The Study of Trajectory Automatic Control Based on RBF Neural Network PID Control

被引：0
|
作者：
Du Zhenmian [1 ]
Ye Zhengmao [1 ]
Zhang Hui [1 ]
Bai Hua [1 ]
Xu Yuanli [2 ]
Jiang Xianguo [2 ]
机构：
[1] Harbin Inst Technol, Sch Mechatron Engn, Harbin, Peoples R China
[2] Nucl Power Inst China, Reactor Engn Res Inst, Chengdu, Peoples R China
来源：
PROCEEDINGS OF 2015 INTERNATIONAL CONFERENCE ON FLUID POWER AND MECHATRONICS - FPM 2015 | 2015年
关键词：
Hydraulic excavator; Trajectory control; PID; RBF;
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：
For the hot and difficult issues of trajectory automatic control based on single bucket hydraulic excavator, this paper introduce the control method of combining RBF neural network with traditional PID. By setting up the mathematical model of machine-electricity-hydraulic control system, using the MATLAB-Simulink simulation analysts to get the conclusion that based on RBF neural network PID control is superior to the conventional PID control. This control method can make the system have the adaptability, automatically adjust the control parameters, adapt to the changes in the charged process, improve the control performance and reliability and provide a theory basis to further realize the excavator trajectory intelligent control.
引用
收藏
页码：1234 / 1238
页数：5
相关论文
共 50 条
  • [1] Study on Adaptive PID Control Algorithm Based on RBF Neural Network
    Chen, Wenbai
    Wu, Xibao
    Pei, Yanrong
    Li, Jin-ao
    [J]. 2010 THE 3RD INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND INDUSTRIAL APPLICATION (PACIIA2010), VOL VI, 2010, : 341 - 344
  • [2] Trajectory Tracking Control Based on RBF Neural Network Learning Control
    Han, Chengyu
    Fei, Yiming
    Zhao, Zixian
    Li, Jiangang
    [J]. INTELLIGENT ROBOTICS AND APPLICATIONS (ICIRA 2022), PT IV, 2022, 13458 : 410 - 421
  • [3] Adaptive PID control based on RBF neural network identification
    Zhang, MG
    Wang, XG
    Liu, MQ
    [J]. ICTAI 2005: 17TH IEEE INTERNATIONAL CONFERENCE ON TOOLS WITH ARTIFICIAL INTELLIGENCE, PROCEEDINGS, 2005, : 681 - 683
  • [4] PID Control Based on RBF Neural Network for Ship Steering
    Li, Zeyu
    Hu, Jiangqiang
    Huo, Xingxing
    [J]. PROCEEDINGS OF THE 2012 WORLD CONGRESS ON INFORMATION AND COMMUNICATION TECHNOLOGIES, 2012, : 1076 - 1080
  • [5] Position Servo Control in Manipulator Based on RBF Neural Network PID Control
    Fang, Peng
    Ping, Li
    [J]. INTERNATIONAL CONFERENCE ON CONTROL SYSTEM AND AUTOMATION (CSA 2013), 2013, : 120 - 125
  • [6] Trajectory control for manipulators based on fuzzy RBF neural network
    Sun Hao-zhang
    Liu Guo-dong
    [J]. Proceedings of the 2007 Chinese Control and Decision Conference, 2007, : 515 - 518
  • [7] Adaptive PID control strategy based on RBF neural network identification
    Zhang, MG
    Li, WH
    Liu, MQ
    [J]. PROCEEDINGS OF THE 2005 INTERNATIONAL CONFERENCE ON NEURAL NETWORKS AND BRAIN, VOLS 1-3, 2005, : 1854 - 1857
  • [8] Research and Application of Compound Control Based on RBF Neural Network and PID
    Liu, Li
    Kang, Ke
    Zhang, Sheng
    [J]. 2008 3RD INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEM AND KNOWLEDGE ENGINEERING, VOLS 1 AND 2, 2008, : 848 - 850
  • [9] Trajectory linearization control of an aerospace vehicle based on RBF neural network
    Xue Yali & Jiang Changsheng Coll.of Automation
    [J]. Journal of Systems Engineering and Electronics, 2008, (04) : 799 - 805
  • [10] Trajectory linearization control of an aerospace vehicle based on RBF neural network
    Yali, Xue
    Jiang Changsheng
    [J]. JOURNAL OF SYSTEMS ENGINEERING AND ELECTRONICS, 2008, 19 (04) : 799 - 805
12345