Trajectory Tracking and Control of Differential Drive Mobile Robots Using Feedback Linearization

Abstract

This study presents a robust control design framework for trajectory tracking of a differential drive mobile robot, addressing the challenges posed by nonlinear dynamics and non-holonomic constraints. The proposed methodology integrates feedback linearization with a multivariable central control strategy, utilizing an inner-outer loop architecture to ensure precise path-following capabilities. Simulations were conducted using Matlab-Simulink to evaluate the robot’s performance on three distinct trajectories: sinusoidal, infinite, and square trajectories. Results demonstrated the robot’s ability to achieve rapid convergence to reference paths with minimal positional and velocity errors, highlighting the superior prediction and tracking accuracy of sinusoidal and infinite trajectories compared to square trajectories. The analysis further revealed the influence of trajectory geometry on stabilization times and system dynamics, with infinite orbits achieving quicker error correction and angular velocity stabilization. These findings indicate the adaptability and effectiveness of the proposed approach, providing insights for optimizing trajectory selection and control tuning in autonomous robotic systems.