Distributed Cooperative Synchronization and Tracking for Heterogeneous Platoons With Mixed-Order Nonlinear Vehicle Dynamics

This paper studies the synchronization and tracking issue for the connected and automated vehicle (CAV) platoon with mixed-order nonlinear vehicle dynamics. Previous researches have demonstrated that vehicle platoons can improve traffic efficiency and minimize the incidence of traffic collisions. However, vehicles within the same platoon may have different-order dynamics in practical scenarios. The heterogeneity issue of a vehicle platoon caused by the different-order dynamics is difficult to address by existing platoon control methods. Therefore, the platoon synchronization and tracking control problem for the heterogeneous CAV platoon which consists of mixed-order vehicles with a hybrid of second- and third-order dynamics is formulated in this paper. The proposed novel distributed sliding mode (DSM) control protocols for vehicles with second- and third-order dynamics aim to guarantee the convergence of vehicle state errors and the stability of the heterogeneous platoon. The distributed neural network-based adaptive estimation technique are developed in this paper to approximate the unknown uncertainties and compensate for the model nonlinearities of the platoon system. The uniform ultimate boundedness of errors and string stability are substantiated through the Lyapunov theory and infinity-norm technique. The efficacy of the developed platoon control strategies can be verified by the numerical examples.