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This paper proposes fault-tolerant control design for uncertain nonlinear systems described under Takagi-Sugeno fuzzy systems with local nonlinear models that satisfy the Lipschitz condition. First, by transforming sensor faults as 'pseudo-actuator' faults, an adaptive sliding mode observer is designed in order to simultaneously estimate system states, actuator and sensor faults despite the presence of norm-bounded uncertainties. Second, an adaptive sliding mode controller is suggested to provide a solution to stabilize the closed-loop system, even in the event of simultaneous occurrence of faults in actuators and sensors. Next, the main objective of the fault-tolerant control strategy is to compensate for the effects of fault based on the feedback information. Therefore, using the LMI optimization method, sufficient conditions are developed with H-ž to calculate the gains of the observer and the controller. Then, particular attention is paid to the simultaneous maximization, by convex multi-objective optimization, of the Lipschitz nonlinear constant in Takagi-Sugeno fuzzy modelling and uncertainties attenuation level. The results of the simulation illustrate the effectiveness of our fault-tolerant control approach using a nonlinear inverted pendulum with a cart system. [ABSTRACT FROM AUTHOR]

The purpose of this study is to present a new robust sliding mode control design for nonlinear systems where both matched and unmatched uncertainties are considered. The proposed controller strategy is composed of two components: the integral sliding mode control and the optimal feedback control law. Moreover, an integral sliding mode surface in integral type is developed to construct the reachability of sliding mode using the Lyapunov functions method. The main advantages of the proposed approach are ensuring the robustness throughout the whole system response against the uncertainties, decrease the chattering effect and eliminate the reaching phase. Finally, the validity of the proposed design strategy is demonstrated through the simulation of a flexible joint robot. [ABSTRACT FROM AUTHOR]

This article deals with the sliding mode fault-tolerant control (FTC) problem for a nonlinear system described under Takagi-Sugeno (T-S) fuzzy representation. In particular, the nonlinear system is corrupted with multiplicative actuator faults, process faults, and uncertainties. We start by constructing the separated FTC design to ensure robust stability of the closed-loop nonlinear system. First, we propose to conceive an adaptive observer in order to estimate nonlinear system states, as well as robust multiplicative fault estimation. The novelty of the proposed approach is that the observer gains are obtained by solving the multiobjective linear matrix inequality (LMI) optimization problem. Second, an adaptive sliding mode controller is suggested to offer a solution to stabilize the closed-loop system despite the occurrence of real fault effects. Compared with the separated FTC, this paper provides an integrated sliding mode FTC in order to achieve an optimal robustness interaction between observer and controller models. Thus, in a single-step LMI formulation, sufficient conditions are developed with multiobjective optimization performances to guarantee the stability of the closed-loop system. At last, nonlinear simulation results are given to illustrate the effectiveness of the proposed FTC to treat multiplicative faults. [ABSTRACT FROM AUTHOR]

This paper proposes a new robust fault reconstruction and estimation design for a class of nonlinear system described by the Takagi-Sugeno model with unmeasurable premise variables subject to faults affecting actuators, sensor faults, and unknown disturbances. The augmented Takagi-Sugeno system is introduced with a new fault vector which has two origins: the first one represents actuator faults, the second one denotes faults affecting sensors. The main contribution is focused primarily to conceive a sliding mode observer with two discontinuous terms designed to compensate for fault behavior and disturbance variation from the system states estimation. In the formalism of linear matrix inequalities, we derive sufficient conditions to guarantee the state estimation error stability and to obtain the observer gains. Meanwhile, additional effort is made to achieve simultaneous faults and disturbance reconstruction. Simulation results are given to illustrate the proposed approach performances. [ABSTRACT FROM AUTHOR]

This paper considers the problem of robust reconstruction of simultaneous actuator and sensor faults for a class of uncertain Takagi-Sugeno nonlinear systems with unmeasurable premise variables. The proposed fault reconstruction and estimation design method with H∞ performance is used to reconstruct both actuator and sensor faults when the latter are transformed into pseudo-actuator faults by introducing a simple filter. The main contribution is to develop a sliding mode observer (SMO) with two discontinuous terms to solve the problem of simultaneous faults. Sufficient stability conditions in terms linear matrix inequalities are achieved to guarantee the stability of the state estimation error. The observer gains are obtained by solving a convex multiobjective optimization problem. Simulation examples are given to illustrate the performance of the proposed observer. [ABSTRACT FROM AUTHOR]