Identification Modelling of the Hammerstein Nonlinear Systems Utilizing Adaptive Neural Fuzzy Networks and State Space Model-Reference-Cited by-同舟云学术

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Identification Modelling of the Hammerstein Nonlinear Systems Utilizing Adaptive Neural Fuzzy Networks and State Space Model

Published:2024-05-17 Issue: Volume:41 Page:1494-1498
ISSN:
Container-title:2024 IEEE 13th Data Driven Control and Learning Systems Conference (DDCLS)
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Author:

Zhu YanZong¹,Yang Yuesong¹,Li Feng¹,Zhou Zhou¹

Affiliation:

1. School of Electrical and Information Engineering, Jiangsu University of Technology,Changzhou,China,213001

Funder

National Natural Science Foundation of China

Changzhou Municipal Science and Technology Bureau

Qinglan Project of Jiangsu Province of China

Graduate practical innovation project of Jiangsu University of Technology

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10606543/10606546/10606730.pdf?arnumber=10606730

Reference20 articles.

1. Parameter Learning for the Nonlinear System Described by a Class of Hammerstein Models

2. Correlation analysis-based parameter learning of Hammerstein nonlinear systems with output noise

3. Data-Driven Hybrid Neural Fuzzy Network and ARX Modeling Approach to Practical Industrial Process Identification

4. A Convex Relaxation for Model Predictive Control of a Class of Hammerstein Systems

5. Parameter learning for the nonlinear system described by Hammerstein model with output disturbance

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