ANFIS Control for Robotic Manipulators | Adaptive Neuro Fuzzy Inference Systems for Intelligent Control

Jimit Patel (u. a.)

ISBN 10: 3846591718 / ISBN 13: 9783846591710

Published by LAP LAMBERT Academic Publishing, 2011

About this Item

ANFIS Control for Robotic Manipulators | Adaptive Neuro Fuzzy Inference Systems for Intelligent Control | Jimit Patel (u. a.) | Taschenbuch | 88 S. | Englisch | 2011 | LAP LAMBERT Academic Publishing | EAN 9783846591710 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 106714470

Bibliographic Details

• Title: ANFIS Control for Robotic Manipulators | Adaptive Neuro Fuzzy Inference Systems for Intelligent Control
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2011
• Language: English
• ISBN 10: 3846591718
• ISBN 13: 9783846591710
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 6D millimeters 220 millimeters width by 150 millimeters height by 6 millimeters depth
• Weight: 149 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Robots are highly reliable, dependable and technologically advanced factory equipment. The basic architecture of most commercial robots is fundamentally the same, consists of digital servo controlled electrical motor drives on serial-link kinematic machines, usually with no more than six axes (degrees of freedom). All are supplied with a proprietary controller. Virtually all robot applications require significant design and implementation effort by engineers and technicians. Each robot is unique considering the manner in which the components are put together to achieve performance that yields a competitive product. The most important considerations in the application of an industrial robot center on two issues: manipulation and integration. 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.

About the Author

Jimit Patel graduated from Nirma University (India) with B.Tech. Instrumentation & Control Engineering in 2010. He worked with Infosys Technologies Ltd. from 2010 to 2011 as a systems engineer. Currently, he is pursuing MS Electrical Engineering with specialization in Control and Robotics from North Carolina State University, USA.