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_∞ 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.