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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]

Among renewable energy sources, wind power is expected to contribute a larger and rapidly growing portion of the world's energy portfolio. However, the increased penetration of wind power into the power grid has challenged the reliable and stable operation of the grid. This motivates new opportunities in the design and development of novel control schemes capable of actively maintaining the necessary balance between power generation and load, which in turn regulates the grid frequency when plenty of winds are available. This paper presents two active power control schemes that are developed based on adaptive pole placement control and fuzzy gain-scheduled proportional-integral control approaches. The active power control is conducted collectively across a wind farm to provide rapid power response while maintaining safe structural loading on turbines’ components. The proposed active power control schemes are evaluated and compared by a series of simulations on an advanced wind farm benchmark model in the presence of wind turbulences, measurement noises, and grid load variations. It is further demonstrated that the mentioned schemes are able to tolerate probable occurrence of sudden imbalance between generation and load due to relevant faults/failures in the wind farm or electric grid. [ABSTRACT FROM AUTHOR]

Study results of developing formation control system for multi-spacecraft that requires avoiding obstacles and maintaining the formation configuration are presented. In particular, nonlinear adaptive feedback control law is developed by employing special potential functions and a kind of time-varying sliding manifold, to enable the spacecraft formation in a specific configuration by taking into account the obstacle avoidance requirement while tracking a moving target in a way of cooperation or not. Moreover, capability for handling multiple tasks by the proposed control system is demonstrated in the presence of disturbances and parametric uncertainties. The stability proof is based on a Lyapunov-like analysis and the properties of the proposed potential functions. Numerical simulation of the proposed method is presented to demonstrate the advantages with respect to obstacle avoidance, fast tracking and formation flying configuration reconstruction capability. [ABSTRACT FROM AUTHOR]

This paper addresses the control problem of air-breathing hypersonic vehicles subject to input nonlinearities, aerodynamic uncertainties and flexible modes. An adaptive backstepping controller and a dynamic inverse controller are developed for the altitude subsystem and the velocity subsystem, respectively, where the former eliminates the problem of “explosion of terms” inherent in backstepping control. Moreover, a modified smooth inverse of the dead-zone is proposed to compensate for the dead-zone effects and reduce the computational burden. Based on this smooth inverse, an input nonlinear pre-compensator is designed to handle input saturation and dead-zone nonlinearities, which leads to a simpler control design for the altitude subsystem subject to these two input nonlinearities. It is proved that the proposed controllers can guarantee that all closed-loop signals are bounded and the tracking errors converge to an arbitrarily small residual set. Simulation results are carried out to demonstrate the effectiveness of the proposed control scheme. [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]