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Neural Adaptive Control of a Robot Joint Using Secondary Encoders

  • Using industrial robots for machining applications in flexible manufacturing processes lacks a high accuracy. The main reason for the deviation is the flexibility of the gearbox. Secondary Encoders (SE) as an additional, high precision angle sensor offer a huge potential of detecting gearbox deviations. This paper aims to use SE to reduce gearbox compliances with a feed forward, adaptive neural control. The control network is trained with a second network for system identification. The presented algorithm is capable of online application and optimizes the robot accuracy in a nonlinear simulation.

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Author:Jonas WeigandORCiD, Magnus VolkmannORCiD, Martin RuskowskiORCiD
URN (permanent link):urn:nbn:de:hbz:386-kluedo-62123
ISBN:978-3-030-19648-6
ISSN:2194-5365
Parent Title (English):Advances in Service and Industrial Robotics
Publisher:Springer
Place of publication:Switzerland
Editor(s):Karsten BernsORCiD, Daniel GörgesORCiD
Document Type:Article
Language of publication:English
Publication Date:2021/01/13
Year of Publication:2019
Publishing Institute:Technische Universität Kaiserslautern
Date of the Publication (Server):2021/01/13
Tag:Neural Adaptive Control; Robot control; Secondary Encoders
Number of page:8
Source:https://link.springer.com/book/10.1007/978-3-030-19648-6#editorsandaffiliations
Faculties / Organisational entities:Fachbereich Maschinenbau und Verfahrenstechnik
DDC-Cassification:5 Naturwissenschaften und Mathematik / 500 Naturwissenschaften
Licence (German):Creative Commons 4.0 - Namensnennung (CC BY 4.0)
Licence (German):Zweitveröffentlichung