A robust MPC approach for platooning control of automated vehicles with constraints on acceleration

This paper deals with the issue of robust model predictive control (MPC)-based automated vehicle platooning control under acceleration constraints. A unified framework is established to characterize the dynamics of cooperative longitudinal motion of the vehicle platoon with parameter uncertainties as well as the saturated control input. More specifically, the parameter uncertainties are described by norm bounded, and the saturated control input is assumed to be sector-bounded. The coordinated platoon behaves like a linear model where the deviations from the reference spacing and velocity are selected as the state variables. The main objective of this paper is to develop a robust MPC-based platooning control such that the controlled vehicular platoon can track the leading vehicle under the acceleration constraint and parameter uncertainties, meanwhile maintaining safety and resource management. By solving the optimization problem, sufficient conditions for MPC-based platooning control system stability in the mean-squared sense and performance analysis are provided and the controller gain is obtained at each instant. Finally, multi-vehicle cases are conducted to demonstrate the feasibility of the developed control algorithm.