Robust Kalman filter for fractional order systems with uncertain colored noise variance

被引：0
|
作者：
Wang, Guanran [1 ]
Sun, Xiaojun [1 ,2 ,3 ]
机构：
[1] Heilongjiang Univ, Sch Elect Engn, Harbin, Heilongjiang, Peoples R China
[2] Key Lab Informat Fus Estimat & Detect, Harbin, Heilongjiang, Peoples R China
[3] Heilongjiang Univ, Sch Elect Engn, Xuefu Rd 74, Harbin 150080, Heilongjiang, Peoples R China
来源：
MEASUREMENT & CONTROL | 2024年 / 57卷 / 10期
关键词：
Centralized fusion; weighted fusion; robust filtering; fractional calculus; optimal estimation; CONTROLLER-DESIGN; STABILITY; CALCULUS;
D O I：
10.1177/00202940241241917
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
For fractional order systems with colored process noise, the discretization fractional order system model is used to construct the augmented vector defined by the state vector and colored process noise vector. Based on the augmented equation of fractional order systems, the robust local Kalman filtering algorithm for fractional order systems with colored process noise is derived. The matrix weighted fusion, weighted measurement fusion and centralized fusion methods were used to fuse and estimate the state of multi-sensor fractional order system. Simulation results show the effectiveness of the proposed algorithm.
引用
收藏
页码：1445 / 1455
页数：11
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