Distributed cooperative cruise control for high‐speed trains with multi‐objective optimization

This paper proposes a novel cooperative cruise control strategy to jointly optimize the energy consumption and ride comfort for multiple high-speed trains. The cooperative control strategy is constructed by combining the consensus algorithm and potential function to achieve the synchronization of train speed and keep a safe tracking interval. A multi-objective optimal function of multiple high-speed trains is constituted of cruise following error, energy consumption and ride comfort. The non-dominated quick sorting algorithm (NSGA-II) is used to find the global Pareto-optimal solutions to obtain the optimal cooperative control gains, which achieve the optimal trade-offs between energy consumption and riding comfort for high-speed trains. The asymptotic stability of the proposed control strategy is proved strictly. The simulation results verify that the proposed control strategy can effectively reduce energy consumption and improve the riding comfort simultaneously when compared with existing methods.