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 18 条

[1]

[Anonymous], 1999, Neural network control of robot manipulators and nonlinear systems

[2]

[Anonymous], J IEEE T NEURAL NETW

[3] NEURAL NETWORKS FOR CONTROL-SYSTEMS - A SURVEY [J].

HUNT, KJ ;

SBARBARO, D ;

ZBIKOWSKI, R ;

GAWTHROP, PJ .

AUTOMATICA, 1992, 28 (06) :1083-1112

[4]

K. J. A<degrees>stro<spacing diaeresis>m, 2013, Adaptive control

[5]

Liu G., 2001, ADV IND CONTROL

[6] Self-tuning Controller for Nonlinear Object [J].

Nawrocka, Agata ;

Kwasniewski, Janusz .

MECHATRONIC SYSTEMS AND MATERIALS: MECHATRONIC SYSTEMS AND ROBOTICS, 2010, 164 :139-144

[7]

Page G.F., 1993, Application of Neural Networks to Modelling and Control

[8] A PERCEPTION NETWORK FOR FUNCTIONAL IDENTIFICATION AND CONTROL OF NONLINEAR-SYSTEMS [J].

SADEGH, N .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 1993, 4 (06) :982-988

[9]

Slotine J. J. E., 1991, APPL NONLINEAR CONTR

[10]

Soderstrom T., 1997, IDENTYFIKACJA SYSTEM

← 1 2 →