The Research of Automobile Suspension System Performance Based on the Fuzzy Neural Network Control

被引：0
|
作者：
Zhang Guosheng [1 ]
Ye Song [1 ]
Zhang Xia [1 ]
Peng Jingyi [1 ]
机构：
[1] Minist Transport, Res Inst Highway, Beijing, Peoples R China
来源：
2014 IEEE TRANSPORTATION ELECTRIFICATION CONFERENCE AND EXPO (ITEC) ASIA-PACIFIC 2014 | 2014年
关键词：
active suspension; Matlab/simulink; Anfis; simulation;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The dynamic performance of suspension systems directly influenced ride comfort and handling stability of driving vehicles. Automobile suspension was assumed as the research object. Dynamics performance index of suspension was analyzed, and dynamic model and state space model of 1/2 body with 6 degree-of-freedom were established. According to the control principle, considering the influence of the input disturbance, a fuzzy controller and self-adaptive neural fuzzy controller were established. Based on the suspension mathematical model and fuzzy neural network controller, the model was simulated by MATLAB/SIMULINK software, and the performance of active suspension was compared to the passive suspension. The result showed that vibration of active suspension could reduce the bodywork acceleration effectively using the fuzzy neural network control algorithm. Its performance was improved, and the requirement of stability and comfort was satisfied.
引用
下载
收藏
页数：6
相关论文
共 50 条
  • [41] RETRACTED: Finite Element Structure Analysis of Automobile Suspension Control Arm Based on Neural Network Control (Retracted Article)
    Li, Yixuan
    SECURITY AND COMMUNICATION NETWORKS, 2021, 2021
  • [42] Automatic control system of automobile suspension
    Li, Yang
    Li, Guo
    Zhang, Qianrong
    PROCEEDINGS OF THE 5TH INTERNATIONAL CONFERENCE ON CIVIL ENGINEERING AND TRANSPORTATION 2015, 2016, 30 : 1824 - 1828
  • [43] Predictive Control System of Gas Recovery Based on Neural Network and Fuzzy Control
    Bian, H. Y.
    Chang, Y. L.
    PROCEEDINGS OF THE 2015 INTERNATIONAL CONFERENCE ON ELECTRICAL, AUTOMATION AND MECHANICAL ENGINEERING (EAME 2015), 2015, 13 : 393 - 396
  • [44] Internal model control of inductive magnetic suspension spherical active joints based on fuzzy neural network inverse system
    Zeng, Li
    Zhang, Xiaohong
    ADVANCES IN MECHANICAL ENGINEERING, 2015, 7 (11):
  • [45] The Research on the Fault Diagnosis for Boiler System Based on Fuzzy Neural Network
    Zhao, Yawei
    Chen, Liang
    Yang, Qing
    2008 7TH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-23, 2008, : 8552 - 8556
  • [46] Research on Risk Assessment of Information System Based on Fuzzy Neural Network
    Zhu, Guangliang
    Wang, Yuanbao
    PROCEEDINGS OF THE INTERNATIONAL ACADEMIC CONFERENCE ON FRONTIERS IN SOCIAL SCIENCES AND MANAGEMENT INNOVATION (IAFSM 2018), 2018, 62 : 50 - 55
  • [47] Research on the Fault Diagnosis for Boiler System based on Fuzzy Neural Network
    Yu Yang
    Chen Liang
    Yang Qing
    Zhao Yawei
    2009 WRI WORLD CONGRESS ON SOFTWARE ENGINEERING, VOL 2, PROCEEDINGS, 2009, : 128 - 132
  • [48] Fault Diagnosis System Of The Fire Control System Based On Fuzzy Neural Network
    Zhang Peng-jun
    Bo Yu-cheng
    Wang Hui-yuan
    Li Qiang
    ADVANCED DESIGNS AND RESEARCHES FOR MANUFACTURING, PTS 1-3, 2013, 605-607 : 828 - 831
  • [49] Recognition of automobile road surface based on fuzzy clustering neural network
    Liu, YH
    Ao, MW
    Wang, GL
    PROCEEDINGS OF THE THIRD INTERNATIONAL SYMPOSIUM ON INSTRUMENTATION SCIENCE AND TECHNOLOGY, VOL 2, 2004, : 368 - 374
  • [50] ADAPTIVE NEURAL NETWORK CONTROL OF ELECTROMAGNETIC SUSPENSION SYSTEM
    Suebsomran, Anan
    INTERNATIONAL JOURNAL OF ROBOTICS & AUTOMATION, 2014, 29 (02): : 144 - 154
12345