Sensor and actuator faults estimation for T-S fuzzy systems subject to disturbances and uncertainties
Résumé
This paper addresses the estimation problem of sensor and actuator faults (SAF) for nonlinear systems represented by Takagi-Sugeno (T-S) fuzzy models with parametric uncertainties and Unknown Bounded Disturbances (UBD). For this, an adaptive descriptor observer is designed to estimate jointly state and SAF vectors. Two sufficient conditions are deduced in form of Linear Matrix Inequalities (Lillis) using Lyapunov theory to prove the existence of this observer. A robustness to disturbance is elaborated by considering the Hoc performance index. Finally, a numerical example and simulation results are illustrated to prove the mentioned process efficiency.