Dual-mode Distributed Model Predictive Control for Platooning of Connected Vehicles with Nonlinear Dynamics

This paper presents a dual-mode distributed model predictive control (DMPC) strategy for platooning of connected vehicles with nonlinear dynamics. A third-order nonlinear model is employed to describe the dynamic characteristics of vehicles. In order to deal with the system nonlinearity and enhance the control precision, a DMPC based optimization problem is formulated for the vehicle platoon control, in which the nonlinear dynamics and the input boundaries are both considered as its constraints. Then, a dual-mode structure with the control scheme from the optimization and a local state feedback controller is proposed to drive the vehicles to the desired platoon. Comparing with other vehicle platoon algorithms, the proposed dual-mode DMPC strategy can significantly reduce the computational burden and save the communication resources. Furthermore, the iterative feasibility and the stability of proposed control system are strictly analyzed. In final, numerical simulations are provided to validate the effectiveness of proposed approaches.