Adaptive Sliding Mode Control for Autonomous Vehicle Platoon under Unknown Friction Forces

Abstract

Multi-robot formation control has various applications in domains such as vehicle troops, platoons, payload transportation, and surveillance. Maintaining formation in a vehicle platoon requires designing a suitable control scheme that can tackle external disturbances and uncertain system parameters while maintaining a predefined safe distance between the robots. A crucial challenge in this context is dealing with the unknown/uncertain friction forces between wheels and the ground, which vary with changes in road surface, wear in tires, and speed of the vehicle. Although state-of-the-art adaptive controllers can handle a priori bounded uncertainties, they struggle with accurately modeling and identifying frictional forces, which are often state-dependent and cannot be a priori bounded. This thesis proposes a new adaptive sliding mode controller for wheeled mobile robot-based vehicle platoons that can handle the unknown and complex behavior of frictional forces without prior knowledge of their parameters and structures. The controller uses the adaptive sliding mode control techniques to regulate the platoon’s speed and maintain a predefined inter-robot distance, even in the presence of external disturbances and uncertain system parameters. This approach involves a two-stage process: first, the kinematic controller calculates the desired velocities based on the desired trajectory; and second, the dynamics model generates the commands to achieve the desired motion. By separating the kinematics and dynamics of the robot, this approach can simplify the control problem and allow for more efficient and robust control of the wheeled mobile robot. The stability of the closed-loop system employing both the proposed controllers are studied analytically via Lyapunov theory. The effectiveness of the proposed controller is demonstrated through simulations using Gazebo, a popular robot simulation tool. The simulations show that the proposed controller outperforms existing state-of-the-art controllers in terms of stability, convergence, and robustness to changes in frictional forces. The simulations also demonstrate the controller’s ability to maintain formation under various road conditions, including slopes, curves, and rough terrain.