This paper deals with the design of a multiple observer allowing estimating the state vector of a nonlinear system described by a Takagi-Sugeno multiple model subject to modelling and input uncertainties which are considered as unknown inputs. The main contribution of the paper is the conception of a multiple observer based on the elimination of these unknown inputs. Convergence conditions are established in order to guarantee the convergence of the state estimation error. These conditions are expressed in Linear Matrix Inequality (LMI) formulation. An example of simulation is given to illustrate the proposed method.

This paper deals with the problem of active fault tolerant control strategy for nonlinear systems described by Takagi-Sugeno models. The proposed control law uses the estimated fault. The considered systems are affected by sensor faults. A mathematical transformation is used in order to conceive an augmented system in which the sensor faults affecting the initial system appear as unknown inputs. A proportional integral observer with unknown inputs is conceived in order to estimate simultaneously states and sensor faults. The stability of the system with the proposed fault tolerant control strategy is formulated using Lyapunov theory and the observer gains are obtained by solving linear matrices inequalities. To illustrate the proposed method, it is applied to the three columns.Keywords: Takagi-Sugeno model; proportional integral observer with unknown inputs; sensor faults; active fault tolerant control strategy.Reference to this paper should be made as follows: Jamel, W., Khedher, A. and Ben Othman, K. (2017) 'Observer design and active fault tolerant control for Takagi-Sugeno systems affected by sensors faults', Int.

In this paper we focus on the state estimation of a nonlinear system described by a Takagi-Sugeno multiple model submitted to unknown inputs and outputs. The proposed approach consists on a mathematical transformation which enables to consider the unknown outputs as unknown inputs that can be eliminated by a designed multiple observer. To evaluate the efficiency of the proposed approach, the convergence conditions of the state estimation error are formulated as linear matrix inequalities (LMI). Simulation Examples are given to illustrate the proposed methods.

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