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Approach to telerobotic control using neuro-fuzzy techniques

Lookup NU author(s): Watcharin Po-Ngaen, Dr Bob Bicker, Dr Zhongxu Hu, Dr Kevin Burn

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Abstract

A bilateral teleoperator control scheme, based on a neuro-fuzzy controller is proposed for a single-axis experimental teleoperator that is designed to validate the model responses. Simulation is used to compare the dynamic response of teleoperator control using a conventional proportional + derivative (PD) with the neuro-fuzzy structures in a positon/force control mode under various conditions. A first order Sugeno neuro-fuzzy model is applied to obtain the appropriate controller parameters through the training process. A hybrid algorithm (the root-mean-square estimator rule in combined with the back-propagation rule) was designed to adjust the membership functions and the linear polynomial equations of fuzzy inference. A single joint robotic teleoperation was modelled and the simulation results show that the neuro-fuzzy approach is promising, being robust with respect to the changes in the environmental stiffness.

Publication metadata

Author(s): Po-Ngaen W, Bicker R, Hu Z, Burn K

Editor(s): Tian Huang

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 11th World Congress in Mechanism and Machine Science

Year of Conference: 2004

Pages: 1761-1766

Publisher: China Machine Press

Library holdings: Search Newcastle University Library for this item

ISBN: 7111140737

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