1] Liaoning Univ, Sch Math, Shenyang 110036, Peoples R China
[2] Liaoning Univ, Coll Light Ind, Shenyang 110036, Peoples R China
来源：
ISA TRANSACTIONS | 2020年 / 102卷
基金：
中国博士后科学基金;
关键词：
Fractional-order extended Kalman filters; Colored noises; State estimation; Fractional-order average derivative; STOCHASTIC-SYSTEMS; DESIGN; STATE;
D O I：
10.1016/j.isatra.2019.07.010
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The fractional-order extended Kalman filter (FEKF) algorithm for a nonlinear fractional-order system perturbed by the colored noise is presented. Firstly, the first-order Taylor expansion is employed to linearize the nonlinear functions in the estimated system. Then, Grunwald-Letnikov difference (GLD) and the concept of fractional-order average derivative (FOAD) are employed to discretize nonlinear fractional-order systems perturbed by colored fractional-order process or measurement noise. An augmented system determined by the state and colored noises is presented to treat colored noises. Hence, the FEKFs using GLD and FOAD are carried out, respectively. By comparing two kinds of Kalman filters, FEKFs using FODA can gain the better effect of filtering for colored process or measurement noise to raise the estimation precision. Finally, we discuss three examples to show the validity of investigated FEKFs. (C) 2019 ISA. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：68 / 80
页数：13
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