Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/6441
Title: Neural network based repetitive learning control of robot manipulators
Authors: Çobanoğlu, Necati
Tatlıcıoğlu, Enver
Zergeroğlu, Erkan
Çobanoğlu, Necati
Tatlıcıoğlu, Enver
Izmir Institute of Technology. Electronics and Communication Engineering
Keywords: Controllers
Flexible manipulators
Industrial robots
Manipulators
Robots
Issue Date: 2017
Publisher: Institute of Electrical and Electronics Engineers Inc.
Source: Çobanoğlu, N., Tatlıcıoğlu, E., and Zergeroğlu, E. (2017, 24-26 May). Neural network based repetitive learning control of robot manipulators. Paper presented at the 2017 American Control Conference. doi:10.23919/ACC.2017.7963781
Abstract: Control of robot manipulators performing periodic tasks is considered in this work. The control problem is complicated by presence of uncertainties in the robot manipulator's dynamic model. To address this restriction, a model free repetitive learning controller design is aimed. To reduce the heavy control effort, a neural network based compensation term is fused with the repetitive learning controller. The convergence of the tracking error to the origin is ensured via Lyapunov based techniques. Numerical simulations and experiments are performed to demonstrate the viability of the proposed controller.
Description: 2017 American Control Conference, ACC 2017; Sheraton Seattle HotelSeattle; United States; 24 May 2017 through 26 May 2017
URI: http://doi.org/10.23919/ACC.2017.7963781
http://hdl.handle.net/11147/6441
ISBN: 9781509059928
ISSN: 0743-1619
Appears in Collections:Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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