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Erkan Zergeroglu on Muck Rack

Erkan Zergeroglu

As seen in: Nature, Mechanical Engineering Magazine
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Articles by Erkan Zergeroglu

A transfer learning based deep neural network adaptive controller for the Furuta pendulum subject to uncertain disturbance signals - Scientific Reports

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By Erkan Zergeroglu
| Nature Verified
Abstract In this study, a control algorithm that integrates a Deep Neural Network (DNN) adaptive control architecture with a robust disturbance rejection mechanism for the underactuated mechanical system referred to as the Futura Pendulum. The study has a hybrid learning structure that combines offline supervised pretraining of the DNN’s inner layers with an online adaptation law that updates the output-layer weights in real time.
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An Extended Jacobian-Based Formulation for Operational Space Control of Kinematically Redundant Robot Manipulators With Multiple Subtask Objectives: An Adaptive Control Approach

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By Kamil Cetin, Enver Tatlicioglu, Erkan Zergeroglu, Gebze Technical
| Mechanical Engineering Magazine Verified
Conkur, E. S. , and Buckingham, R. , 1997, “Clarifying the Definition of Redundancy as Used in Robotics,” Robotica, 15(5), pp. 583–586. [CrossRef] Siciliano, B. , 1990, “Kinematic Control of Redundant Robot Manipulators: A Tutorial,” J. Intell. Rob. Syst., 3(3), pp. 201–212. [CrossRef] Nakamura, Y. , 1991, Advanced Robotics Redundancy and Optimization, Addison-Wesley, Reading, MA. Siciliano, B. , and Khatib, O. , 2008, Springer Handbook of Robotics, Springer, Secaucus, NJ. Khatib, O.
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On Operational Space Tracking Control of Robotic Manipulators With Uncertain Dynamic and Kinematic Terms

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By Gebze Technical, Kamil Cetin, Enver Tatlicioglu, Erkan Zergeroglu
| Mechanical Engineering Magazine Verified
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.
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