Lateral Control of Vehicle Platoons Under External Disturbance and Parameter Uncertainty: An Adaptive DMPC Approach

This paper proposes an estimator-based distributed model predictive control (DMPC) approach for vehicle platoons in the presence of external disturbance and uncertain cornering stiffness. A lateral dynamics model of vehicle platoons is established by utilizing a path-based vehicle-following strategy. An adaptive parameter estimator is then proposed to estimate the cornering stiffness. Based on it, a distributed disturbance-feedback min-max model predictive controller is developed to ensure the lateral disturbance string stability of vehicle platoons, enhance path-following performance and lateral stability of following vehicles, and simultaneously prevent the actuator saturation. Considering the high computational burden involved in solving min-max optimization, the linear matrix inequalities-based conditions are derived to facilitate the controller gain solving. The proposed method can effectively tackle the cornering stiffness within large uncertain intervals and guarantee the lateral string stability of platoons under external disturbances. Simulation results validate the effectiveness of the proposed DMPC approach in different scenarios.