Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

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

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  • Conference Object
    Citation - Scopus: 5
    Adaptive Visual Servo Regulation Control for Camera-In Configuration With a Fixed Camera Extension
    (Institute of Electrical and Electronics Engineers Inc., 2007) Tatlıcıoğlu, Enver; Dawson, Darren M.; Xian, B.
    In this paper, image-based regulation control of a robot manipulator with an uncalibrated vision system is discussed. To compensate for the unknown camera calibration parameters, a novel prediction error formulation is presented. To achieve the control objectives, a Lyapunov-based adaptive control strategy is employed. The control development for the camera-in-hand problem is presented in detail and a fixed-camera problem is included as an extension.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 4
    Adaptive Visual Servo Regulation Control for Camera-In Configuration With a Fixed Camera Extension
    (ACTA Press, 2009) Tatlıcıoğlu, Enver; Dawson, Darren M.; Xian, B.
    In this paper, image-based regulation control of a robot manipulator with an uncalibrated vision system is discussed. To compensate for the unknown camera calibration parameters, a novel prediction error formulation is presented. To achieve the control objectives, a Lyapunov-based adaptive control strategy is employed. The control development for the camera-in-hand problem is presented in detail and a fixed-camera problem is included as an extension.
  • Article
    Citation - WoS: 43
    Citation - Scopus: 48
    Adaptive Control of Redundant Robot Manipulators With Sub-Task Objectives
    (Cambridge University Press, 2009) Tatlıcıoğlu, Enver; Braganza, David; Burg, Timothy C.; Dawson, Darren M.
    In this paper, adaptive control of kinematically redundant robot manipulators is considered. An end-effector tracking controller is designed and the manipulator's kinematic redundancy is utilized to integrate a general sub-task controller for self-motion control. The control objectives are achieved by designing a feedback linearizing controller that includes a least-squares estimation algorithm to compensate for the parametric uncertainties. Numerical simulation results are presented to show the validity of the proposed controller.