A novel sensor fault diagnosis approach for time-varying delay systems with non-linear uncertainty

In this paper, a sensor fault diagnosis approach is presented for a class of time delay non-linear systems via the use of adaptive updating rules. The considered system is represented by a time-varying delay dynamical state space model, and is subjected to a non-linear vector, which represents the modelling uncertainty in the state equation. Firstly, a fault detector observer is constructed to detect the fault. Then, the method for choosing the threshold value is given. Furthermore, a fault diagnosis device is constructed to diagnose the fault. The Lyapunov stability theory is used to obtain the required adaptive tuning rules for the estimation of the sensor fault. An adaptive diagnosis algorithm is developed to obtain information on the sensor fault. Finally, a simulated numerical example and a robotic example are included to demonstrate the use of the proposed approach, and experimental results show that the proposed adaptive diagnosis algorithm can track the fault signal and that the proposed method is valid.