Robust Adaptive Neural Control of Morphing Aircraft with Prescribed Performance

This study proposes a low-computational composite adaptive neural control scheme for the longitudinal dynamics of a swept-back wing aircraft subject to parameter uncertainties. To efficiently release the constraint often existing in conventional neural designs, whose closed-loop stability analysis always necessitates that neural networks (NNs) be confined in the active regions, a smooth switching function is presented to conquer this issue. By integrating minimal learning parameter (MLP) technique, prescribed performance control, and a kind of smooth switching strategy into back-stepping design, a new composite switching adaptive neural prescribed performance control scheme is proposed and a new type of adaptive laws is constructed for the altitude subsystem. Compared with previous neural control scheme for flight vehicle, the remarkable feature is that the proposed controller not only achieves the prescribed performance including transient and steady property but also addresses the constraint on NN. Two comparative simulations are presented to verify the effectiveness of the proposed controller

Adaptive fuzzy observer-based active fault-tolerant dynamic surface control for a class of nonlinear systems with actuator faults

International audienc

Adaptive fuzzy observer-based active fault-tolerant dynamic surface control for a class of nonlinear systems with actuator faults

Accepted January 2013International audienceThe problem of fault-tolerant dynamic surface control (DSC) for a class of uncertain nonlinear systems with actuator faults is discussed, and an active fault-tolerant control (FTC) scheme is proposed. Using the DSC technique, a novel fault diagnostic algorithm is proposed, which removes the classical assumption that the time derivative of the output error should be known. Further, an accommodation scheme is proposed to compensate for both actuator time-varying gain and bias faults, and avoids the controller singularity. In addition, the proposed controller guarantees that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and converge to a small neighborhood of the origin. Finally, the effectiveness of the proposed FTC approach is demonstrated on a simulated aircraft longitudinal dynamics example

Adaptive fuzzy observer-based active fault-tolerant dynamic surface control for a class of nonlinear systems with actuator faults

Accepted January 2013International audienceThe problem of fault-tolerant dynamic surface control (DSC) for a class of uncertain nonlinear systems with actuator faults is discussed, and an active fault-tolerant control (FTC) scheme is proposed. Using the DSC technique, a novel fault diagnostic algorithm is proposed, which removes the classical assumption that the time derivative of the output error should be known. Further, an accommodation scheme is proposed to compensate for both actuator time-varying gain and bias faults, and avoids the controller singularity. In addition, the proposed controller guarantees that all signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB), and converge to a small neighborhood of the origin. Finally, the effectiveness of the proposed FTC approach is demonstrated on a simulated aircraft longitudinal dynamics example