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International audience; 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.

In this work, we investigate the problem of control for nonlinear systems represented by Takagi-Sugeno (T-S) fuzzy models affected by both sensor and actuator faults subject to an unknown bounded disturbances (UBD). For this, we design an adaptive observer to estimate state, sensor and actuator fault vectors simultaneously despite the presence of external disturbances. Based on this observer, we develop a fault tolerant control (FTC) law not only to stabilize closed loop system, but also to compensate the fault effects. For the observer-based controller design, we propose less conservative conditions formulated in terms of linear matrix inequalities (LMIs). Moreover, both observer and controller gains are calculated via solving a set of LMIs only in single step. Finally, comparative results and an application to single-link flexible joint robot are afforded to prove the efficiency of the proposed design.

In this work, the admissibility analysis and the control problem are investigated for nonlinear singular systems represented by interval type-2 Takagi-Sugeno (T-S) fuzzy models with time delay. First, the interval type-2 fuzzy singular systems with time delay have been described. Second, the admissibility analysis of the autonomous singular systems is studied. Third, the control problem has been investigated. For this, an interval type-2 fuzzy control law is designed to guarantee the admissibility of the closed-loop system despite the presence of uncertainties and time delay. To demonstrate the existence of the proposed controller, by using generalised integral inequalities, sufficient delay-dependent conditions are given in terms of Linear Matrix Inequalities (LMIs). Finally, an application to inverted pendulum system presented by interval type-2 fuzzy models is afforded to show the effectiveness of the suggested method.

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 $H_{\infty}$ performance. For the stability, sufficient conditions are given in term of relaxed Linear Matrix Inequalities $(LLIs)$ where the descriptor formulation is considered. To prove the efficiency of our proposed method, a reduced bioreactor model and simulation results are illustrated.

In this work, we investigate the detection and estimation problems of Sensor and Actuator Faults (SAF) for uncertain nonlinear systems represented by Takagi-Sugeno (TS) fuzzy models subject to an Unknown Bounded Disturbance (UBD). For this, we design a Proportional Integral (PI) observer to estimate state and both sensor and actuator fault vectors, simultaneously. To maximize the fault detection and to minimize the disturbance effects, we consider the H_/H ∞ multiobjective performances. By solving a set of Linear Matrix Inequalities (LMIs) and using Lyapunov theory, we prove the existence of this observer and we guarantee the convergence of both the state estimation errors and fault estimation errors. The descriptor formulation is used to get relaxed LMIs. Finally, a numerical example and simulation results are illustrated to prove the mentioned process efficiency.

This paper investigates the sensor and actuator fault (SAF) estimations and the fault tolerant tracking control (FTTC) problem for uncertain systems represented by Takagi–Sugeno (T–S) fuzzy model affected by Unknown Bounded Disturbance (UBD). A robust descriptor adaptive observer based FTTC is firstly designed to simultaneously estimate the unmeasurable system states and SAF vectors and then to track reference trajectories. Sufficient design conditions are developed in terms of Linear Matrix Inequalities ( L M I s ) . The gains of both observer and fault tolerant controller are computed by solving a set of LMI constraints in single step. Robustness against external disturbances is analysed using the H ∞ performance index to attenuate its effect on the tracking error for bounded reference inputs. Finally, simulation results are illustrated by considering three types of actuator faults. Moreover, two comparisons are presented to show the mentioned process effectiveness.

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 (LMIs) using Lyapunov theory to prove the existence of this observer. A robustness to disturbance is elaborated by considering the Hx) performance index. Finally, a numerical example and simulation results are illustrated to prove the mentioned process efficiency.

In this paper, the detection and estimation problem of sensor and actuator faults (SAF) for nonlinear systems represented by Takagi-Sugeno (T-S) fuzzy models subject to an Unknown Bounded Disturbance (UBD) is investigated. Moreover, we focus on state estimation. For this, we propose a new observer design to simultaneously estimate state and SAF vectors. This observer not only lead to estimate the actuator fault, but also to improve the performance of fault estimation. To maximize the fault effects on the residual and minimize the disturbance effects, we consider the H_/H ∞ performances. For the stability, conditions are given in term of Linear Matrix Inequalities (LMIs). Finally, simulation results are afforded to prove the mentioned process efficiency.