Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

Permanent URI for this collectionhttps://hdl.handle.net/11147/11

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Institution Author: search.filters.institutionAuthor.Çetin, Kamil

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  • Article
    Citation - WoS: 4
    Citation - Scopus: 7
    On Operational Space Tracking Control of Robotic Manipulators With Uncertain Dynamic and Kinematic Terms
    (American Society of Mechanical Engineers, 2019) Çetin, Kamil; Tatlıcıoğlu, Enver; Zergeroǧlu, Erkan
    In this study, a continuous robust-adaptive operational space controller that ensures asymptotic end-effector tracking, despite the uncertainties in robot dynamics and on the velocity level kinematics of the robot, is proposed. Specifically, a smooth robust controller is applied to compensate the parametric uncertainties related to the robot dynamics while an adaptive update algorithm is used to deal with the kinematic uncertainties. Rather than formulating the tracking problem in the joint space, as most of the previous works on the field have done, the controller formulation is presented in the operational space of the robot where the actual task is performed. Additionally, the robust part of the proposed controller is continuous ensuring the asymptotic tracking and relatively smooth controller effort. The stability of the overall system and boundedness of the closed loop signals are ensured via Lyapunov based arguments. Experimental results are presented to illustrate the feasibility and performance of the proposed method.
  • Article
    Citation - WoS: 5
    Citation - Scopus: 6
    An Extended Jacobian-Based Formulation for Operational Space Control of Kinematically Redundant Robot Manipulators With Multiple Subtask Objectives: An Adaptive Control Approach
    (The American Society of Mechanical Engineers(ASME), 2019) Çetin, Kamil; Tatlıcıoğlu, Enver; Zergeroğlu, Erkan
    In this study, an extended Jacobian matrix formulation is proposed for the operational space tracking control of kinematically redundant robot manipulators with multiple subtask objectives. Furthermore, to compensate the structured uncertainties related to the robot dynamics, an adaptive operational space controller is designed, and then, the corresponding stability analysis is presented for kinematically redundant robot manipulators. Specifically, the proposed method is concerned with not only the stability of operational space objective but also the stability of multiple subtask objectives. The combined stability analysis of the operational space objective and the subtask objectives are obtained via Lyapunov based arguments. Experimental and simulation studies are presented to illustrate the performance of the proposed method.
  • 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.