State filtering‐based least squares parameter estimation for bilinear systems using the hierarchical identification principle-Reference-Cited by-同舟云学术

State filtering‐based least squares parameter estimation for bilinear systems using the hierarchical identification principle

Published:2018-08 Issue:12 Volume:12 Page:1704-1713
ISSN:1751-8652
Container-title:IET Control Theory & Applications
language:en
Short-container-title:IET Control Theory & Applications

Author:

Zhang Xiao¹,Ding Feng¹,Xu Ling¹,Yang Erfu²

Affiliation:

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

2. Department of Design, Manufacture and Engineering ManagementSpace Mechatronic Systems Technology Laboratory, Strathclyde Space Institute, University of StrathclydeGlasgowG1 1XJScotland, UK

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.2018.0156

Reference55 articles.

1. LaSalle-Type Theorem and Its Applications to Infinite Horizon Optimal Control of Discrete-Time Nonlinear Stochastic Systems

2. Unbiased Minimum Variance Fault and State Estimation for Linear Discrete Time-Varying Two-Dimensional Systems

3. Some remarks on stability of stochastic singular systems with state-dependent noise

4. Iterative identification algorithms for bilinear-in-parameter systems with autoregressive moving average noise

5. Iterative parameter identification for pseudo‐linear systems with ARMA noise using the filtering technique

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