Neural Network Adaptive Control of Flexible Robotic with Unknown Time-delay

In this paper, an adaptive dynamic surface control(DSC) method is proposed for the state time-delay flexible robotic system with unmodeled dynamics and time-varying output constraints. The dynamic disturbances are effectively dealt with by introducing a dynamic signal. The unknown continuous functions are approximated by using radial basis function neural networks (RBFNNs). An asymmetric time-varying barrier Lyapunov function (BLF) is employed to ensure constraint satisfaction. The Lyapunov-Krasovskii function is used to deal with the unknown time-delay. By theoretical analysis, the closed-loop control system is shown to be semi-globally uniformly ultimately bounded. Simulation results are provided to illustrate the effectiveness of the proposed approach.