Finite-Time Prescribed Performance Tracking Control for High-Order Nonlinear Time-Delay Systems

This paper presents a study on the tracking control problem of a class of nonlinear high order time-delay systems. The method used to approximate the unknown nonlinear functions is the Radial basis function neural networks (RBFNNs). Then, we propose a feasible adaptive neural tracking control scheme backstepping and prescribed performance technology. The Lyapunov stability theory is applied to ensure that all signals in the closed-loop system are semiglobally uniformly ultimately bounded (SGUUB), and that the tracking error is always kept within the prescribed performance range. The proposed control policy is verified to he effective through simulation results.