Abstract

In this paper, a novel forward adaptive neural MIMO NARX model is used for modelling and identifying the forward kinematics of an industrial 3-DOF robot arm system. The nonlinear features of the forward kinematics of the industrial robot arm drive are thoroughly modelled based on the forward adaptive neural NARX model-based identification process using experimental input-output training data. This paper proposes a novel use of a back propagation (BP) algorithm to generate the forward neural MIMO NARX (FNMN) model for the forward kinematics of the industrial 3-DOF robot arm. The results show that the proposed adaptive neural NARX model trained by a Back Propagation learning algorithm yields outstanding performance and perfect accuracy.

Details

Title
Novel Adaptive Forward Neural MIMO NARX Model for the Identification of Industrial 3-DOF Robot Arm Kinematics
Author
Ho Pham Huy Anh 1 ; Nguyen Thanh Nam 2 

 Faculty of Electrical and Electronic Engineering, HCM City University of Technology, VNU-HCM, Vietnam 
 DCSELAB, HCM City University of Technology, VNU-HCM, Vietnam 
Publication year
2012
Publication date
Oct 2012
Publisher
Sage Publications Ltd.
ISSN
17298806
e-ISSN
17298814
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2325269679
Copyright
© 2012. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.