Rancang Bangun Sistem Kontrol Kecepatan Motor DC Sumber Daya Terpisah untuk Sistem Penggerak Roda Mobil Cerdas (ICAR ITS)

Muhammad Shah, Yaqzhan Elkiya (2023) Rancang Bangun Sistem Kontrol Kecepatan Motor DC Sumber Daya Terpisah untuk Sistem Penggerak Roda Mobil Cerdas (ICAR ITS). Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Intelligent CAR (iCAR) ITS adalah prototipe mobil otonom ITS yang menggunakan motor listrik sumber daya terpisah sebagai motor penggeraknya. Performa dari kecepatan motor DC sumber daya terpisah sendiri dipengaruhi oleh keandalan system dan keandalan program. Namun, implementasi dari sistem saat ini masih belum mencapai performa yang stabil. Karena dalam fase pemakaian, sering terjadi perjalanan yang tidak mulus dan respon yang lambat terutama ketika terjadi perubahan beban. Tujuan yang dikemukakan dalam proposal ini ialah mengoptimalkan kestabilan kecepatan pada mobil iCAR ITS dan
meningkatkan pengaturan kontrol motor yang bergantung pada tingkat beban mobil iCAR ITS.
Solusi yang ditawarkan ialah menggunakan metode PID. Untuk mentukan Kp, Ki, dan Kd, digunakan pula algoritma Neural Network PID sebagai algoritma penyokong. Sistem juga dibuat closed loop dengan memasang rotary encoder sehingga dapat melakukan kontrol kecepatan mobil cerdas iCAR ITS berdasarkan feedback melalui rotary encoder. Dalam penelitian ini, dibandingkan empat algoritma antara lain ialah tanpa PID, PID, Neural Network, dan PIDNN. Hasil dari penelitian ini baik di simulasi maupun implementasi adalah
algoritma PID dapat menstabilkan kecepatan motor meskipun masih memiliki overshoot yang relatif tinggi. Algoritma PIDNN dapat menjadikan kecepatan motor lebih stabil dan lebih adaptif daripada PID sehingga nilai overshoot dan rise time lebih rendah. Algoritma neural network dapat membuat kecepatan motor lebih stabil dan lebih adaptif daripada PIDNN pada semua case kecuali case dua. Namun, algoritma neural network memiliki nilai rise time yang lebih tinggi daripada PIDNN. Saran dari penelitian ini ialah menggunakan neuro-fuzzy, memperbaiki data training untuk neural network, dan menambah sensor beban pada ICAR ITS

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intelligent CAR (iCAR) ITS is an ITS autonomous car prototype that use separately excited DC motor. performance of separately excited DC motor is affected by system reliability and program algorithm. But the implementation by the system nowadays does not reach the stabile performance because it happens often that the travel of iCAR ITS is not smooth and the response is tend to be slow especially when there is a change in car load. The purpose of this research is to optimize stability of iCAR ITS velocity and increase motor control system respecting carload variable. The Solution offered is using PID method. to obtaine value of Kp, Ki, and Kd, here impelemented also Neural Network PID as supportive algorithm. Control system is also designed to two variables. the variables are separately excited DC motor
control and brake mechanism control. the system is also designed closed loop by assembling rotary encoder so the iCAR ITS velocity can be controlled based on feedback from rotary encoder. This research compares four algorithms. Those are closed loop, PID, neural network, and PIDNN. The result of this research both in simulation and implementation is PID algorithm can stabilize speed of motor so that overshoot and rise time value can be decreased.
The PIDNN algorithm can make the speed of motor more stable and more adaptive than PID so it reduces the overshoot and rise time lower than PID output. The neural network algorithm can make the speed of motor more stable and adaptive than PIDNN almost in all case except case two. But, the output of neural network algorithm has the rise time value higher than PIDNN. The advice of this research is to develop with neuro-fuzzy algorithm, improving training data in neural network, and adding load sensor on ICAR ITS.
Keywords: Separately Excited DC Motor, PID, Neural Network, Autonomous Car.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Motor DC Sumber Daya Terpisah, PID, Neural Network, Mobil Otonom, Separately Excited DC Motor, PID, Neural Network, Autonomous Car.
Subjects:	T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2681.B47 Electric motors, Direct current. T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK2785 Electric motors, Induction. T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3070 Automatic control T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK4055 Electric motor
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User:	Yaqzhan Elkiya Muhammad Shah
Date Deposited:	26 Jul 2023 03:45
Last Modified:	26 Jul 2023 03:45
URI:	http://repository.its.ac.id/id/eprint/99159

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