Tracking control of a convoy of autonomous robotic cars with a prescribed performance

Abstract

This paper studies the tracking control of a convoy of multiple autonomous cars or car-like robots in the planar motion without any collision with a prescribed performance that has not been addressed sufficiently in the literature yet. Toward this end, a coordinate transformation is initially employed to transform the posture errors between each two successive cars in a group from the earth-fixed frame into their relative distance and angle errors that should satisfy some predefined transient and steady-state constraints. By employing the prescribed performance technique, a nonlinear transformation is used to transform the constrained relative distance and angle errors and to obtain an unconstrained kinematic error equation. Then, a novel kinematic controller is designed to satisfy the prescribed transient and steady-state performance specifications without any collision and any controller singularity. Next, the Dynamic Surface Control technique is effectively used to simplify the convoy controller design at the dynamic level by using a first-order filter. An adaptive neural network is used to maintain the control system robustness against modelling errors and external disturbances. The Lyapunov theory proves the stability of the convoy control system and, finally, simulation examples verify the controller performance for multiple autonomous cars in intelligent transportation applications.