Nonlinear robust control for a small unmanned helicopter based on neural network

This paper presents an asymptotic tracking controller for a small-size unmanned helicopter using neural network(NN) and a continuous nonlinear robust control strategy called robust integral of the signum of the error(RISE). The NN in the control law approaches the uncertain parts of the helicopter's dynamics using online network weight tuning, while the NN approximation errors and the external disturbances are compensated by using the RISE approach. Semi-global asymptotic stability of the error signals and the boundedness of the closed-loop system signals are ensured via Lyapunov based stability analysis. Finally, real-time experiments are performed on a helicopter attitude control test-bed. The experimental results show that the proposed controller achieves a good performance and the closed loop systems obtain good robustness with respect to system uncertainties and external disturbances. © 2018, Editorial Office of Control and Decision. All right reserved.