The Auxiliary Model Based Hierarchical Estimation Algorithms for Bilinear Stochastic Systems with Colored Noises

被引：30

作者：

Guo, Chunqiu ^{[1
]}

Wang, Longjin ^{[1
]}

Deng, Fang ^{[1
]}

机构：

[1] Qingdao Univ Sci & Technol, Sch Elect & Mech Engn, Qingdao 266061, Shandong, Peoples R China

来源：

INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS | 2020年 / 18卷 / 03期

基金：

中国国家自然科学基金;

关键词：

Auxiliary model; bilinear system; hierarchical identification; least squares; recursive identification; PARAMETER-ESTIMATION ALGORITHM; LEAST-SQUARES IDENTIFICATION; NONLINEAR-SYSTEMS; DYNAMICAL-SYSTEMS; MULTI-INNOVATION; DESIGN; SPEED; STATE;

D O I：

10.1007/s12555-019-0115-4

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 considers the parameter identification for a class of nonlinear stochastic systems with colored noise. An input-output representation is derived by eliminating the state variables in the bilinear system. Based on the obtained identification model, a recursive generalized extend least squares algorithm is proposed by using the auxiliary model identification idea. Moreover, a two-stage recursive generalized extended least squares algorithm is presented to reduce the computational burden by using the hierarchical identification principle and the auxiliary model identification idea, respectively. A stochastic gradient identification algorithm is proposed for comparison. The simulation results show that the proposed algorithms have a good performance in estimating the parameters of the bilinear systems with colored noises.

引用

页码：650 / 660

页数：11

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