New Results on Proportional Plus Derivative Feedback Control for Singular Takagi-Sugeno Fuzzy Systems Based on Observer Design

This paper presents new insights into the design of a proportional plus derivative (PD) feedback controller for singular Takagi-Sugeno (T-S) fuzzy systems based on observer design. By introducing certain free-weighting matrices and employing Lyapunov theory, sufficient conditions for ensuring the stability of the closed-loop system are provided in the form of linear matrix inequalities (LMIs). To solve for the controller and observer parameters, an iterative algorithm-based solution approach is proposed. Finally, the effectiveness of the proposed method is validated through a simulation example.

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Published
2024-11-01
DOI
https://doi.org/10.1109/cac63892.2024.10865149
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

New Results on Proportional Plus Derivative Feedback Control for Singular Takagi-Sugeno Fuzzy Systems Based on Observer Design

He-Bin Wang, Huayang Zhang
Network Security and Intrusion Detection
article

New Results on Proportional Plus Derivative Feedback Control for Singular Takagi-Sugeno Fuzzy Systems Based on Observer Design

He-Bin Wang, Huayang Zhang
article en

Abstract

This paper presents new insights into the design of a proportional plus derivative (PD) feedback controller for singular Takagi-Sugeno (T-S) fuzzy systems based on observer design. By introducing certain free-weighting matrices and employing Lyapunov theory, sufficient conditions for ensuring the stability of the closed-loop system are provided in the form of linear matrix inequalities (LMIs). To solve for the controller and observer parameters, an iterative algorithm-based solution approach is proposed. Finally, the effectiveness of the proposed method is validated through a simulation example.

Liaoning University of Technology (CN)
Department of Education of Liaoning Province, Liaoning University
Climate action
Openalex Percentile: Top 68%
Network Security and Intrusion Detection
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