自适应模糊控制在磁流变半主动悬架中的应用

李伟平; 柳超; 张利轩; 张宝珍; 窦现东

doi:10.13433/j.cnki.1003-8728.2014.1120

自适应模糊控制在磁流变半主动悬架中的应用

doi: 10.13433/j.cnki.1003-8728.2014.1120

1.
湖南大学汽车车身先进设计制造国家重点实验室, 长沙 410082

基金项目:

国家高技术研究发展计划(863计划)项目(2012AA111802)

教育部长江学者与创新团队发展计划项目(531105050037)资助

详细信息

作者简介:
李伟平(1971- ),副教授,博士,研究方向为汽车系统动力学和优化方法,lwpzlbb@yeah.net。

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出版历程
- 收稿日期: 2013-04-26

Application of Adaptive Fuzzy Control in Vehicle Semi-active Suspension System with Magnetorhelogical Damper

1.
State Key Laboratory of Advanced Design and Manufacture for Vehicle Body, Hunan University, Changsha 410082

摘要

摘要: 设计了一种应用于磁流变半主动悬架的自适应模糊控制器,该控制器利用神经网络训练模糊控制规则与隶属度函数,实现了神经网络与模糊控制的优势互补。为了综合反映汽车的侧倾和俯仰性能,建立了七自由度的半主动悬架非线性动力学模型和四轮随机路面模型,采用改进型BoucWen模型模拟磁流变阻尼器。同时为了验证控制器的稳定性,加入制动模块与转向模块,可以更加真实的反映汽车的行驶路况。仿真结果表明:神经模糊控制方法能够减小悬架的动位移、车身的垂直加速度、侧倾角加速度、俯仰角加速度,提高汽车的舒适性和安全性,改善幅度高于利用隔代遗传算法优化的分数阶PID控制器控制的半主动悬架。
- 半主动悬架 /
- 磁流变阻尼器 /
- 七自由度 /
- 四轮路面 /
- 神经模糊 /
- 分数阶PID /
- 隔代遗传算法
Abstract: A novel adaptive fuzzy controller applied to the semi-active suspension with magnetorhelogical damper is introduced in this paper,which combines neural networks with fuzzy control and complements training fuzzy control rules and membership function with neural network. In order to comprehensively reflect the performance of car's roll and pitch,the nonlinear dynamical model of semi-active suspension with seven degrees of freedom and the random road model of four wheels are established,using an improved Bouc-Wen model of magnetorhelogical damper.Meanwhile,in order to verify the stability of the controller,the brake model and the steering model are added,which may really reflect traveling road condition of the car. The simulation results show that: the neuro-fuzzy controller can decrease dynamic displacement of each suspension,the body's vertical acceleration,roll angular acceleration and pitch angular acceleration,and raise the comfort and safety of the car,and its improving magnitude is better than the semi-active suspension with the fractional PID controller optimized by atavistic algorithm.
- algorithms /
- atavistic algorithm /
- automobite suspensions /
- computer simulation /
- controllers /
- damping /
- degrees of freedom(mechanics)

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参考文献(8)

[1]	Laoufi M,Eskandarian A. Fuzzy logical control for actaivesuspension of a non-linear full-vehictae model[C]//Intelligent Vehictaes Symposium,2012
[2]	陈无畏.汽车半主动悬架的非线性神经网络自适应控制研究[J]机械工程学报,2000,36(1),76-78Chen W W Research on adaptive control for automotivesemi-actaive suspensions based on nonlinear neuralnetworks[J]Chinese Journal of MechanicalEngineering,2000,36(1):76-78(in Chinese)
[3]	周燕.基于磁流变阻尼器的汽车半主动悬架的神经模糊控制[J]南京理工大学学报,2008,32(6);716-718Zhou Y. Neuro-fuzzy control of semi-actaive vehictaesuspension system with magneto-rheological-damper[J]Journal of Nanjing University of Science and Technology,2008,32(6);716-718(in Chinese)
[4]	Ammar Abdulshaheed Aldair. Neurofuzzy Controller BasedFull Vehictae Nonlinear Actaive Suspension SystenLS,2012,3
[5]	董丹磁流变半主动悬架系统及其控制策略研究[D]杭州:浙江大学,2011Dong D. Research on the MR semi-actaive suspensionsystem and its control strategy[D]Hangzhou:ZhejiangUniversity,2011(in Chinese)
[6]	陈杰平,陈无畏基于Matlab/Simulink的随机路面建模与不平度仿真[J]农业机械学报,2010,41(3)Chen J P,Chen W W Modeling and simulation onstochastic road surface irregularity based on matlab/simulink[J]Transactaions of The Chinese Society forAgricultural Machinery,2010,41(3)(in Chinese)
[7]	张立军,张天侠车辆四轮相关时域随机输人通用模型的研究[J]农业机械学报,2005,12;29-30Zhang L J, Zhang T X. Study on general model of randominputs of the vehictae with four wheels correlated in timedomain[J]Transactaions of the Chinese Society forAgricultural Machinery,2005,12;29-30(in Chinese)
[8]	郭伟,王莉,周旺平分数阶PID模型预测控制算法改进研究[J]控制工程,2011,(5);20-23Guow,Wang L, Zhou W P. Improved fractaional-orderPID model algorithmic: control algorithm[J]ControlEngineering of China,2011,(5);20-23(in C hinese)Chang Y. N-(limension golden sectaion search:its variantsand limitations[C]//Biomedical Engineering andInformatics,2009