Vehicle stability control via VRFT with probabilistic robustness guarantees

In four-wheel steering vehicles, the rear wheels can be used to adjust the driver's front action to enhance vehicle stability and performance. To the best of the authors' knowledge, all the existing control design methods rely on a simple model of the lateral dynamics, which may lead to unsatisfactory results in case of uncertainty. In this paper, we propose to use a modified version of the (model-free) Virtual Reference Feedback Tuning approach, where probabilistic guarantees are given for operating conditions different from the identification experiment. We validate the proposed approach on a thorough simulation campaign using a multibody simulator.