Faycal Ben Hmida

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This paper describes a method of actuator fault estimation for linear uncertain systems. In this work, the upper bound of the unknown input is not required. To remove this requirement a modified sliding mode observer is presented. The novelty in this method lies in the structure of the mechanism introduced to calculate the sliding mode observer gain(More)
This paper describes a robust fault reconstruction and estimation design for a class of nonlinear system described by Takagi-Sugeno structure subject to faults affecting actuators, sensor faults and disturbances. The premise variables are assumed to be unmeasurable. The main innovation is focused primarily to conceive Sliding Mode Observer (SMO) designed to(More)
This paper investigated the problem of state and fault estimation for nonlinear discrete time systems in presence of unknown disturbances. A novel unbiased minimum variance filter (UMVF) is derived by reconstructing the non linear version of NUMV filter. In this work we assume that no prior knowledge about the dynamic of the disturbance and the fault are(More)
Censoring is a phenomenon usually encountered in the analysis of lifetime system. It became commonly used in the last few decades because of its flexibility in removing failed units from tests. In this paper, the Inverse Flexible Weibull Distribution (IFWD) proposed in [1] is studied using maximum likelihood technics based on three different algorithms:(More)
Industrial environments are becoming more and more dynamic, complex, and uncertain. In such conditions, building safe systems is a major requirement and a big challenge which cannot be achieved without suitable diagnosis tools and methods. The early diagnosis approaches were mostly centralized and done offline. It was then proved that distribution is of a(More)
This paper presents a new recursive optimal filter structure for joint input and state estimation of linear time-varying discrete systems in the presence of unknown inputs. The method is concerned with the direct feedthrough matrix which has an arbitrary rank. The resulting filter is optimal in the sense of the unbiased minimum-variance (UMV) criteria. The(More)
In this paper we interest in the problem of multiplicative faults detection and isolation for linear systems. To solve this problem we use a bank of adaptive observers. The proposed algorithm is applied on a numerical example to conclude that the correct and robust detection and isolation in respect to the actuators multiplicative faults.
This paper is concerned with the simultaneous actuator and sensor faults reconstruction problem using sliding mode observer for polytopic Linear Parameter Varying (LPV) systems. Sufficient conditions in terms of Linear Matrix Inequality (LMI) are derived to guarantee the stability of such observer. A simple filter is introduced to transform the sensor fault(More)
This paper proposes a design approach of robust sliding mode observer (SMO) of linear uncertain systems. The uncertainty under consideration being norm bounded. The two steps of the design methodology are investigated. The stability step, in which the robust state estimation error is shown to be uniformly ultimately bounded known as practical stability. In(More)
This paper proposes a method for robust and simultaneous actuator and sensor faults reconstruction of linear uncertain system based on sliding mode observer (SMO). In comparison with existing work, the observer contains two discontinuous terms to solve the problem of simultaneous faults. The idea is to introduce an appropriate filter on the systems output(More)