车辆磁流变半主动悬架滑模变结构优化控制  

Sliding Mode Variable Structure Optimization Control of Vehicle Magneto-rheological Semi-active Suspension

作　　者：徐明 黄庆生[1,2] 李刚 XU Ming;HUANG Qingsheng;LI Gang(School of Mechatronic Engineering,East China Jiaotong University,Nanchang 330013,China;Key Laboratory of Vehicle Intelligent Equipment and Control of Nanchang,East China Jiaotong University,Nanchang 330013,China)

机构地区：[1]华东交通大学机电与车辆工程学院,南昌330013 [2]华东交通大学南昌市车辆智能装备与控制重点实验室,南昌330013

出　　处：《机械科学与技术》2021年第7期1106-1113,共8页Mechanical Science and Technology for Aerospace Engineering

基　　金：国家自然科学基金项目(51765016);江西省重点研发计划项目(20192BBEL50012)。

摘　　要：对悬架系统所用磁流变阻尼器进行阻尼特性试验,利用Levenberg-Marquardt优化算法对磁流变可调Sigmoid模型进行参数辨识,运用最小二乘法对辨识的参数进行拟合;基于天棚阻尼系统,设计了四分之一车辆悬架系统滑模控制器;采用极点配置法确定切换面参数,使用饱和函数代替符号函数,缓解滑模控制系统抖振问题,运用模糊控制、RBF神经网络对半主动悬架滑模控制器进行优化;以随机路面激励作为输入,分别对模糊控制、RBF神经网络优化的滑模控制器半主动悬架进行仿真分析。仿真结果表明:该优化算法辨识的可调Sigmoid模型具有良好的控制性能,利用该模型可实现对阻尼力的准确控制,所设计的RBF优化滑模控制器具有比模糊滑模控制器更优异的性能。The damping characteristic test of the magnetorheological damper used in the suspension system is performed.The Levenberg-Marquardt optimization algorithm is used to identify the parameters of the adjustable Sigmoid model of the magnetorheological damper.The identified parameters are fitted using the least square method.A sliding mode controller for a quarter-vehicle suspension system is designed;the switching surface parameters are determined using the pole placement method.To alleviate the chattering problem of the sliding mode control system,the saturation function is used instead of the symbolic function.Fuzzy control and RBF neural network are used to optimize sliding mode controller of semi-active suspension.With the input of a random road excitation,the simulation analysis of the semi-active suspension with the optimized sliding mode controller is performed.Simulation results show that the adjustable Sigmoid model can achieve a more precise control of the damping force,and this model identified by the optimization algorithm can control the quarter-vehicle suspension system well.Moreover,RBF optimized sliding mode controller has better performance than fuzzy sliding mode controller.

关 键 词：磁流变阻尼器 可调Sigmoid模型 参数辨识 模糊控制 滑模控制 RBF神经网络 

分 类 号：U463.33[机械工程—车辆工程]