Adaptive neural tracking control of nonlinear time-delay systems with disturbances

摘要

In this paper, a novel adaptive neural tracking control scheme is presented for a class of perturbed strict-feedback nonlinear time-delay systems with unknown virtual control coefficients. The introduction of new estimated parameters reduces the number of adaptive parameters and the size of neural networks required. Based on radial basis function neural network on-line approximation, an adaptive neural tracking controller is proposed by combining Lyapunov-Krasovskii functionals and decoupled backstepping. The proposed scheme guarantees semi-global uniform ultimate boundedness of all the signals in the closed-loop system and the tracking error converges to a small neighborhood around the origin. Simulation results demonstrate the effectiveness of the proposed results.