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This paper deals with the problem of flight tracking control against actuator faults using the linear matrix inequality (LMI) method and adaptive method. An adaptive fault-tolerant flight controller design method is developed based on the online estimation of an eventual fault and the addition of a new control law to the normal control law in order to reduce the fault effect on the system without the need for a fault detection and isolation (FDI) mechanism. In the framework of LMI approach, the normal tracking performance of the resultant closed-loop system is optimized without any conservativeness and the states of fault modes asymptotically track those of the normal mode. A numerical example of an F-16 aircraft model and its simulation results are given.

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This paper is concerned with the problem of robust fault estimation and fault-tolerant control for a class of Takagi-Sugeno (T-S) fuzzy systems with time-varying state delay and actuator faults. Based on the (k − 1)th fault estimation information, a novel k-step fault-estimation observer is proposed to construct the kth fault error dynamics. The obtained fault estimates via k-step fault-estimation can practically better depict the size and shape of the faults. Then, based on the information of online k-step fault-estimation, a dynamic output feedback fault tolerant controller is designed to compensate the fault effects on the closed-loop fuzzy system. Furthermore, some less conservative delay dependent sufficient conditions for the existence of fault estimation observers and fault tolerant controllers are given in terms of solution to a set of linear matrix inequalities. Finally, simulation results of two numerical examples are presented to show the effectiveness and merits of the proposed methods. Index Terms-Dynamic output feedback control, fault tolerant control (FTC), k-step-fault-estimation, linear matrix inequalities (LMIs), Takagi-Sugeno (T-S) fuzzy systems, time-varying delay.