Robust adaptive neural control for a class of time-varying delay systems with backlash-like hysteresis input

This paper proposes a robust adaptive dynamic surface control (DSC) scheme for a class of time-varying delay systems with backlash-like hysteresis input. The main features of the proposed DSC method are that 1) by using a transformation function, the prescribed transient performance of the tracking error can be guaranteed; 2) by estimating the norm of the unknown weighted vector of the neural network, the computational burden can be greatly reduced; 3) by using the DSC method, the explosion of complexity problem is eliminated. It is proved that the proposed scheme guarantees all the closed-loop signals being uniformly ultimately bounded. The simulation results show the validity of the proposed control scheme.