基于神经网络逆系统方法的汽车底盘解耦控制  

Vehicle Chassis Decoupling Control Based on Neural Network Inverse Method

作　　者：朱茂飞[1] 陈无畏[1] 夏光[1,2] 

机构地区：[1]合肥工业大学机械与汽车工程学院,合肥230009 [2]合肥工业大学汽车工程研究院,合肥230009

出　　处：《农业机械学报》2011年第12期13-17,5,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(51075112;51175135)

摘　　要：为了消除汽车底盘各电控子系统间的耦合影响,采用了一种基于神经网络逆系统方法的底盘解耦控制策略。对集成主动前轮转向(AFS)、直接横摆力矩控制(DYC)和主动悬架(ASS)的汽车底盘系统进行研究,利用Interactor算法分析了底盘系统的可逆性,建立了多变量底盘系统的BP神经网络逆系统模型,将闭环控制器与神经网络逆系统组成复合控制器用于改善系统的动态性能,并进行了仿真验证。结果表明,基于神经网络逆系统方法的解耦控制策略能够消除底盘各电控子系统间的干涉和耦合影响,有效改善整车的操纵稳定性。In order to eliminate the interference and coupling among automobile chassis electronic control subsystems,an integrated decoupling control approach based on neural network inverse method was proposed.The integration of active front steering（AFS）,direct yaw moment control（DYC） and active suspension（ASS） was studied.According to Interactor algorithm,the reversibility of chassis system was analyzed and a BP neural network inverse system of the multivariable chassis system was obtained.Designing a close-loop controller and combining it with neural network inverse system,a compound controller was completed to improve dynamic performance.The simulation results showed that the proposed decoupling control approach could eliminate the interference and couple among automobile chassis electronic control subsystems,and improve the automobile handling and stability performance.

关 键 词：汽车 底盘 解耦控制 神经网络 逆系统方法 

分 类 号：U463.1[机械工程—车辆工程] TP273[交通运输工程—载运工具运用工程]