WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7150

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Department: search.filters.department.İzmir Institute of TechnologyInstitution Author: search.filters.institutionAuthor.Dede, Mehmet İsmet Can

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Now showing 1 - 4 of 4
  • Article
    A Hybrid Actuation System for Enhancing the Performance Metrics Related to Kinesthetic-Type Haptic Devices
    (IEEE-Inst Electrical Electronics Engineers Inc, 2025) Kucukoglu, Sefa Furkan; Can Dede, Mehmet ismet
    High torque to volume ratio, fast response, and high dynamic range are some of the desired performance metrics for kinesthetic-type haptic device actuation systems. In this article, we present a hybrid actuation system consisting of an active actuator and a magnetorheological fluid-based brake (MRF brake). MRF brake's tradeoffs, namely, off-state torque and slow response (compared to an electric motor), are investigated and resolved by this hybrid actuation system. First, the transient behavior of the MRF brake is investigated and an mathematical model is proposed to mimic its transient response behavior. It is found that the performance of the proposed model performs better than the conventionally used first-order transfer function. Second, hybrid actuation system is constructed. The active actuator is used for compensating for the speed of the response and the off-state torque based on the proposed mathematical model of the MRF brake. It is measured that the off-state torque is largely eliminated from 0.178 to 0.008 N center dot m, the dynamic range is enlarged from 15 to 42.4 dB, and its time constant is improved from 69.6 to 4.4 ms when the hybrid actuation system is used instead of just an MRF brake.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 1
    Modeling a Magneto-Rheological Fluid-Based Brake Via a Neural Network Method
    (Springer international Publishing Ag, 2022) Kucukoglu, Sefa Furkan; Dede, Mehmet Ismet Can; Ceccarelli, Marco
    Identifying the model of a magneto-rheological (MR) fluid-based brake is extremely important for designing and controlling a haptic device with hybrid actuation. Therefore, in this study, an Elman Recurrent Neural Network (ERNN) is designed to understand and model a characterization of an MR fluid-based rotational brake. Three important factors that affect the MR brake's performance are chosen as inputs: current, speed, and the first derivative of the input current. The proposed network is trained, and the performance of the network is tested with three different experimental scenarios. Then, the effect of these inputs on the system is investigated. According to the results, it can be said that the designed ERNN is a good candidate for modelling an MR brake.
  • Conference Object
    Citation - Scopus: 1
    Kinematic Representation of a Biomimetic Squid Soft Robot's Arms in a Simulation Environment
    (Springer international Publishing Ag, 2022) Emet, Hazal; Dede, M. I. Can
    Biomimetic robot systems have received attention from researchers and in accordance the implementation of soft robotic arms has been studied. Kinematic and dynamic modeling of robots with infinite degrees of freedom is challenging and a number of methods have been proposed. In this work, a procedure is proposed to represent soft robot arm motion in a simulation environment. A biomimetic squid robot is used as a case study. This robot's soft arms are modeled by using the Piecewise Constant Curvature approach. This model is visualized by discretizing the soft arms into a finite number of rigid-body manipulators in MatLab using its 3D animation toolbox.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 2
    A New Correction Coefficient Formula for the Simplified Dynamic Model of a Surgical Robot
    (Springer international Publishing Ag, 2021) Ayit, Orhan; Dede, Mehmet Ismet Can
    Execution of model-based control algorithms such as computed torque technique requires the knowledge of the dynamic model of the robotic system. In our work, the active part of the surgical robot, NeuRoboScope, has a parallel kinematics architecture and the dynamic model is relatively complicated to run in a microprocessor with limited computing capabilities. For this reason, we formulated a simplified dynamic model to run in the selected microprocessor. In this work, a new formula for calculating the correction coefficients is described to minimize the errors in the whole orientation range of the robot's base platform. This new formula is examined in terms of execution time and the result is reported in this paper.