Robust Fault Estimation for T-S Fuzzy Systems with Unmeasurable Premise Variables and Random Time Delays

This paper studies the problem of actuator fault estimation (FE) for a class of T-S fuzzy systems with unmeasurable premise variables, which is subject to random time-varying delay and norm-bounded external disturbance. By taking the unmeasurable premise variables and actuator fault as auxiliary disturbance signal, the robust FE observer based on n-steps iterative learning algorithm is constructed to guarantee the error dynamic system to be asymptotically stable with a prescribed H-infinity performance. An improved sufficient condition of such observer is presented in terms of linear matrix inequality, which includes the information of the upper and lower bounds of time delay. Finally, a numerical example is given to illustrate the effectiveness of the proposed method.