Nonlinear Dynamics based Trajectory Tracking Robust Control of Unmanned Ground Vehicle

Abstract

This paper investigates the issue of unmanned ground vehicles (UGVs) trajectory tracking. A model predictive control and nonlinear dynamics-based robust control (MPC-NDRC) framework is suggested for UGV to improve trajectory tracking performance. The MPC-NDRC framework is divided into two phases. Building a predictive model controller is the first step in preventing the issue of poor real-time performance brought on by online computing complex models. The creation of a robust nonlinear dynamics-based controller is the second step in ensuring the performance of trajectory tracking and controller model accuracy. Additionally, by designing the system's poles with a stability margin, the system's robust stability is ensured. The Lyapunov theorem establishes the sufficient condition for closed-loop system stability. The MATLAB-Carsim platform's simulation results show the proposed MPC-NDRC framework considerably improves trajectory tracking performance.