基于遗传算法和神经网络的车辆主动悬架控制技术  

Control Technology of Vehicle Active Suspension Based on Genetic Algorithm and Neural Network

作　　者：唐传茵[1] 李华[1,2] 周炜[3] 周淑文[1] 赵广耀[1] 

机构地区：[1]东北大学机械工程与自动化学院,沈阳110004 [2]沈阳农业大学工程学院,沈阳110161 [3]交通部公路科学研究院汽车运输技术研究中心,北京100088

出　　处：《农业机械学报》2009年第2期6-11,共6页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家自然科学基金资助项目(10402008);交通部西部交通建设科技项目(2005031822322)

摘　　要：采用遗传算法与神经网络相结合的控制策略,以四自由度车辆主动悬架半车模型为仿真对象,与传统的被动悬架进行控制性能比较。通过改变神经网络训练参数、遗传算法输入函数以及车速,对系统的响应特性进行了分析。结果表明车辆主动悬架控制策略可以减小车辆的振动,改善车辆行驶平顺性。An active suspension system of vehicles by using the genetic algorithms and neural network controls strategy has been proposed. A half-car four-degree of freedom suspension vibration model was described. Compared with the conventional passive suspension system, the analysis has been done to the system control performance. The analysis of the system response was obtained through the change of the neural network training coefficients, genetic algorithms input functions and the change of velocity. The simulation results indicated that the vehicle vibration could be reduced and the ride comfort is ameliorated by the proposed suspension systems.

关 键 词：车辆 主动悬架 神经网络 遗传算法 仿真 

分 类 号：U463.33[机械工程—车辆工程]