Sabilillah, Muhammad Daffa Safriel (2026) Sistem Estimasi Kecepatan Menggunakan Super Twisting Sliding Mode Observer Sebagai Umpan Balik Untuk Field-Oriented Control Pada Kendali Model Propulsi Kereta Tanpa Sensor. Diploma thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Sistem propulsi modern berbasis Field Oriented Control membutuhkan informasi kecepatan rotor yang akurat untuk mempertahankan orientasi medan dan menghasilkan pengendalian torsi yang presisi. Penggunaan sensor kecepatan pada sistem konvensional meningkatkan biaya, kompleksitas, serta menurunkan keandalan sistem ketika dioperasikan pada lingkungan dengan getaran tinggi dan kondisi operasi yang dinamis. Penelitian ini mengimplementasikan algoritma Super-Twisting Sliding Mode Observer sebagai estimator kecepatan pada sistem Indirect Rotor Field Oriented Control untuk model propulsi kereta berbasis motor induksi tiga fasa. Implementasi dilakukan pada mikrokontroler STM32F446RE dengan memanfaatkan sinyal arus dan tegangan stator sebagai input estimator sehingga sistem dapat beroperasi tanpa sensor kecepatan pada daerah operasi sensorless. Hasil implementasi menunjukkan bahwa estimator mampu beroperasi pada rentang sensorless 300–2700 RPM dengan Mean Absolute Percentage Error sebesar 2,43%. Pengendalian arus d-axis dan q-axis menghasilkan error rata-rata masing-masing sebesar 0,016 A dan 0,063 A, sedangkan validasi torsi menunjukkan error antara 4,0% hingga 12,4% terhadap nilai referensi. Hasil pengujian sensorless menunjukkan bahwa algoritma Super-Twisting Sliding Mode Observer mampu menghasilkan error estimasi kecepatan dibawah 5%, mempertahankan karakteristik Indirect Rotor Field Oriented Control, serta efektif digunakan sebagai sensorless speed feedback pada model sistem propulsi kereta.
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Modern propulsion systems based on Field-Oriented Control require accurate rotor speed information to maintain field orientation and achieve precise torque control. The use of speed sensors in conventional systems increases cost and complexity and reduces system reliability when operated in high-vibration environments and under dynamic operating conditions. This research implements the Super-Twisting Sliding Mode Observer algorithm as a speed estimator in an Indirect Rotor Field-Oriented Control system for a three-phase induction motor-based train propulsion model. The implementation is carried out on an STM32F446RE microcontroller by utilizing stator current and voltage signals as inputs to the estimator, enabling the system to operate without a speed sensor in the sensorless operating region. The implementation results show that the estimator is capable of operating in the sensorless range of 300–2700 RPM with the Mean Absolute Percentage Error was 2.43%. Control of the d-axis and q-axis currents resulted in average errors of 0.016 A and 0.063 A, respectively, while torque validation showed errors ranging from 4.0% to 12.4% relative to the reference value. These results indicate that the Super-Twisting Sliding Mode Observer algorithm is capable maintaining accurate speed estimates around under 5% error, maintaining the characteristics of Indirect Rotor Field Oriented Control, and effectively serving as sensorless speed feedback in a train propulsion system model.
| Item Type: | Thesis (Diploma) |
|---|---|
| Uncontrolled Keywords: | Indirect Rotor Field Oriented Control, Super-Twisting Sliding Mode Observer, estimator kecepatan, motor induksi tiga fasa, sistem propulsi kereta. |
| Subjects: | T Technology > TF Railroad engineering and operation > TF1327.O58 High speed ground transportation (train) T Technology > TK Electrical engineering. Electronics Nuclear engineering T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2692 Inverters T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2785 Electric motors, Induction. T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3070 Automatic control |
| Divisions: | Faculty of Vocational > 36304-Automation Electronic Engineering |
| Depositing User: | Muhammad Daffa Safriel Sabilillah |
| Date Deposited: | 04 Aug 2026 03:47 |
| Last Modified: | 04 Aug 2026 03:47 |
| URI: | http://repository.its.ac.id/id/eprint/141413 |
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