Carrying Robot System Control Based on Neural Network

被引：0
|
作者：
Yang Xiuxia [1 ]
Yi Zhang [1 ]
Yang Zhiyong [1 ]
Gu Wenjin [1 ]
机构：
[1] Naval Aeronaut & Astronaut Univ, Dept Control Engn, Yantai 264001, Peoples R China
来源：
PROCEEDINGS OF THE 27TH CHINESE CONTROL CONFERENCE, VOL 5 | 2008年
关键词：
Lower Extreme Carrying Exoskeleton robot; Virtual Torque Control; Neural Network; Dynamic Mathematics Model Study; Feedforward Study Controller;
D O I：
10.1109/CHICC.2008.4605847
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The virtual torque control is a relative effective control law for the lower extremity carrying exoskeleton robot, which needs no direct measurements from the pilot or the human-machine interface,but it needs the exact mass properties and its PD controllor is not applicable for the serious nonlinear system. To overcome these defaults, the virtual prototyping software ADAMS is introduced to model the exoskeleton and the model is also used to the neural network(NN) dynamic mathematics model study. At the same time, the NN is used to the dynamic feedforward controller to compensate the human-machine interaction force. Theoretical analyse and simulation results test the feasibility and validity of this control method.
引用
收藏
页码：495 / 499
页数：5
相关论文
共 50 条
  • [1] Neural Network Control System for a Tracked Robot
    Kuzmina, Tatiana
    Dubrovskiy, Grigoriy
    PROCEEDINGS OF THE 2015 IEEE NORTH WEST RUSSIA SECTION YOUNG RESEARCHERS IN ELECTRICAL AND ELECTRONIC ENGINEERING CONFERENCE (2015 ELCONRUSNW), 2015, : 233 - 235
  • [2] Neural network control system of cooperative robot based on genetic algorithms
    Liu, Aiqin
    Zhang, Yuezhong
    Zhao, Honghua
    Wang, Shi
    Sun, Dianmin
    NEURAL COMPUTING & APPLICATIONS, 2021, 33 (14): : 8217 - 8226
  • [3] Neural network control system of cooperative robot based on genetic algorithms
    Aiqin Liu
    Yuezhong Zhang
    Honghua Zhao
    Shi Wang
    Dianmin Sun
    Neural Computing and Applications, 2021, 33 : 8217 - 8226
  • [4] Combination control of robot based on the neural network
    Zhou, ET
    He, H
    Zhou, SC
    Lin, ZZ
    PROCEEDINGS OF THE 3RD INTERNATIONAL SYMPOSIUM ON FLUID POWER TRANSMISSION AND CONTROL, 1999, : 286 - 291
  • [5] Control of Time Varying Nonlinear System of Supporting Robot Based on Neural Network
    Zhu, Yuhao
    Li, Xie
    Zheng, Hui
    Yang, Zhen
    Wu, You
    Fei, Jian
    Fu, Zhuang
    PROCEEDINGS FIRST INTERNATIONAL CONFERENCE ON ELECTRONICS INSTRUMENTATION & INFORMATION SYSTEMS (EIIS 2017), 2017, : 24 - 28
  • [6] A neural network based control system for a mobile robot employing link mechanism
    Sato, M
    Ishii, K
    2005 IEEE/ASME INTERNATIONAL CONFERENCE ON ADVANCED INTELLIGENT MECHATRONICS, VOLS 1 AND 2, 2005, : 426 - 431
  • [7] Redundant robot kinematics control based on neural network
    Ma, Guang
    Shen, Guiying
    Gaojishu Tongxin/High Technology Letters, 2002, 12 (01):
  • [8] Tracking control based on neural network for robot manipulator
    Sonmez, Murat
    Kandilli, Ismet
    Yakut, Mehmet
    ARTIFICIAL INTELLIGENCE AND NEURAL NETWORKS, 2006, 3949 : 49 - 57
  • [9] ROBOT LEARNING CONTROL BASED ON NEURAL NETWORK PREDICTION
    Asensio, Jonathan
    Chen, Wenjie
    Tomizuka, Masayoshi
    PROCEEDINGS OF THE ASME 5TH ANNUAL DYNAMIC SYSTEMS AND CONTROL DIVISION CONFERENCE AND JSME 11TH MOTION AND VIBRATION CONFERENCE, DSCC 2012, VOL 1, 2013, : 917 - +
  • [10] Artificial neural network based robot control: An overview
    Prabhu, SM
    Garg, DP
    JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 1996, 15 (04) : 333 - 365
12345