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Journals / An International Journal of Optimization and Control: Theories & Applications (IJOCTA) / 2021 / Cilt: 11 - Sayı: 1

Simultaneous state and fault estimation for Takagi-Sugeno implicit models with Lipschitz constraints

Jalal SOULAMI
Manal OUZAZ
Abdellatif El ASSOUDI
El Hassane El YAAGOUBI
Pages
100–108
Publication Date
2022-10-11
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Finally, numerical simulation results are given to highlight the performances of the proposed method by using a TSIM of a single-link flexible joint robot.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This paper presents a state and fault observer design for a class of Takagi Sugeno implicit models (TSIMs) with unmeasurable premise variables satisfy ing the Lipschitz constraints.
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Key Findings & Data:The fault variable is constituted by the actuator and sensor faults.
💡
Conclusion & Impact:Finally, numerical simulation results are given to highlight the performances of the proposed method by using a TSIM of a single-link flexible joint robot.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

This paper presents a state and fault observer design for a class of Takagi Sugeno implicit models (TSIMs) with unmeasurable premise variables satisfy ing the Lipschitz constraints. The fault variable is constituted by the actuator and sensor faults. The actuator fault affects the state and the sensor fault affects the output of the system. The approach is based on the separation between dynamic and static relations in the TSIM. Firstly, the method begins by decomposing the dynamic equations of the algebraic equations. Secondly, the fuzzy observer design that satisfies the Lipschitz conditions and permits to estimate simultaneously the unknown states, actuator and sensor faults is developed. The aim of this approach for the observer design is to construct an augmented model where the fault variable is added to the state vector. The exponential convergence of the state estimation error is studied by using the Lyapunov theory and the stability condition is given in term of only one linear matrix inequality (LMI). Finally, numerical simulation results are given to highlight the performances of the proposed method by using a TSIM of a single-link flexible joint robot.

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Cite This Article

SOULAMI, J., OUZAZ, M., ASSOUDI, A. E., YAAGOUBI, E. H. E. (2022). Simultaneous state and fault estimation for Takagi-Sugeno implicit models with Lipschitz constraints. An International Journal of Optimization and Control: Theories & Applications (IJOCTA), Cilt: 11 - Sayı: 1, 100–108. https://ajindex.com/articles/440529

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