Intelligent vehicle trajectory tracking with an adaptive robust nonsingular fast terminal sliding mode control in complex scenarios - Min Gao; Jing Li; Taihong Hu; Jin Luo; Baidong Feng (Scientific Reports)
Abstract This study presents a strategy for an intelligent vehicle trajectory tracking system that employs an adaptive robust non-singular fast terminal sliding mode control (ARNFTSMC) approach to address the challenges of uncertain nonlinear dynamics. Initially, a path tracking error system based on mapping error is established, along with a speed tracking error system. Subsequently, a novel ARNFTSMC strategy is introduced to tackle the uncertainties and external perturbations encountered during actual vehicle operation. The adaptive laws established for the longitudinal demand force and the front-wheel steering angle do not require prior understanding of the upper limit of the lumped uncertainty, while successfully avoiding singularities and eliminating chattering. By applying Lyapunov’s stability theorem, it is shown that the control system for trajectory tracking can reach the equilibrium point within a finite time. Following this, a torque optimization distribution control strategy is developed. Ultimately, numerical simulations are used to validate both the effectiveness of the proposed approach and its robustness across different conditions.