Robust adaptive proportional integral observer for faults estimation: Application to Bioreactor - Université de Picardie Jules Verne
Communication Dans Un Congrès Année : 2019

Robust adaptive proportional integral observer for faults estimation: Application to Bioreactor

Résumé

In this work, we focus on state and both sensor and actuator fault (SAF) estimations for Takagi-Sugeno (T-S) fuzzy systems in the presence of an Unknown Bounded Disturbance (UBD). To reach this objective, we design a novel observer to estimate simultaneously state and SAF vectors. Indeed, we study the robustness against disturbance by considering the H-infinity performance. For the stability, sufficient conditions are given in term of relaxed Linear Matrix Inequalities (LMIs) where the descriptor formulation is considered. To prove the efficiency of our proposed method, a reduced bioreactor model and simulation results are illustrated.
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Dates et versions

hal-03633207 , version 1 (06-04-2022)

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  • HAL Id : hal-03633207 , version 1

Citer

Salama Makni, Maha Bouattour, Ahmed El Hajjaji, Mohamed Chaabane. Robust adaptive proportional integral observer for faults estimation: Application to Bioreactor. 2019 19TH INTERNATIONAL CONFERENCE ON SCIENCES AND TECHNIQUES OF AUTOMATIC CONTROL AND COMPUTER ENGINEERING (STA), Mar 2019, Sousse, Tunisia. pp.269-273. ⟨hal-03633207⟩
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