ABAnouar Boukhlouf
Anouar Boukhlouf
*This is an algorithmically generated author record based on publicly available information.
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The organizations/institutes from the scholar's latest article
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Anouar Boukhlouf has a total of 2 co-authors. Here are the top co-authors by number of shared publications:
- Mohamed Yacine Hammoudi
Mohamed Khider University of Biskra, Algeria
1 shared publication - Wail Hamdi
Laboratory of Energy Systems Modeling (LMSE), Department of Electrical Engineering, University of Biskra, BP 145, Biskra 07000, Algeria
1 shared publication
Latest Publications
- Open Access
- 15 November 2023
- Published by MDPI AG in Engineering Proceedings
- Vol. 58 (1) , 28
Observer Design for Takagi–Sugeno Fuzzy Systems with Unmeasurable Premise Variables Based on Differential Mean Value Theorem
In this work, we present the design of an observer for Takagi–Sugeno fuzzy systems with unmeasurable premise variables. Moving away from Lipschitz-based and attenuation-based methods—which fall short in eliminating the mismatching terms in the estimation error dynamics—we leverage the differential mean value theorem. This approach not only removes these terms but also streamlines the factorization of the estimation error dynamics, making it directly proportional to the estimation error. To ensure the asymptotic convergence of the estimation error, we apply the second Lyapunov theorem, which provides sufficient stability conditions described as linear matrix inequalities. A numerical example applied on a three-tank hydraulic system is presented to demonstrate the observer’s effectiveness.- 15 November 2023
- Published by MDPI AG in Engineering Proceedings
- Vol. 58 (1) , 28
Open AccessObserver Design for Takagi–Sugeno Fuzzy Systems with Unmeasurable Premise Variables Based on Differential Mean Value Theorem
In this work, we present the design of an observer for Takagi–Sugeno fuzzy systems with unmeasurable premise variables. Moving away from Lipschitz-based and attenuation-based methods—which fall short in eliminating the mismatching terms in the estimation error dynamics—we leverage the differential mean value theorem. This approach not only removes these terms but also streamlines the factorization of the estimation error dynamics, making it directly proportional to the estimation error. To ensure the asymptotic convergence of the estimation error, we apply the second Lyapunov theorem, which provides sufficient stability conditions described as linear matrix inequalities. A numerical example applied on a three-tank hydraulic system is presented to demonstrate the observer’s effectiveness.