Robust control for line-following robots with model uncertainties and dynamic disturbances

Abstract

This paper proposes a robust nonlinear control law for line-following robots under dynamic disturbances caused by model uncertainties. The control objective is to ensure that the robot accurately tracks the desired trajectory, even in the presence of line paths with varying curvature. The control strategy is designed based on a cascade structure, consisting of two loops: the kinematic loop and the dynamic loop. The outer loop, corresponding to the kinematic controller, is developed using a Lyapunov function. The dynamic control law in the inner loop is derived from differential geometric methods and guarantees finite-time stability. System uncertainties and disturbances are compensated by introducing a predefined term in the control law. The closed-loop stability is rigorously proven using Lyapunov theory. Simulation results, along with comparisons to the LQR controller, demonstrate the effectiveness and robustness of the proposed approach, highlighting its fast convergence, small tracking error, and strong disturbance rejection capability.