发动机磁流变半主动悬置变论域模糊控制的研究
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- 英文论文题名：A Study on the Variable Universe Fuzzy Control of Engine Magneto rheological Semi active Mount
- 论文作者：邓召学 ; 郑玲 ; 李以农 ; 张自伟
- 英文论文作者：Deng Zhaoxue Zheng Ling Li Yinong Zhang Ziwei Chongqing University ; State Key Laboratory of Mechanical Transmission ; Chongqing ; 400044
- 年：2013
- 作者机构：重庆大学机械传动国家重点实验室;
- 论文关键词：磁流变悬置 ; BP神经网络 ; 遗传算法 ; 变论域模糊控制
- 英文论文关键词：Magneto rheological mount ; BP neural network ; Genetic algorithm ; Variable universe fuzzy control
- 会议召开时间：2013-11-26
- 会议录名称：2013中国汽车工程学会年会论文集
- 英文会议录名称：Proceedings of 2013 SAE-China Congress
- 语种：中文
- 分类号：U464.13
- 学会代码：QCGC
- 会议名称：2013中国汽车工程学会年会
- 会议地点：中国北京
- 主办单位：中国汽车工程学会
- 学会名称：中国汽车工程学会
- 页数：1
- 文件大小：22k
- 原文格式：O
- 会议级别：全国
摘要
利用遗传算法(GA)BP神经网络的模型辨识方法建立了磁流变悬置的正、逆模型;并设计了变论域模糊控制器,对发动机磁流变悬置系统进行半主动控制的仿真。结果表明:变论域模糊控制比传统模糊控制具有更好的宽频隔振效果,发动机转速对应的二阶主频位侈和加速度振动峰值明显减小,验证了GABP网络逆模型及其变论域模糊控制算法的正确性和有效性。
The direct and inverse models for magneto rheological(MR) mount are created by using model identification technique with genetic algorithm(GA) BP neural network,a variable universe fuzzy controller is designed,and a simulation on the semiactive control of engine MR mount system is conducted.The results show that the variable universe fuzzy control has better vibration isolation performance in a wide frequency range compared with conventional fuzzy control,and the peak amplitudes of displacement and acceleration reduce significantly at the second dominant frequency corresponding to engine speed,validating the correctness and effectiveness of GABP neural network inverse model and its variable universe fuzzy algorithm.
The direct and inverse models for magneto rheological(MR) mount are created by using model identification technique with genetic algorithm(GA) BP neural network,a variable universe fuzzy controller is designed,and a simulation on the semiactive control of engine MR mount system is conducted.The results show that the variable universe fuzzy control has better vibration isolation performance in a wide frequency range compared with conventional fuzzy control,and the peak amplitudes of displacement and acceleration reduce significantly at the second dominant frequency corresponding to engine speed,validating the correctness and effectiveness of GABP neural network inverse model and its variable universe fuzzy algorithm.
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