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基于遗传算法-神经网络的半主动悬架控制仿真
引用本文:郑泉.基于遗传算法-神经网络的半主动悬架控制仿真[J].合肥工业大学学报(自然科学版),2002,25(2):230-235.
作者姓名:郑泉
作者单位:安徽农业大学,农业工程系,安徽,合肥,230036
基金项目:安徽省自然科学基金资助项目 (0 0 0 43 2 3 8)
摘    要:分析了汽车悬架的非线性特性 ,提出了一种采用遗传算法 -神经网络的控制方法实现对车辆半主动悬架系统的控制 ,并用一个 4自由度的车辆模型 ,分别对有该控制规律的半主动悬架和传统的被动悬架进行了计算机仿真 ,结果表明前者比后者具有更好的减振效果。文章将神经网络与遗传算法相结合 ,使控制器对付复杂问题的能力大大增强 ,为汽车半主动悬架控制系统的研究提供了一条崭新的途径

关 键 词:悬架  遗传算法  神经网络  仿真
文章编号:1003-5060(2002)02-0230-06
修稿时间:2001年9月30日

Simulation of vehicle semi-active suspension control based on genetic algorithm and neural networks
ZHENG,Quan.Simulation of vehicle semi-active suspension control based on genetic algorithm and neural networks[J].Journal of Hefei University of Technology(Natural Science),2002,25(2):230-235.
Authors:ZHENG  Quan
Abstract:A method of adopting genetic algorithm and neural networks to control the semi active suspension of vehicle is presented. With the help of a four degree of freedom vehicle model,the conventional passive suspension and the semi active suspension with a control strategy by genetic algorithm and neural networks are simulated respectively. The results show that the latter is superior to the former in improving the ride comfort. By combining genetic algorithm with neural networks,the ability of the controllor to deal with complicated problems is improved greatly.This paper provides a new way of studying the semi active suspension control.
Keywords:suspension  genetic algorithm  neural networks  simulation
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