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Challenging design problems arise regularly in modern fault diagnosis systems. Unfortunately, classical analytical techniques often cannot provide acceptable solutions to such difficult tasks. This explains why soft computing techniques such as neural networks become more and more popular in industrial applications of fault diagnosis. Taking into account the two crucial aspects, i.e., the nonlinear behaviour of the system being diagnosed as well as the robustness of a fault diagnosis scheme with respect to modelling uncertainty, two different neural network based schemes are described and carefully discussed. The final part of the paper presents an illustrative example regarding the modelling and fault diagnosis of a DC motor, which shows the performance of the proposed strategy.

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This paper proposes an approach for the joint state and fault estimation for a class of uncertain nonlinear systems with simultaneous unknown input and actuator faults. This is achieved by designing an unknown input observer combined with a set-membership estimation in the presence of disturbances and measurement noise. The observer is designed using quadratic boundedness approach that is used to overbound the estimation error. Sufficient conditions for the existence and stability of the proposed state and actuator fault estimator are expressed in the form of linear matrix inequalities (LMIs). Simulation results for a quadruple-tank system show the effectiveness of the proposed approach.

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Abstract. In this paper, a virtual actuator-based active fault-tolerant control strategy is presented. After a short introduction to Takagi-Sugeno fuzzy systems, it is shown how to design a fault-tolerant control strategy for this particular class of non-linear systems. The key contribution of the proposed approach is an integrated fault-tolerant control design procedure of fault identification and control within an integrated fault-tolerant control scheme. In particular, fault identification is implemented with the suitable state observer. While, the controller is implemented in such a way that the state of the (possibly faulty) system tracks the state of a fault-free reference model. Consequently, the fault-tolerant control stabilizes the possibly faulty system taking into account the input constraints and some control objective function. Finally, the last part of the paper shows a comprehensive case study regarding the application of the proposed strategy to fault-tolerant control of a twin-rotor system.