Recursive least squares estimation methods for a class of nonlinear systems based on non‐uniform sampling-Reference-Cited by-同舟云学术

Recursive least squares estimation methods for a class of nonlinear systems based on non‐uniform sampling

Published:2021-05-09 Issue:8 Volume:35 Page:1612-1632
ISSN:0890-6327
Container-title:International Journal of Adaptive Control and Signal Processing
language:en
Short-container-title:Int J Adapt Control Signal Process

Author:

Liu Qilin¹^ORCID,Chen Feiyan²,Ding Feng¹^ORCID,Alsaedi Ahmed³,Hayat Tasawar³

Affiliation:

1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering Jiangnan University Wuxi China

2. School of Science Xi'an Jiaotong Liverpool University Suzhou PR China

3. Department of Mathematics King Abdulaziz University Jeddah Saudi Arabia

Funder

Higher Education Discipline Innovation Project

National Natural Science Foundation of China

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Signal Processing,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/acs.3263

Reference111 articles.

1. A new filter-based stochastic gradient algorithm for dual-rate ARX models

2. Fully parametric identification for continuous time fractional order Hammerstein systems

3. Hierarchical least squares parameter estimation algorithm for two-input Hammerstein finite impulse response systems

4. Three‐stage forgetting factor stochastic gradient parameter estimation methods for a class of nonlinear systems

5. Robust extended recursive least squares identification algorithm for Hammerstein systems with dynamic disturbances

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