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Neuro-fuzzy modelling and control of robot manipulators for trajectory tracking

Pham, D. T. and Fahmy, Ashraf 2005. Neuro-fuzzy modelling and control of robot manipulators for trajectory tracking. Presented at: 16th IFAC World Congress 2005, Prague, Czech Republic, 4-8 July 2005. Published in: Zitek, Pavel ed. Proceedings of the 16th IFAC World Congress, 2005. World Congress International Federation of Automatic Control, p. 1452. 10.3182/20050703-6-CZ-1902.01453

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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 modelling rules from input/output measurements 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 on-line 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.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Engineering
Subjects: T Technology > TA Engineering (General). Civil engineering (General)
Uncontrolled Keywords: dynamic systems, fuzzy systems, fuzzy-PID controllers, neuro-fuzzy systems, robot manipulators
Publisher: International Federation of Automatic Control
ISBN: 978-3-902661-75-3
ISSN: 14746670
Last Modified: 29 Apr 2016 03:46
URI: http://orca-mwe.cf.ac.uk/id/eprint/69258

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