A time-varying forgetting factor stochastic gradient combined with Kalman filter algorithm for parameter identification of dynamic systems

被引：17

作者：

Li, Junpeng ^{[1
,2
]}

Hua, Changchun ^{[1
]}

Tang, Yinggan ^{[1
]}

Guan, Xinping ^{[1
,2
]}

机构：

[1] Yanshan Univ, Inst Elect Engn, Qinhuangdao 066004, Peoples R China

[2] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200240, Peoples R China

来源：

NONLINEAR DYNAMICS | 2014年 / 78卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Dynamic systems; Parameter estimation; Stochastic gradient; Kalman filter; STATE-SPACE SYSTEMS; MODEL; DELAY;

D O I：

10.1007/s11071-014-1540-9

中图分类号：

TH [机械、仪表工业];

学科分类号：

0802 ;

摘要：

Parameter estimation problem of a class of observer canonical state-space system is considered in this paper. By means of the property of the shift operator, the space-state model is transformed into the input-output representations. Then, a time-varying forgetting factor stochastic gradient combined with Kalman filter algorithm is proposed. The proposed algorithm is based on interactively estimating unknown parameters to achieve all the parameters identification of the system. A numerical example is provided to verify the effectiveness of the proposed algorithm.

引用

页码：1943 / 1952

页数：10

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