Path-tracking control for autonomous vehicles using double-hidden-layer output feedback neural network fast nonsingular terminal sliding mode

In this paper, a double-hidden-layer output feedback neural network fast nonsingular terminal sliding mode control strategy is developed for path-tracking tasks of autonomous vehicles. First, a vehicle kinematic-and-dynamic model is established to describe the vehicle’s fundamental lateral dynamics in path-tracking behavior. Afterwards, detailed design procedure of the proposed controller is shown, where the control system’s stability is verified in the Lyapunov sense. Finally, MATLAB-Carsim co-simulations are executed for the aim of testing the control performance. Simulation results illustrate that the designed control algorithm possesses remarkable superiority reflected in higher tracking precision, faster convergence rate and firmer robustness in comparison with a conventional sliding mode controller and a nonsingular terminal sliding mode controller.