SummaryThis paper studies the problem of robust fault estimation for a class of Takagi‐Sugeno(T‐S) fuzzy systems which subject to interval time‐varying delay, external disturbance, and actuator fault. The designed learning observer can achieve simultaneous estimation of system state and time‐varying or constant actuator fault. Then, we construct a new Lyapunov‐Krasovskii functional including the information of the lower and upper delay bounds; compared with the time‐varying delay, the interval time‐varying delay is the less conservative form. Furthermore, one less conservative delay‐dependent condition for the existence of learning observer is given in terms of linear matrix inequalities. In addition, the results for the systems with interval time‐varying delay are simplified when the delay is not concluded. Finally, simulation results of two examples are presented to show the effectiveness of the proposed method.

Summary This paper deals with the problem of H∞ robust fault estimation for a class of Takagi‐Sugeno (T‐S) fuzzy systems with state time‐varying delay, sensor, and actuator faults. The faults considered in this paper are time‐varying signals whose k‐order derivatives with respect to time are bounded. Then, we propose a proportional multiple integral observer to achieve simultaneous estimation of system states and time‐varying actuator and sensor faults. Furthermore, one less conservative delay‐dependent sufficient condition for the existence of fault estimation observer is given in terms of linear matrix inequality. The disturbance attenuation is constrained to a given level using H∞ performance index. Finally, simulation results of one numerical example is presented to show the effectiveness of the proposed method.