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This paper considers the reliable control problem for multiple trailing fixed-wing unmanned aerial vehicles (UAVs) against actuator faults and wake vortices. A distributed adaptive fault-tolerant control (FTC) scheme is proposed by using a distributed sliding-mode estimator, dynamic surface control architecture, neural networks, and disturbance observers. The proposed control scheme can make all trailing fixed-wing UAVs converge to the leading UAV with pre-defined time-varying relative positions even when all trailing UAVs encounter the wake vortices generated by the leading UAV and a portion of trailing UAVs is subjected to the actuator faults. It is shown that under the proposed distributed FTC scheme, the tracking errors of all trailing UAVs with respect to their desired positions are bounded. Comparative simulation results are provided to illustrate the effectiveness of the proposed control scheme. • The fault-tolerant close formation flight control of multiple UAVs is considered. • The nonlinear 6-DOF fixed-wing UAV model is used in the control design. • A composite learning algorithm is proposed to enhance the estimation capability. [ABSTRACT FROM AUTHOR]

This paper presents a dual adaptive fault-tolerant control strategy for a quadrotor helicopter based on adaptive sliding mode control and adaptive boundary layer. Within the proposed adaptive control strategy, both model uncertainties and actuator faults can be compensated without the knowledge of the uncertainty bounds and fault information. By virtue of the proposed adaptive control scheme, the minimum discontinuous control gain is adopted, which significantly reduces the control chattering effect. As compared to the existing adaptive sliding mode control schemes in the literature, larger actuator faults can be tolerated by employing the proposed control scheme while suppressing control chattering. Moreover, boundary layer is used to smoothen control discontinuity and further eliminate control chattering. Nevertheless, the choice of boundary layer thickness is a trade-off between system stability and tracking accuracy. By explicitly considering this fact, an adaptive boundary layer is developed and synthesized with the proposed adaptive control framework to ensure stability and tracking accuracy of the considered system. When the control parameter tends to be overestimated, the thickness of boundary layer can be appropriately adjusted to avoid control parameter overestimation. Simulation and experimental tests of a quadrotor helicopter are both conducted to validate the effectiveness of the proposed control scheme. Its advantages are demonstrated in comparison with a conventional adaptive sliding mode control scheme. [ABSTRACT FROM AUTHOR]