Adaptive Sliding Mode Control for Vehicle Platoons with State-Dependent Friction Uncertainty

TL;DR

This paper introduces an adaptive sliding mode control method for vehicle platoons that effectively manages state-dependent friction uncertainties without prior parameter knowledge, ensuring formation stability and robustness.

Contribution

It proposes a novel adaptive sliding mode controller specifically designed for vehicle platoons to handle complex, state-dependent friction uncertainties without needing prior system parameter information.

Findings

Successfully maintains platoon formation despite unknown friction forces.

Enhances robustness against external disturbances and system uncertainties.

Separates kinematic and dynamic control for improved efficiency.

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.