Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
Browse
2 results
Search Results
Conference Object Citation - WoS: 3Citation - Scopus: 4Neural Network Based Repetitive Learning Control of Robot Manipulators(Institute of Electrical and Electronics Engineers Inc., 2017) Çobanoğlu, Necati; Tatlıcıoğlu, Enver; Tatlıcıoğlu, Enver; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyControl 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.Conference Object Citation - WoS: 2Citation - Scopus: 3On Null-Space Control of Kinematically Redundant Robot Manipulators(Institute of Electrical and Electronics Engineers Inc., 2016) Çetin, Kamil; Tatlıcıoğlu, Enver; Zergeroğlu, Erkan; 03.05. Department of Electrical and Electronics Engineering; 03. Faculty of Engineering; 01. Izmir Institute of TechnologyIn this study, we consider the null-space control problem of redundant robot manipulators. Specifically for robot manipulators with kinematically redundancy where at least one extra degree of freedom is present, we introduce a sub-task controller that will ensure the use of the extra degrees of freedom for possible control purposes while still ensuring the main objective. The stability of the main (end-effector tracking) and sub-task objectives are obtained via Lyapunov based arguments. Extension to adaptive controller formulation for robotic devices with uncertain system dynamics is also presented. Numerical studies for the adaptive controller are presented to illustrate the liability of the proposed method.