Adaptive Neuro-Fuzzy Inference System Based Control of Robotic Manipulators

Please use this identifier to cite or link to this item: http://10.1.7.192:80/jspui/handle/123456789/11670

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DC Field	Value	Language
dc.contributor.author	Adhyaru, D. M.
dc.contributor.author	Patel, Jimit
dc.contributor.author	Gianchandani, Rishi
dc.date.accessioned	2023-04-20T11:06:47Z	-
dc.date.available	2023-04-20T11:06:47Z	-
dc.date.issued	2010-09-10
dc.identifier.citation	International Conference on Mechanical and Electrical Technology-2010, (ICMET 2010), Singapore, Page No. 353-358	en
dc.identifier.isbn	978-1-4244-8100-2
dc.identifier.uri	http://10.1.7.192:80/jspui/handle/123456789/11670	-
dc.description.abstract	Robot manipulators have become increasingly important in the field of flexible automation. Through the years considerable research effort has been made in their controller design. In order to achieve accurate trajectory tracking and good control performance, a number of control schemes have been developed. Amongst these, ANFIS (Adaptive Neuro-Fuzzy Inference System) has provided best results for control of robotic manipulators as compared to the conventional control strategies.	en
dc.publisher	IEEE	en
dc.relation.ispartofseries	ITFIC002-5	en
dc.subject	Neural Network	en
dc.subject	Fuzzy Logic	en
dc.subject	Robot Conroller	en
dc.subject	IC Faculty Paper	en
dc.subject	Faculty Paper	en
dc.subject	ITFIC002	en
dc.title	Adaptive Neuro-Fuzzy Inference System Based Control of Robotic Manipulators	en
dc.type	Faculty Papers	en
Appears in Collections:	Faculty Papers, E&I

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