A data-driven control method for vehicle lateral stability in snow and ice-rutted conditions under aperiodic sampling

Designing a controller to ensure vehicle stability under snow and ice-rutted road conditions, in the absence of accurate model knowledge and with potential sampling data delay, poses a significant challenge. To address this, this paper presents a novel data-driven parametric approach that integrates linear matrix inequalities (LMIs) methods. This approach allows for the determination of an appropriate sampling time interval. By iteratively solving LMIs, a state-feedback controller is derived, which guarantees both system stability and robustness. The effectiveness of the proposed approach is demonstrated through numerical simulations conducted on the MATLAB/CarSim platform. The results highlight the good control performance and robustness achieved by the proposed method.