列车主动悬挂预测控制算法研究  

Study on the Predictive Control Algorithm for Train's Active Suspension Systems

作　　者：曹青松[1] 王明翔[1] 陶晶[1] 

机构地区：[1]华东交通大学机电工程学院,南昌330013

出　　处：《噪声与振动控制》2016年第1期21-25,共5页Noise and Vibration Control

基　　金：国家自然科学基金(51265009);华东交通大学研究生创新专项资金项目(YC2014-S265)

摘　　要：为有效抑制列车车体的振动,针对列车在运行时受到的不确定轨道干扰激励等影响因素,开展一种基于标准正交基函数Laguerre的主动悬挂预测控制算法研究。首先建立列车主动悬挂系统的状态空间模型,再以此作为预测控制模型,结合预测控制中的滚动优化等基本原理,为高速列车连续时域主动悬挂系统设计相应的预测控制器。仿真结果表明:设计的预测控制器能够优化高速列车在运行时的振动主动控制性能,改善列车的乘坐舒适性。In order to effectively reduce the vibration of high-speed trains due to uncertain track interference incentives, an algorithm for active suspension prediction control based on a typical orthonormal base function, the Laguerre function, was proposed and studied. The state space model of the train’s active suspension system was set up. Regarding this model as a predictive control model and combined with the basic principle of rolling optimization in predictive control, the predictive controller for the active suspension system of the high-speed train in continuous time domain was designed. The simulation results show that the designed predictive controller can optimize the active vibration control performance of the high-speed train and improve the ride comfort of vehicles.

关 键 词：振动与波 轨道干扰激励 主动悬挂 正交基函数 状态空间模型 预测控制器 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置] TP273[自动化与计算机技术—控制科学与工程]