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Neuro-fuzzy inverse model control structure of robotic manipulators utilized for physiotherapy applications

Ashraf Fahmy Abdo Orcid Logo, A.M. Abdel Ghany

Ain Shams Engineering Journal, Volume: 4, Issue: 4, Pages: 805 - 829

Swansea University Author: Ashraf Fahmy Abdo Orcid Logo

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Abstract

This paper presents a new neuro-fuzzy controller for robot manipulators. First, an inductive learning technique is applied to generate the required inverse modeling rules from input/output data recorded in the off-line structure learning phase. Second, a fully differentiable fuzzy neural network is...

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Published in: Ain Shams Engineering Journal
ISSN: 2090-4479
Published: Elsevier BV 2013
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa62566
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Abstract: This paper presents a new neuro-fuzzy controller for robot manipulators. First, an inductive learning technique is applied to generate the required inverse modeling rules from input/output data recorded in the off-line structure learning phase. Second, a fully differentiable fuzzy neural network is developed to construct the inverse dynamics part of the controller for the online parameter learning phase. Finally, a fuzzy-PID-like incremental controller was employed as Feedback servo controller. The proposed control system was tested using dynamic model of a six-axis industrial robot. The control system showed good results compared to the conventional PID individual joint controller.
Keywords: Dynamic systems; Fuzzy systems; Fuzzy-PID controllers; Neuro-fuzzy systems; Robot manipulators
College: Faculty of Science and Engineering
Issue: 4
Start Page: 805
End Page: 829