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Proceedings Paper

Robotic hybrid position/force control using artificial neural network
Author(s): Yong Zheng; Weidong Chen; Bo You; Hegao Cai
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Paper Abstract

A hybrid position/force controller is designed for the joint 2 and the joint 3 of the PUMA 560 robot. The hybrid controller includes a multilayered neural network, which can identify the dynamics of the contacted environment and can optimize the parameters of the PID controller. The experimental results show that after having been trained, the robot has both stable response to the training patterns and strong adaptive ability to the situation between the patterns.

Paper Details

Date Published: 28 August 1995
PDF: 5 pages
Proc. SPIE 2620, International Conference on Intelligent Manufacturing, (28 August 1995); doi: 10.1117/12.217558
Show Author Affiliations
Yong Zheng, Harbin Institute of Technology (China)
Weidong Chen, Harbin Institute of Technology (China)
Bo You, Harbin Institute of Technology (China)
Hegao Cai, Harbin Institute of Technology (China)

Published in SPIE Proceedings Vol. 2620:
International Conference on Intelligent Manufacturing
Shuzi Yang; Ji Zhou; Cheng-Gang Li, Editor(s)

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