Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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Scopus Q: search.filters.scopusQuartile.Q2Subject: search.filters.subject.Robot manipulators

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  • Article
    Citation - WoS: 16
    Citation - Scopus: 16
    Learning Control of Robot Manipulators in Task Space
    (John Wiley and Sons Inc., 2018) Doğan, Kadriye Merve; Tatlıcıoğlu, Enver; Zergeroğlu, Erkan; Çetin, Kamil
    Two important properties of industrial tasks performed by robot manipulators, namely, periodicity (i.e., repetitive nature) of the task and the need for the task to be performed by the end-effector, motivated this work. Not being able to utilize the robot manipulator dynamics due to uncertainties complicated the control design. In a seemingly novel departure from the existing works in the literature, the tracking problem is formulated in the task space and the control input torque is aimed to decrease the task space tracking error directly without making use of inverse kinematics at the position level. A repetitive learning controller is designed which “learns” the overall uncertainties in the robot manipulator dynamics. The stability of the closed-loop system and asymptotic end-effector tracking of a periodic desired trajectory are guaranteed via Lyapunov based analysis methods. Experiments performed on an in-house developed robot manipulator are presented to illustrate the performance and viability of the proposed controller.
  • Article
    Citation - WoS: 9
    Citation - Scopus: 13
    Nonlinear Robust Control of Tendon–driven Robot Manipulators
    (Springer Verlag, 2015) Okur, Beytullah; Aksoy, Orhan; Zergeroglu, Erkan; Tatlıcıoglu, Enver
    This work addresses the position tracking control problem for tendon–driven robotic mechanisms in the presence of parametric uncertainty and additive external disturbances. Specifically, a full state feedback nonlinear robust controller is proposed to tackle the link position tracking problem for tendon–driven robot manipulators with uncertain dynamical system parameters. A robust backstepping approach has been utilized to achieve uniformly ultimately bounded tracking performance despite the lack of exact knowledge of the dynamical parameters and presence of additive but bounded disturbance terms. Stability of the overall system is proven via Lyapunov based arguments. Simulation studies performed on a two link planar robot manipulator driven by a six tendon mechanism are presented to illustrate the effectiveness and viability of the proposed approach.