铁路通信信号工程技术2025，Vol.22Issue(7)：1-9,9.DOI:10.3969/j.issn.1673-4440.2025.07.001
基于运行曲线区间优化的磁浮列车分层协同控制方法
Hierarchical Cooperative Control Method for Maglev Trains Based on Operational Curve Interval Optimization
摘要
Abstract
To address the challenges of conflict between individual train optimization objectives and group-wide goals in close-headway maglev train operations,and the insufficient robustness of single velocity profiles under dynamic disturbances,this study proposes a hierarchical cooperative control method based on operational trajectory interval optimization.First,a reference velocity interval generation model integrating safety constraints and multi-objective optimization is established,enabling collaborative planning of velocity boundaries for train formations.Subsequently,a hierarchical cooperative control architecture is designed,where the upper layer employs mixed-integer programming to solve multi-objective optimization problems;the lower layer implements an Optimized Distributed Model Predictive Control(ODMPC)scheme,incorporating interval relaxation factors and a dynamic weighting mechanism to achieve high-precision tracking of reference trajectories.Simulation experiments based on actual medium-low-speed maglev line data demonstrate that the proposed method significantly outperforms conventional Particle Swarm Optimization(PSO)and standard DMPC approaches across core performance metrics,with tracking accuracy improvement of 37%,ride comfort enhancement of 38%,energy consumption reduction of 5.2%-8.7%.These findings provide theoretical foundations and engineering references for cooperative control of maglev train formations in complex electromagnetic environments.关键词
磁浮列车/追踪运行/速度区间优化/分层协同控制Key words
maglev train/tracking operation/speed interval optimization/hierarchical cooperative control分类
交通工程引用本文复制引用
刘鸿恩,胡志豪,崔俊锋,贾云光,杨明春,熊光华,王琦..基于运行曲线区间优化的磁浮列车分层协同控制方法[J].铁路通信信号工程技术,2025,22(7):1-9,9.基金项目
国家自然科学基金项目(62463011) （62463011）
国家重点研发计划项目子课题(2023YFB4302104-2) （2023YFB4302104-2）
江西省自然科学基金项目(20224BAB202025) （20224BAB202025）
