Distributed Cooperative Neural Control for Nonlinear Heterogeneous Platoon Systems with Unknown Uncertainties

This study investigates the issue of vehicle platoon control for nonlinear heterogeneous vehicle platoon systems containing a leader and several followers subject to unknown uncertainties and disturbances. Platoon control has been shown to effectively achieve the consensus of vehicles, increase road capacity, and enhance traffic safety. Achieving that the vehicle platoon maintains a desired inter-vehicle spacing and reaches the velocity consensus is the main objective of platoon control. To achieve vehicle consensus and avoid collisions, the new distributed cooperative sliding mode control protocols are proposed for the heterogeneous platoon to ensure the convergence of vehicle spacing errors and velocity errors and to guarantee string stability. The spacing policy and information flow topology are introduced within the development of the platoon control strategies. Furthermore, the novel distributed neural adaptive control strategies utilizing the nonsingular updating method are developed to address the problem of the unknown uncertainties and heterogeneities in the platoon vehicles. The proof of the ultimate boundedness of the spacing and velocity errors is carried out by utilizing the Lyapunov theory. The analysis of string stability is conducted to confirm the effectiveness of the vehicle platoon control strategies. Finally, the correctness and efficacy of the control strategies can be verified through a numerical example.