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
收藏
页码：274 / 279
页数：6
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