Mufit, Choirul (2021) Rancang Bangun Sistem Speed Sensorless Induction Motor Berbasis Disturbance Observer Dan Extended Kalman Filter. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Motor induksi dipilih karena memiliki banyak kelebihan diantaranya tidak memerlukan brushes, inersia motor rendah ukuran dan berat yang ringan serta relatif murah. penggunaan sensor kecepatan pada motor induksi dinilai kurang efektif karena harganya yang mahal dan reliability yang semakin berkurang. Seiring berjalannya waktu dikembangkan sebuah metode speed sensorless motor induksi yang digunakan untuk menggantikan sensor kecepatan dan salah satunya adalah dengan menggunakan estimator dengan algoritma disturbance observer dan Extended Kalman filter. Sensor arus digunakan untuk mengukur arus yang masuk kedalam motor induksi, Sensor kecepatan digunakan sebagai validasi dari estimasi yang telah dibuat ,Toshiba Inverter VF-nC3 digunakan sebagai kontroller motor induksi, serta software Simulink MATLAB untuk membangun algoritma estimasi. Dari penelitian yang telah dilakukan hasil estimator extended kalman filter memiliki RMSE RMSE steady state terendah pada kecepatan 650 rpm yaitu sebesar 0.637%. Sedangkan Hasil Estimator Disturbance observer untuk mengestimasi kecepatan memiliki RMSE steady state terendah pada kecepatan 350 rpm yaitu 0.979%. Adapun dari perbandingan kedua algoritma dalam estimasi kecepatan yang sama didapatkan bahwa estimasi kecepatan menggunakan disturbance observer memiliki eror RMSE lebih kecil Namun memiliki error oveshoot estimasi di awal respon estimasinya. Kemudian pada Pengujian perubahan kecepatan dapat diketahui bahwa estimator real-time berbasis extended kalman filter dan disturbance observer dapat mengikuti perubahan kecepatan yang ada.
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The induction motor was chosen because it has many advantages including not requiring brushes, low inertia motor size and light weight and relatively cheap. the use of speed sensors on induction motors is considered less effective because of the high price and diminishing reliability. Over time, a speed sensorless induction motor method was developed which is used to replace the speed sensor and one of them is by using an estimator with the disturbance observer algorithm and the Extended Kalman filter. The current sensor is used to measure the current entering the induction motor, the speed sensor is used as validation of the estimates that have been made, the Toshiba Inverter VF-nC3 is used as an induction motor controller, and the Simulink MATLAB software to build the estimation algorithm. From the research that has been done, the results of the Extended Kalman Filter Estimator have a steady state RMSE of less than 5% with the lowest steady state RMSE at 650 rpm, which is 0.637%. While the results of the Disturbance Observer Estimator to estimate the speed have a steady state RMSE of less than 5% with the lowest steady state RMSE at 350 rpm, which is 0.979%. As for the comparison of the two algorithms in the same speed estimation, it is found that the speed estimation using the disturbance observer has a smaller RMSE error but has an estimated overshoot error at the beginning of the estimation response. In the speed change test, it can be seen that both the real-time estimator based on the Extended Kalman filter and the Disturbance observer can follow changes in speed.
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