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Dual Adaptive Neural Network Controller for Underactuated Systems

Published online by Cambridge University Press:  05 February 2021

Seyed Hassan Zabihifar Open the ORCID record for Seyed Hassan Zabihifar [Opens in a new window] ,
Hamed Navvabi  and
Arkady Semenovich Yushchenko
Seyed Hassan Zabihifar*
Affiliation:
Faculty of Mechatronics and Robotics, Bauman Moscow State technical university (BMSTU), Moscow, Russia. E-mail: navvabi_hamed@mecheng.iust.ac.ir
Hamed Navvabi
Affiliation:
Faculty of Mechanic Engineering, Iran University of Science and Technology (IUST), Tehran, Iran. E-mail: yusch@bmstu.ru
Arkady Semenovich Yushchenko
Affiliation:
Faculty of Mechatronics and Robotics, Bauman Moscow State technical university (BMSTU), Moscow, Russia. E-mail: navvabi_hamed@mecheng.iust.ac.ir
*
*Corresponding author. E-mail: zabihifar@student.bmstu.ru
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Summary

A new stable adaptive controller based on a neural network for underactuated systems is proposed in this paper. The control scheme has been developed for two underactuated systems as examples. The Furuta pendulum and the Inertia Wheel Pendulum (IWP) have been examined in this paper. The presented approach aims to address the control problem of the given system in swing up, stabilization, and disturbance rejection. To avoid oscillations, two adaptive neural networks (ANNs) are implemented. The first one is used to approximate the equivalent control online and the second one to minimize the oscillations.

Keywords

Adaptive neural networkOscillation compensationRotary inverted pendulumFurutaInertia wheel pendulum
Type
Article
Information
Robotica , Volume 39 , Issue 7 , July 2021 , pp. 1281 - 1298
Copyright
© The Author(s), 2021. Published by Cambridge University Press

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