Coordinating the motions of multiple agents in a shared workspace is a standing challenge in multi-robot trajectory planning. Prioritized planning allows to generate coordinated trajectories by planning individual paths around static obstacles first and collision-free velocity profiles in a second step. However, the main drawback of prioritized planning is that the robots are only guaranteed to reach their goals without collisions or deadlocks, if they follow their planned trajectories precisely in both space and time. In real-world environments shared with humans or non-automated traffic, disturbances, delaying individual robots in the exact execution of their plans, are likely. This can affect other planned trajectories and leaves the system prone to deadlocks. Instead of replanning all trajectories or pausing all agents to maintain the coordination integrity, control strategies that allow safe deviations from the originally planned trajectories have been proposed in recent research. Yet, many assumptions, e.g., circular robot shape or unlimited acceleration, prevent these approaches from being applied to heavy machinery such as trucks or busses. Therefore, a revised trajectory tracking controller is presented, that maintains the consistency of the coordinated plans while accounting to the kinematic constraints and the swept area of large, articulated vehicles.