Robust Approximate Constraint‐Following Control for Autonomous Vehicle Platoon Systems

Abstract

AbstractWe consider an autonomous vehicle platoon system consisting of N+1 vehicles in the presence of modeling uncertainty. The uncertainty may be due to parameter variations, aerodynamics, external disturbances, etc., which is nonlinear and time‐varying. Subject to the collision avoidance consideration, the original state is one‐sided restricted. To resolve this restriction, we propose a state transformation to convert the bounded state into a globally unbounded state. Furthermore, motivated by the properties of artificial swarm systems, we incorporate the swarm system performance into the platoon system by treating it as a d'Alembert's constraint. By the Udwadia and Kalaba's approach, we obtain the analytic (closed‐form) expression of the constraint force. Based on this, a class of robust controls for each vehicle (except the leading vehicle) is proposed to drive the platoon system to follow the ideal swarm model. Four major system performances are accomplished: (i) compact vehicle formation, (ii) collision avoidance, (iii) stable platoon system formation, (iv) global behavior.