Recursive parameter estimation and its convergence for bilinear systems-Reference-Cited by-同舟云学术

Recursive parameter estimation and its convergence for bilinear systems

Published:2020-01-08 Issue:5 Volume:14 Page:677-688
ISSN:1751-8652
Container-title:IET Control Theory & Applications
language:en
Short-container-title:IET Control Theory & Applications

Author:

Zhang Xiao¹,Ding Feng¹²^ORCID

Affiliation:

1. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), School of Internet of Things Engineering, Jiangnan UniversityWuxi214122People's Republic of China

2. College of Automation and Electronic Engineering, Qingdao University of Science and TechnologyQingdao266061People's Republic of China

Funder

National Natural Science Foundation of China

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Control and Optimization,Computer Science Applications,Human-Computer Interaction,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-cta.2019.0413

Reference70 articles.

1. Particle filtering based parameter estimation for systems with output-error type model structures

2. Weighted Parameter Estimation for Hammerstein Nonlinear ARX Systems

3. On Some Separated Algorithms for Separable Nonlinear Least Squares Problems

4. State estimation for bilinear systems through minimizing the covariance matrix of the state estimation errors

5. A filtering based multi-innovation extended stochastic gradient algorithm for multivariable control systems

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