Soebagio Soebagio
Jurusan Elektro FTI, Institut Teknologi Sepuluh Nopember Surabaya

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Pengaturan Kecepatan Motor Induksi Tanpa Sensor Kecepatan dengan Metoda Direct Torque Control Menggunakan Observer Recurrent Neural Network Sunarno, Epyk; Soebagio, Soebagio; Purnomo, Mauridhi Heri
Jurnal Teknik Elektro Vol 8, No 2 (2008): SEPTEMBER 2008
Publisher : Institute of Research and Community Outreach

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (262.771 KB) | DOI: 10.9744/jte.8.2.88-95


This paper describes about development of sensorless control for three phase induction motor speed which is operated by Direct Torque Control (DTC). Induction motor speed is identified by an Observer. Current supply and Stator Voltage are ruquired by Observer to gain Motor Speed Estimation. Observer for motor speed identification is developed using Artificial Neural Network (ANN) Method and Recurrent Neural Network (RNN) learning algorithm. The simulation results using MathLab/Simulink show that on PI controller with Recurrent Neural Network (RNN) observer, there are the overshoot 7,0224%, rise time 0,0125 second and settling time 0,364 second with reference speed 77,9743 rad./sec. Abstract in Bahasa Indonesia: Penelitian ini membahas pengembangan kontrol pada kecepatan motor induksi tiga fasa tanpa sensor kecepatan (speed sensorless) yang dioperasikan dengan metoda Direct Torque Control (DTC). Kecepatan motor induksi diidentifikasi oleh suatu observer. Estimasi kecepatan motor oleh observer memerlukan masukkan arus dan tegangan stator. Observer untuk identifikasi kecepatan motor menggunakan metode Artificial Neural Network (ANN) dengan algoritma pembelajaran menggunakan Recurrent Neural Network (RNN). Hasil simulasi menggunakan matlab-simulink menunjukkan saat motor diberikan kecepatan referensi 77,9743 rad/detik terjadi overshoot 7,0224% , rise time 0,0125 detik dan settling time 0,364 detik. Kata Kunci: direct torque control, speed sensorless, recurrent neural network
Jurnal Teknik Elektro Vol 8, No 2 (2008): SEPTEMBER 2008
Publisher : Institute of Research and Community Outreach

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (249.006 KB) | DOI: 10.9744/jte.8.2.79-87


This paper describes about development of 3 phase speed sensorless induction motor speed controller using Field Oriented Vector(FOC) method. Motor speed is estimated by an observer using Self Constructing fuzzy Neural Network (SCFNN) with Levenberg Marquardt(LM) learning algorithm method, that replaces backpropagation method because this method is slow to reach convergent. SCFNN method combines the fuzzy and neural network. The simulation results show that the system can estimate flux and speed of induction motor and it converges faster than backpropagation method. .The estimation result can be used to identify rotor speed of induction motor with good performance Abstract in Bahasa Indonesia: Dalam penelitian ini dikembangkan pengaturan kecepatan motor induksi 3 phase tanpa sensor yang dioperasikan dengan metoda Field Oriented Vector (FOC). Kecepatan motor diestimasi oleh suatu observer dengan suatu metoda Self Constructing Fuzzy Neural Network (SCFNN) dimana pelatihannya menggunakan metode algoritma pelatihan Levenberg Marquardt (LM), yang menggantikan metode Backpropagasi karena metode ini kurang cepat mencapai konvergen. Metode SCFNN mempunyai kemampuan untuk menggabungkan Fuzzy dan Neural Networks. Hasil simulasi menunjukkan sistem dapat mengestimasi fluksi dan kecepatan dengan kekonvergenan yang lebih cepat dari metode backpropagasi. Hasil estimasi dapat digunakan untuk mengidentifikasi kecepatan rotor motor induksi Kata kunci: pengaturan kecepatan, motor induksi tanpa sensor, FOC, SCFNN observer, Levenberg Marquardt
New Algorithm for the Smoothing Speed Control of Induction Motor in Electric Car based on Self-Tuning Parameter PID-Fuzzy Logic Happyanto, Dedid Cahya; Soebagio, Soebagio; Purnomo, Mauridhi Hery
IPTEK The Journal for Technology and Science Vol 23, No 2 (2012)
Publisher : IPTEK, LPPM, Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20882033.v23i2.10


Driving system of electric car for low speed has a performance of controller that is not easily set up on large span so it does not give a comfort to passengers. The study has been tested in the bumpy road conditions, by providing disturbances in the motor load, it is to describe the condition of the road. To improve the system performance, the speed and torque controller was applied using Field Oriented Control (FOC) method. In this method, On-Line Proportional Integral Derivative Fuzzy Logic Controller (PID-FLC) is used to give dynamic response to the change of speed and maximum torque on the electric car and this results the smooth movement on every change of car performance both in fast and slow movement when breaking action is taken. Optimization of membership functions in Fuzzy PID controller is required to obtain a new PID parameter values which is done in autotuning in any changes of the input or disturbance. PID parameter tuning in this case using the Ziegler-Nichols method based on frequency response. The mechanism is done by adjusting the PID parameters and the strengthening of the system output. The test results show that the controller Fuzzy Self-Tuning PID appropriate for Electric cars because they have a good response about 0.85% overshoot at to changes in speed and braking of electric cars.
Distorsi dalam Transisi Demokrasi di Indonesia Soebagio, Soebagio
Makara Human Behavior Studies in Asia Vol. 13, No. 2
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar


Reformation which shifts democratization of the state gave constructive energy for Indonesian to reconstruct its democratic state. Therefore, reformation which became the democratic transition to democratic consolidation, is a phase toward substancial democratic state who prospers the people in politics, social & economics. In fact, the democratic transition is not always smooth; many distortions disturbing the democratic consolidation toward the realization of the democratic state appear.