The Linkage Mechanism with Clearance Modeling Based on Neural Network and its Intelligent Control

被引:0
|
作者
Li, Tinggui [1 ]
Xue, Shaowen [1 ]
机构
[1] Luzhou Vocat & Tech Coll, Luzhou 646005, Sichuan, Peoples R China
关键词
linkage mechanism; clearance; BP neural network; parameters self-adjusting fuzzy control;
D O I
10.4028/www.scientific.net/AMM.401-403.1644
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Using the traditional control method is difficult to obtain the ideal control result, because the linkage mechanism with clearance is a strongly nonlinear system, and it is difficult to establish the accurate mathematical model. In response to these problems, take the linkage mechanism with clearance for example and establish BP neural network offline modeling, on the basis of the experimental sample data. We separately applied the neural network internal model control and the parameters self-adjusting fuzzy control to reduce the nonlinear error caused by the clearance. The experimental results show that using intelligent control technology, the system stability has been significantly improved, and the system error has been reduced effectively.
引用
收藏
页码:1644 / 1648
页数:5
相关论文
共 50 条
  • [1] Neural network modeling and intelligent control of FCAW penetration
    Liu, Xiwen
    Wang, Guorong
    Xiao, Xinyuan
    China Welding (English Edition), 2010, 19 (01): : 54 - 59
  • [2] Neural network modeling based on FCM clustering and its application to intelligent driving
    Ma, Yong
    Yang, Yu-Pu
    Xu, Xiao-Ming
    Zidonghua Xuebao/Acta Automatica Sinica, 2002, 28 (03): : 363 - 370
  • [3] Artificial neural network-based modeling and intelligent control of transitional flows
    Sahan, RA
    KocSahan, N
    Albin, DC
    Liakopoulos, A
    PROCEEDINGS OF THE 1997 IEEE INTERNATIONAL CONFERENCE ON CONTROL APPLICATIONS, 1997, : 359 - 364
  • [4] Neural Network Intelligent Control Based on MPSO
    Kou, Aijun
    Li, Xiaojun
    IEEE ACCESS, 2023, 11 : 58565 - 58577
  • [5] Mechanism for an intelligent neural network based driving system
    Srinivasan, T
    Jonathan, JBS
    Chandrasekhar, A
    E-TECH 2004, 2004, : 53 - 60
  • [6] AN INTELLIGENT CONTROL SYSTEM BASED ON RECURRENT NEURAL FUZZY NETWORK AND ITS APPLICATION TO CSTR
    JIA Li YU Jinshou (Research Institute of Automation
    Journal of Systems Science & Complexity, 2005, (01) : 43 - 54
  • [7] AN INTELLIGENT CONTROL SYSTEM BASED ON RECURRENT NEURAL FUZZY NETWORK AND ITS APPLICATION TO CSTR
    JIA Li YU Jinshou (Research Institute of Automation
    East China University of Science and Technology
    Shanghai
    JournalofSystemsScienceandComplexity, 2005, (01) : 43 - 54
  • [8] Intelligent compaction control based on fuzzy neural network
    Ju, YF
    Lin, GF
    Fan, YD
    Liu, ZY
    PDCAT 2005: Sixth International Conference on Parallel and Distributed Computing, Applications and Technologies, Proceedings, 2005, : 930 - 934
  • [9] NEURAL NETWORK LATERAL DYNAMICS MODELING AND CONTROL BASED ON ED-LSTM FOR INTELLIGENT VEHICLE
    Fang P.
    Cai Y.
    Chen L.
    Sun X.
    Wang H.
    Lixue Xuebao/Chinese Journal of Theoretical and Applied Mechanics, 2022, 54 (07): : 1896 - 1908
  • [10] Dilated Convolutional Neural Network-Based Modeling and Tracking Control Design for Intelligent Vehicles
    Zhang, Yu
    Pei, Wenhui
    Li, Lanxin
    Ma, Baosen
    IFAC PAPERSONLINE, 2024, 58 (29): : 100 - 105