Observer-Based Controller of Two-Dimensional Large-Scale Polynomial Fuzzy Systems*

This study focuses on the observer-based feedback controller design of two-dimensional(2-D) discrete large-scale polynomial fuzzy systems. Firstly, a two-dimensional large-scale fuzzy system is established, with the 2-D polynomial Roesser model as the local model, including unknown interconnection terms. The separation property is established under the 2-D large-scale fuzzy framework. By this way, the fuzzy controller and the fuzzy observer can be individually solved and the corresponding closed-loop 2-D polynomial fuzzy system is asymptotically stable. The developed design algorithms are convex SOS conditions, which can be directly solved by the SOSTOOLS. Finally, a numerical example is shown to demon-strated the effectiveness of the proposed approach.

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Publication Details

Published
2024-12-12
DOI
https://doi.org/10.1109/icarcv63323.2024.10821651
Primary Topic
Advanced Data Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00

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Observer-Based Controller of Two-Dimensional Large-Scale Polynomial Fuzzy Systems*

Li-Zhen Li
Advanced Data Processing Techniques
article

Observer-Based Controller of Two-Dimensional Large-Scale Polynomial Fuzzy Systems*

Li-Zhen Li
article en

Abstract

This study focuses on the observer-based feedback controller design of two-dimensional(2-D) discrete large-scale polynomial fuzzy systems. Firstly, a two-dimensional large-scale fuzzy system is established, with the 2-D polynomial Roesser model as the local model, including unknown interconnection terms. The separation property is established under the 2-D large-scale fuzzy framework. By this way, the fuzzy controller and the fuzzy observer can be individually solved and the corresponding closed-loop 2-D polynomial fuzzy system is asymptotically stable. The developed design algorithms are convex SOS conditions, which can be directly solved by the SOSTOOLS. Finally, a numerical example is shown to demon-strated the effectiveness of the proposed approach.

Shanghai University of Electric Power (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 70%
Advanced Data Processing Techniques
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