Predictive Control of Vehicle Dynamics Equipped with Intelligent Tire Sensors via Gaussian Process Regression of Lateral Tire Force

This paper investigates the estimation of lateral tire forces and predictive control for vehicles equipped with intelligent tires. Motivated by the capability of intelligent tires to estimate lateral tire forces, we propose a control scheme that includes a predictor for lateral tire forces, utilizing the Gaussian Process Regression technique. In addition, a metric for online data management is proposed, which has the characteristic of retaining more data in regions where the change of the function value is relatively large. The proposed metric can be interpreted as an extension of the existing method, allowing for the control of dataset quality within its limited size. We apply the proposed control scheme to the model predictive contouring control problem. Numerical simulations demonstrate the robustness of the proposed control scheme to tire parameter uncertainty, in comparison to a baseline controller.