An adaptive unscented particle filter for a nonlinear fractional-order system with unknown fractional-order and unknown parameters

被引：1

作者：

Jiao, Zhiyuan ^{[1
]}

Gao, Zhe ^{[1
,2
,3
]}

Chai, Haoyu ^{[1
]}

Xiao, Shasha ^{[1
]}

Jia, Kai ^{[1
]}

机构：

[1] Liaoning Univ, Sch Math & Stat, Shenyang 110036, Peoples R China

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

[3] Jilin Univ, Key Lab Symbol Computat & Knowledge Engn, Minist Educ, Changchun 130012, Peoples R China

来源：

SIGNAL PROCESSING | 2024年 / 220卷

关键词：

Adaptive unscented particle filter; Nonlinear fractional-order systems; Unknown order; Unknown parameters; State estimation; KALMAN FILTER; CHARGE ESTIMATION; STATE; TRACKING; OBSERVER; DESIGN;

D O I：

10.1016/j.sigpro.2024.109443

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

An unscented particle filter (UPF) is proposed for a nonlinear fractional -order system (NFOS) with an unknown order (UO) and unknown parameters. The Gr & uuml;nwald-Letnikov difference is used to discretize the continuous -time NFOS and the corresponding difference equation is acquired. For each sampled particle, a unscented transformation is applied, and the particles are afterwards optimized using a resampling algorithm. Furthermore, the augmented equations of the states, UO, and unknown parameters are established by an augmented vector method. The proposed fractional -order UPF is more accurate in estimating states than the fractional -order unscented Kalman filter and the fractional -order particle filter. Besides, the adaptive fractionalorder UPF effectively estimate the UO and unknown parameters. Finally, two numerical examples and a practical example are used to verify the effectiveness of the proposed algorithm.

引用

页数：12

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