Artificial neural networks for identification in real time of the robot manipulator model parameters

被引：0
|
作者：
Nawrocki, Marcin [1 ]
Nawrocka, Agata [2 ]
机构：
[1] AGH Univ Sci & Technol, Fac Mech Engn & Robot, Dept Min Dressing & Transport Machines, Krakow, Poland
[2] AGH Univ Sci & Technol, Fac Mech Engn & Robot, Dept Proc Control, Krakow, Poland
来源：
2014 15TH INTERNATIONAL CARPATHIAN CONTROL CONFERENCE (ICCC) | 2014年
关键词：
neural network; robot manipulator; identification; SYSTEMS;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, the manipulator identification process was presented. To identify single-layer neural network with sigmoidal functions that describe individual neurons was used. The main goal was the approximation nonlinearities of manipulator model in real time. It was assumed that the nonlinearity of the manipulator are unknown. The stability of the identification system adopted by the law of the learning network weights generated based on Lyapunov stability theory.
引用
收藏
页码：383 / 386
页数：4
相关论文
共 50 条
  • [1] Real time track identification with artificial neural networks
    Athanasiu, G.
    Pavlopoulos, P.
    Vlachos, S.
    Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, 1993, A324 (1-2) : 320 - 329
  • [2] Identification of Tire Model Parameters with Artificial Neural Networks
    Olazagoitia, Jose Luis
    Perez, Jesus Angel
    Badea, Francisco
    APPLIED SCIENCES-BASEL, 2020, 10 (24): : 1 - 16
  • [3] REAL-TIME TRACK IDENTIFICATION WITH ARTIFICIAL NEURAL NETWORKS
    ATHANASIU, G
    PAVLOPOULOS, P
    VLACHOS, S
    NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT, 1993, 324 (1-2): : 320 - 329
  • [4] A Dynamic Feedback Neural Model for Identification of the Robot Manipulator
    Ay, Mustafa
    Koca, Gonca Ozmen
    MECHATRONICS 2017: RECENT TECHNOLOGICAL AND SCIENTIFIC ADVANCES, 2018, 644 : 347 - 355
  • [5] Control of a robot manipulator and pendubot system using artificial neural networks
    Constantin, J
    Nasr, C
    Hamad, D
    ROBOTICA, 2005, 23 : 781 - 784
  • [6] Real-Time Decentralized Neural Backstepping Controller for a Robot Manipulator
    Garcia-Hernandez, R.
    Sanchez, E. N.
    Santibanez, V.
    Llama, M. A.
    Bayro-Corrochano, E.
    2009 IEEE CONTROL APPLICATIONS CCA & INTELLIGENT CONTROL (ISIC), VOLS 1-3, 2009, : 701 - +
  • [7] Real-Time Decentralized Neural Block Controller for a Robot Manipulator
    Garcia-Hernandez, R.
    Sanchez, E. N.
    Santibanez, V.
    Llama, M. A.
    Bayro-Corrochano, E.
    2009 IEEE-RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS, 2009, : 906 - 911
  • [8] Pose Determination System for a Serial Robot Manipulator Based on Artificial Neural Networks
    Rodriguez-Miranda, Sergio
    Yanez-Mendiola, Javier
    Calzada-Ledesma, Valentin
    Villanueva-Jimenez, Luis Fernando
    De Anda-Suarez, Juan
    MACHINES, 2023, 11 (06)
  • [9] A Real-time system for the automatic identification of motorcycle - using Artificial Neural Networks
    Pillai, B. Raveendran
    Kumar, Sukesh A.
    ICCN: 2008 INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND NETWORKING, 2008, : 445 - +
  • [10] Evaluation of Parameter Identification of a Real Manipulator Robot
    Urrea, Claudio
    Agramonte, Rayko
    SYMMETRY-BASEL, 2022, 14 (07):
12345