Prescribe performance dynamic surface control of a flapping-wing aerial vehicle with unknown input dead-zone

To perform the position and attitude control of the flapping wing aerial vehicle (FWAV), this article proposes a prescribed performance function based dynamic surface controller (PPDSC) with adaptive neural network (ANN) estimator in presence of unknown input dead-zone. A special radical Lyapunov function consists of a L function is chosen to guarantee the prescribed performance (PP) of the position and attitude trajectory tracking errors for the FWAV. The dynamic surface control (DSC) is a method that utilizing a first-order low pass filter to avoid the phenomenon named explosion of complex of the backstepping method. Meanwhile, the ANN estimator is designed to pay the effect of unknown input dead-zone and disturbance. Then, the stability of the closed-loop FWAV system is proved by utilizing Lyapunov’s direct method. Finally, numerical simulations are given to demonstrate the effectiveness of the above method.