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http://hdl.handle.net/20.500.12358/23385
TitleImproving Trajectory Tracking Performance of Robotic Manipulator Using Neural Online Torque Compensator
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Abstract

This paper introduces an intelligent adaptive control strategy called Neural Online Torque Compensator (NOTC) based on the learning capabilities of artificial neural networks (ANNs) in order to compensate for the structured and unstructured uncertainties in the parameters of a robotic manipulator trajectory tracking control system. A two-layered neural perceptron was designed and trained using an Error Backpropagation Algorithm (EBA) to learn the difference between the actual torques generated by the joints of a 2-DOF robotic arm and the torques generated by the computed torque disturbance rejection controller that was designed previously. An objected oriented approach based on Modelica was adopted to develop a model for the whole robotic arm trajectory tracking control system. The simulation results obtained proved the effectiveness of the NOTC compensator in improving the performance of the computed torque disturbance rejection controller by compensating for both structured and unstructured uncertainties.

Authors
Elaydi, Hatem A.
Abu Hadrous, Iyad
TypeJournal Article
Date2014
LanguageEnglish
Subjects
robotic manipulator
index terms-trajectory tracking control
neural network control
computed torque method
backpropagation algorithm
Published inJournal of Engineering Research and Technology
SeriesVolume: 1, Number: 2
Publisherالجامعة الإسلامية - غزة
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  • Staff Publications- Faculty of Engineering [908]
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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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The institutional repository of the Islamic University of Gaza was established as part of the ROMOR project that has been co-funded with support from the European Commission under the ERASMUS + European programme. This publication reflects the views only of the author, and the Commission cannot be held responsible for any use which may be made of the information contained therein.

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