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Inductive fuzzy neural network for multi-input multi-output dynamic systems modelling

Pham, Duc Truong, Fahmy, Ashraf and Eldukhri, Eldaw Elzaki 2007. Inductive fuzzy neural network for multi-input multi-output dynamic systems modelling. Presented at: I*PROMS 2007 Innovative Production Machines and Systems, online, 1-14 July 2007.

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Abstract

This paper presents a systematic inductive fuzzy neural network for multi-input multi-output dynamic systems modeling of a 6-DOF PUMA560® industrial robot arm based on input/output measurements. An inductive learning algorithm is applied to generate the required fuzzy modelling rules from input/output numerical measurements recorded from the dynamic system. Then, a full differentiable fuzzy neural network is developed to construct the dynamic model of the multi-input multi-output system, while back-propagation algorithm or similar techniques can be further applied to tune the network parameters due to the differentiable nature of the developed network.

Item Type: Conference or Workshop Item (Paper)
Date Type: Completion
Status: Unpublished
Schools: Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Engineering
Subjects: T Technology > TJ Mechanical engineering and machinery
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Last Modified: 09 Aug 2020 16:39
URI: http://orca.cf.ac.uk/id/eprint/37874

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