Predictive Controller for Large-Scale Fuzzy Polynomial Systems

This paper presents an innovative method to tackle the predictive-control challenges associated with large-scale fuzzy polynomial systems comprising interconnected polynomial fuzzy systems. This study models large-scale nonlinear fuzzy systems in a polynomial framework, which can reduce the number of fuzzy rules. We derive the conditions for controller synthesis in the main theorem using the Lyapunov theory and sum-of-squares technique. Simulation results confirm the validity and efficiency of this approach.

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Publication Details

Journal
Journal of Advanced Computational Intelligence and Intelligent Informatics
Published
2024-09-19
DOI
https://doi.org/10.20965/jaciii.2024.p1186
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
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article

Predictive Controller for Large-Scale Fuzzy Polynomial Systems

Li-Zhen Li, Ziqin Xu
Journal of Advanced Computational Intelligence and Intelligent Informatics
Advanced Control Systems Optimization
article

Predictive Controller for Large-Scale Fuzzy Polynomial Systems

Li-Zhen Li, Ziqin Xu
article en

Abstract

This paper presents an innovative method to tackle the predictive-control challenges associated with large-scale fuzzy polynomial systems comprising interconnected polynomial fuzzy systems. This study models large-scale nonlinear fuzzy systems in a polynomial framework, which can reduce the number of fuzzy rules. We derive the conditions for controller synthesis in the main theorem using the Lyapunov theory and sum-of-squares technique. Simulation results confirm the validity and efficiency of this approach.

Journal of Advanced Computational Intelligence and Intelligent InformaticsVol. 28(5)
Shanghai University of Electric Power (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 83%
Advanced Control Systems Optimization
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