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

页码：383 / 386

页数：4

共 50 条

[31] Studies on the possibility of applying artificial neural networks to estimate real time operation parameters of power systems
Shen, C
Sun, YZ
Lu, Q
CONTROL OF POWER SYSTEMS AND POWER PLANTS 1997 (CPSPP'97), 1998, : 305 - 309
[32] ROBOT CONTROL BY ARTIFICIAL NEURAL NETWORKS
ASAKAWA, K
BULLETIN OF THE JAPAN SOCIETY OF PRECISION ENGINEERING, 1990, 24 (03): : 163 - 167
[33] Water Distribution Networks Model Identification using Artificial Neural Networks
Mosetlhe, Thapelo
Hamam, Yskandar
Du, Shengzhi
Monacelli, Eric
Alayli, Yasser
2019 IEEE AFRICON, 2019,
[34] Identification of parameters of dynamic Preisach model by neural networks
Trapanese, Marco
JOURNAL OF APPLIED PHYSICS, 2008, 103 (07)
[35] Identification of DEM simulation parameters by Artificial Neural Networks and bulk experiments
Benvenuti, L.
Kloss, C.
Pirker, S.
POWDER TECHNOLOGY, 2016, 291 : 456 - 465
[36] Identification of minerals using artificial neural networks based on Moessbauer parameters
Shi, Hairong
Xiao, Yuming
Huang, Hongbo
Wu, Dongmin
Ali, A. M.
Li, Min
Li, Shimin
Xia, Yuanfu
He Jishu/Nuclear Techniques, 2000, 23 (07): : 467 - 474
[37] On-line identification of modal parameters using artificial neural networks
Lim, TW
Cabell, RH
Silcox, RJ
JOURNAL OF VIBRATION AND ACOUSTICS-TRANSACTIONS OF THE ASME, 1996, 118 (04): : 649 - 656
[38] Using of Artificial Neural Networks (ANN) for Aircraft Motion Parameters Identification
Bondarets, Anatolij
Kreerenko, Olga
ENGINEERING APPLICATIONS OF NEURAL NETWORKS, PROCEEDINGS, 2009, 43 : 246 - 256
[39] Identification of Induction Motor Parameters in Industrial Drives with Artificial Neural Networks
Karanayil, Baburaj
Rahman, Muhammed Fazlur
Grantham, Colin
ADVANCES IN FUZZY SYSTEMS, 2009, 2009
[40] Input parameters for artificial neural networks in frame connection damage identification
Wang, Baisheng
Ni, Yiqing
Ko, Janming
Zhendong Gongcheng Xuebao/Journal of Vibration Engineering, 2000, 13 (01): : 137 - 142

← 1 2 3 4 5 →