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Robust fault estimation and fault‐tolerant tracking control for uncertain Takagi–Sugeno fuzzy systems: Application to single link manipulator
Author(s) -
Makni Salama,
Bouattour Maha,
El Hajjaji Ahmed,
Chaabane Mohamed
Publication year - 2021
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.3231
Subject(s) - control theory (sociology) , actuator , observer (physics) , nonlinear system , fuzzy logic , computer science , linear matrix inequality , robustness (evolution) , tracking error , fault tolerance , fault detection and isolation , mathematics , mathematical optimization , control (management) , artificial intelligence , gene , distributed computing , biochemistry , chemistry , physics , quantum mechanics
Summary This article concerns the estimation and tracking control problems for Takagi–Sugeno systems with disturbances and norm bounded uncertainties in presence of sensor and actuator faults (SAF). First, we propose a robust fuzzy observer (RFO) design method to estimate both state and SAF for the considered class of the nonlinear systems. Then, this RFO‐based fault tolerant tracking control is developed not only to compensate the SAF effects but also to ensure the state convergence to desired trajectories in spite of their presence. To reduce the conservatism of design conditions, observer and controller gains are calculated in a single step by solving a set of linear matrix inequality constraints. H ∞ criterion is used to attenuate disturbance effects and to reduce the tracking error. Finally, simulation results by considering two types of actuator fault and comparative study on a single link flexible joint manipulator are provided to underline the performances of the mentioned process.