Multi-innovation parameter and state estimation for multivariable state space systems

被引：2

作者：

Wang, Xuehai ^{[1
]}

Zhu, Fang ^{[2
]}

Huang, Fenglin ^{[1
]}

机构：

[1] Xinyang Normal Univ, Sch Math & Stat, Xinyang 464000, Peoples R China

[2] Xinyang Normal Univ, Inst Educ Sci, Xinyang 464000, Peoples R China

来源：

INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL | 2019年 / 32卷 / 3-4期

基金：

中国国家自然科学基金;

关键词：

parameter estimation; state space; recursive identification; multi-innovation; multivariable system; Kalman filter; IDENTIFICATION; ALGORITHM; MODELS;

D O I：

10.1504/IJMIC.2019.103659

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 work considers the modelling and estimation problem of multivariable state space systems. Based on the observer canonical form, the identification model is derived and a combined state and multi-innovation estimation algorithm is presented by means of the Kalman filter principle. The efficacy of the algorithm is verified by a simulation example.

引用

页码：274 / 279

页数：6

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