Time-varying state constraints-based neural network control of a 2-DOF helicopter system

Abstract

This paper proposes a neural network (NN) control method for a nonlinear 2-DOF helicopter system with time-varying state constraints. By constructing the time-varying barrier Lyapunov technology and the controller designed based on the backstepping method, the system’s states are guaranteed within a predetermined region. The NN is adopted to approximate the unknown function of the system to ensure its tracking performance and stability. Finally, the effectiveness of the derived control is validated by numerical simulation.