Mechanical Engineering / Makina Mühendisliği
Permanent URI for this collectionhttps://hdl.handle.net/11147/4129
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Conference Object Digital Twin of a Servo Driver of a Servo Motor as a First Step Towards a Digital Twin of a Robot Mechanism(Springer, 2022) Küçükoğlu, Sefa Furkan; Carbone, Giuseppe; Küçükoğlu, Sefa Furkan; Dede, Mehmet İsmet Can; 03.10. Department of Mechanical Engineering; 01. Izmir Institute of Technology; 03. Faculty of EngineeringDigital Twin (DT) offers us to acquire actual system’s critical information and hence, it may be possible to develop and produce more suitable systems in terms of low energy consumption and effectiveness. In this way, responsible consumption and production systems can be designed and the system’s parameters can be tuned via DT. In this study, the model of a servomotor system that is used for industrial purposes is experimentally obtained. This study consists of two steps. In the first step, within the embedded control of the system, position and velocity control loops are deactivated. Then through the servo driver, currents with sinusoidal waveforms at various frequencies are applied to the servomotor. The resultant angular velocity of the motor is monitored and recorded. The amplitude of the current is kept constant during this study. The frequency of the current, however, is increased logarithmically. By using these data, a first-order transfer function (TF) is identified for the motor model. In the second step, all control loops are activated. Consequently, the total servomotor system could be represented in a digital environment. Furthermore, the static friction issue is overcome by using a Coulomb friction model with stiction effect. Finally, several experiments are conducted and then results are compared with the digital model of the servomotor system. The results clearly show that digital model can fairly represent the physical system.Conference Object Training and Modelling the Non-Linear Behavior of an Mr Brake by Using Rnn and Lstm(VDE Publishing House, 2021) Karabulut, Mehmet Görkem; Karabulut, Mehmet Görkem; Küçükoğlu, Sefa Furkan; Dede, Mehmet İsmet Can; Dede, Mehmet İsmet Can; Küçükoğlu, Sefa Furkan; 03.10. Department of Mechanical Engineering; 01. Izmir Institute of Technology; 03. Faculty of EngineeringA magneto-rheological (MR) fluid-based semi-active actuation system, or in other words, an MR-fluid based brake system, was designed for displaying larger amount of resistive forces without jeopardizing the dynamic performance of a haptic interface. The working principle of the MR brake device depends on the viscous fluid called MR fluid that changes its viscosity when exposed to the magnetic field. Thus, generated resistive torque can be controlled via regulating the magnetic field by modifying the electrical current that passes along a coil which provides this magnetic field.Dynamic system modeling is required in order to develop a high-performance control. In this study, modeling methods of an MR-fluid based brake is investigated in terms of its friction and hysteresis characteristics.There are numerous works in the literature in which two well-known learning sequence methods, Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM), are used for non-linear dynamic system modeling. In the scope of this study, the performance of RNN and LSTM are compared with the Bouc-Wen model which is commonly used in MR-fluid based system modeling. The effect of learning rate and the number of epoch being the important hyper-parameters, for RNN and LSTM models are investigated.In accordance with these information, both methods can be used for the control purposes of a MR-fluid based brake system. © VDE VERLAG GMBH · Berlin · Offenbach.