Electrical - Electronic Engineering / Elektrik - Elektronik Mühendisliği

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

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Author: search.filters.author.Tatlıcıoğlu, EnverWoS Q: search.filters.wosQuartile.Q4

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  • Article
    Citation - WoS: 6
    Citation - Scopus: 7
    Human-Robot Interfaces of the Neuroboscope: a Minimally Invasive Endoscopic Pituitary Tumor Surgery Robotic Assistance System
    (ASME, 2021) Dede, Mehmet İsmet Can; Kiper, Gökhan; Ayav, Tolga; Özdemirel, Barbaros; Tatlıcıoğlu, Enver; Hanalioğlu, Şahin; Işıkay, İlkay
    Endoscopic endonasal surgery is a commonly practiced minimally invasive neurosurgical operation for the treatment of a wide range of skull base pathologies including pituitary tumors. A common shortcoming of this surgery is the necessity of a third hand when the endoscope has to be handled to allow active use of both hands of the main surgeon. The robot surgery assistant NeuRoboScope system has been developed to take over the endoscope from the main surgeon's hand while providing the surgeon with the necessary means of controlling the location and direction of the endoscope. One of the main novelties of the NeuRoboScope system is its human-robot interface designs which regulate and facilitate the interaction between the surgeon and the robot assistant. The human-robot interaction design of the NeuRoboScope system is investigated in two domains: direct physical interaction (DPI) and master-slave teleoperation (MST). The user study indicating the learning curve and ease of use of the MST is given and this paper is concluded via providing the reader with an outlook of possible new human-robot interfaces for the robot assisted surgery systems.
  • 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: 1
    Experimental Verification of Lead-Lag Compensators on a Twin Rotor System
    (De Gruyter, 2018) Deniz, Meryem; Tatlıcıoğlu, Enver; Bayrak, Alper
    Twin rotor system is a laboratory setup resembling a simplified helicopter model that moves along both horizontal and vertical axes. The literature on control of twin rotor systems reflects a good amount of research on designing PM controllers and their extensions considering several aspects, as well as onsome nonlinear controllers. However, there is almost no previous work on design of lag-lead type compensators for twin rotor systems. In this study, by considering this open research problem, lag and lead type compensators are designed and then experimentally verified on the twin rotor system. Specifically, first, lag and lag-lag compensators are designed to obtain a reduced steady state error as compared with proportional controllers. Secondly, lead compensation is discussed to obtain a reduced overshoot. Finally, lag-lead compensators are designed to make use of their favorable properties. All compensators are applied to the twin rotor system in our laboratory. From experimental studies, it was observed that steady state error was reduced when a lag compensator was used in conjunction with a lead compensator.
  • Article
    Citation - WoS: 6
    Citation - Scopus: 7
    Neural Network Based Robust Control of an Aircraft
    (ACTA Press, 2020) Tanyer, İlker; Tatlıcıoğlu, Enver; Zergeroǧlu, Erkan
    Output tracking control of an aircraft subject to uncertainties in the dynamic model and additive state-dependent nonlinear disturbancelike terms is aimed. Uncertainties in the aircraft dynamic model yield an uncertain input gain matrix, which is neither positive definite nor symmetric and an uncertain term in the error dynamics. To deal with the uncertain input gain matrix, a decomposition method is utilized to put error dynamics in a form where an uncertain positive definite matrix multiplies the auxiliary error but this results in the control input to be pre-multiplied first with a unity upper triangular matrix which is uncertain and then with a known diagonal matrix. A novel controller composed of a neural network compensation term and an integral of signum of error is designed. A novel Lyapunov type stability analysis is utilized to prove global asymptotic tracking of output of a reference model. Extensive numerical simulations are presented to demonstrate the efficacy of the proposed controller where robustness to variation of initial states and a comparison with a robust controller are also shown. © 2020 Acta Press. All rights reserved.