Perancangan Neural Network-Genetic Algorithm (NN-GA) Observer Untuk Identifikasi Kecepatan Motor Induksi

Purwahyudi, Bambang (2005) Perancangan Neural Network-Genetic Algorithm (NN-GA) Observer Untuk Identifikasi Kecepatan Motor Induksi. Masters thesis, Institut Teknologi Sepuluh November.

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Abstract

Penelitian ini membahas pengembangkan kontrol kecepatan tanpa sensor kecepatan motor induksi yang dioperasikan dengan metoda field oriented control (FOC). Kecepatan motor induksi diidentifikasi oleh suatu observer. Estimasi kecepatan motor oleh observer hanya memerlukan masukan tegangan dan arus stator. Observer untuk identifikasi kecepatan motor menggunakan metoda Neural Network-Genetic Algorithm (NN-GA). Algoritma pembelajaran NN menggunakan backpropagasi dan GA digunakan untuk mengoptimasi parameter-parameter NN sehingga diperoleh struktur NN yang optimum. NN-GA Observer dirancang untuk menentukan pola dari fluksi rotor dan kecepatan sudut rotor, sehingga dapat dimanfaatkan untuk pengendalian kecepatan motor induksi. Hasil simulasi menunjukkan bahwa observer dapat mengestimasi fluksi rotor dan kecepatan rotor motor induksi. Neural network-genetic algorithm (NN-GA) yang diusulkan menunjukkan performansi baik.
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This research discusses the development of sensorless speed control for field oriented control (FOC) Induction Motor Drives. Induction motor speed is identified by an observer. Induction motor speed using observer only requests the input voltage and stator current. Observer for identification of induction motor speed uses Neural Network-Genetic Algorithm (NN-GA) method. Neural Network (NN) use backpropagation learning algorithm and GA is used to optimize NN's parameters, so that obtained the optimum NN's structure. NN-GA observer is designed to determine the pattern of flux rotor and rotor angular velocity, so that can be used induction motor speed control. The simulation results show that observer can estimate the patterns of flux rotor and rotor speed of induction motor. The proposed neural network-genetic algorithm (NN-GA) observer shows the good performance.

Item Type:	Thesis (Masters)
Additional Information:	RTE 621.313 6 Pur p
Uncontrolled Keywords:	Motor Induksi, Field Oriented Control, NN-GA Observer, Induction Motor, Field Oriented Control, NN-GA Observer.
Subjects:	Q Science > QA Mathematics > QA402.5 Genetic algorithms. Interior-point methods. T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2785 Electric motors, Induction.
Divisions:	Faculty of Electrical Technology > Electrical Engineering > 20101-(S2) Master Thesis
Depositing User:	magang .
Date Deposited:	07 Oct 2026 01:31
Last Modified:	07 Oct 2026 01:31
URI:	http://repository.its.ac.id/id/eprint/145357

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