State and Parameter Estimation Algorithm for State Space Model Based on Linear Neural Network and Kalman Filter

被引：0
|
作者：
Yang, Yuhang [1 ]
Shi, Ying [1 ]
机构：
[1] Heilongjiang Univ, Coll Elect Engn, Harbin, Peoples R China
来源：
2019 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS AND AUTOMATION (ICMA) | 2019年
关键词：
Kalman filter; recursive extended least square; linear neural network; parameter estimation; SYSTEMS; IDENTIFICATION;
D O I：
10.1109/icma.2019.8816520
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, based on Kalman filter and Linear Neural Network, state and parameter estimation problem are researched for a controlled state space system with unknown model parameters. A computer simulation illustration is given to verify the availability of the presented algorithm.
引用
收藏
页码：2320 / 2324
页数：5
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