This paper studies a control architecture for vehicle lateral dynamics based on the execution of optimal trajectories via feedforward inverse model control. The focus here is on assessing the robustness of this arrangement when the vehicle real forward dynamics is not identically cancelled by the inverse model due to model approximations and parameter uncertainties. The trajectories that are considered are analytic solutions of the minimum square jerk optimal control problem for a simplified kinematic vehicle model in curvilinear coordinates. Various hypotheses are made concerning the mismatch between the inverse model and the actual forward dynamics of the vehicle. Closed-loop stability analysis shows that the studied control scheme guarantees asymptotic stability of both the nominal and the perturbed kinematic model with significant robustness margins. In addition to the theoretical robustness analysis, the same control scheme is validated in simulation using the industry-standard software for virtual vehicle testing IPG CarMaker.