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. |
Official URL: http://conference.iproms.org/inductive_fuzzy_neura...
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) |
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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Status: | Unpublished |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: | 13 Jan 2023 02:24 |
URI: | https://orca.cardiff.ac.uk/id/eprint/37874 |
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