Lukito, Rian (2015) Perancangan Kontroler Neuro-Fuzzy Untuk Electromagnetic Anti-Lock Braking System (ABS) Pada Kendaraan Listrik. Undergraduate thesis, Institut Technology Sepuluh Nopember.
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Abstract
Anti-lock braking system (ABS) digunakan pada kendaraan untuk
menjaga agar roda tidak terkunci saat pengereman mendadak
(pengereman dalam) dan meminimalkan jarak berhenti kendaraan.
Permasalahan yang terjadi saat pengereman mendadak adalah roda
terkunci sehingga steering kendaraan tidak dapat dikendalikan. Sistem
ABS yang dirancang akan diterapkan pada simulator ABS dengan
menggunakan pengereman elektromagnetik. Dalam kondisi normal atau
dalam keadaan tanpa pengereman, kecepatan longitudinal kendaraan
akan sama dengan kecepatan putaran roda sehingga slip ratio bernilai 0
(0%)dan apabila kecepatan putaran roda bernilai 0 (dalam keadaan
terkunci) maka roda bernilai slip 1 (100%). Sistem ABS akan menjaga
agar nilai rasio slip berada di nilai 0,2 (20%). Pada tugas akhir ini
digunakan metode neuro-fuzzy untuk mengontrol nilai slip pada roda.
Masukkannya adalah slip yang diharapkan dan keluarannya adalah slip
dari plant. Algoritma learning yg digunakan adalah BackPropagation
yang akan bekerja secara feedforward untuk mendapatkan ouput aktual
dan bekerja secara feedback setelah mendapatkan nilai error dengan
output target. Jaringan yang dibuat berdasarkan mekanisme fuzzy yakni
fuzzifikasi, inferensi dan defuzzifikasi. Kontroler neuro-fuzzy dapat
mengurangi overshoot respon plant hingga 43,2% dibandingkan respon
plant tanpa kontroler secara loop terbuka.
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Anti-lock braking system (ABS) is used on the vehicle to keep the wheels
are not locked during sudden braking (braking in) and minimize the
distance termination. Problems that occur when sudden braking is locked
so that the will be oversteering. ABS system will be applied using
electromagnetic braking on the wheels of ABS simulator. Under normal
conditions, the vehicle longitudinal speed will be the same as the rotation
speed of the wheel so that the slip ratio is 0 (0%) and when the wheel
rotation speed is 0 (locked), the wheel slip ratio is 1 (100%). ABS system
will keep the value of the slip ratio is at a value of 0.2 (20%). Neuro-Fuzzy
method used to control the value of the wheel slip ratio in my final
project. Slip ratio input is expected and output is the slip ratio of the plant.
Learning algorithms use Back Propagation which will work to get the
actual output with feedforward and feedback work after getting the error
value with a target output. Network created by the fuzzy mechanism
fuzzification, inference and defuzzification. Neuro-Fuzzy controller can
reduced overshoot of plant response until 43.2% than plant response
without controller in open loop system.
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSE 629.831 2 Luk p |
| Uncontrolled Keywords: | ABS, BackPropagation, Neuro-Fuzzy, Simulator ABS |
| Subjects: | Q Science > QA Mathematics > QA9.64 Fuzzy logic T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL257.5 Automobiles--Shock absorbers--Design and construction. |
| Divisions: | Faculty of Electrical Technology > Electrical Engineering > 20201-(S1) Undergraduate Thesis |
| Depositing User: | Mr. Tondo Indra Nyata |
| Date Deposited: | 01 Oct 2019 04:39 |
| Last Modified: | 01 Oct 2019 04:39 |
| URI: | http://repository.its.ac.id/id/eprint/70929 |
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