Robust fault estimation for T-S fuzzy systems with intermittently sampled data based on finite information learning observer

In this article, we study the problem of robust fault estimation for a class of T-S fuzzy systems with time delays and external disturbances based on the finite information learning observer. The learning observer with intermittent sampling is constructed and the change rate of output estimation error is introduced to estimate the system fault effectively. At the same time, by introducing a generalized inverse matrix to the designed observer, a sufficient condition for the stability of the error estimation system is given by using fuzzy Lyapunov function, which not only solves the problem of system fault and external disturbance estimation, but also reduces the conservatism of the obtained conclusion. Finally, the results described by LMI are solved numerically and simulated to demonstrate the effectiveness of the proposed method.