Andreas Surya, Andreas
Jurusan Teknik Elektro, Fakultas Teknik, Universitas Diponegoro, Jalan Prof. Sudharto, SH, Kampus UNDIP Tembalang, Semarang 50275, Indonesia

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DESAIN KONTROLER GENETIC-FUZZY PADA MODEL AUTOMATIC-ANTILOCK BRAKING SYSTEM Surya, Andreas; Triwiyatno, Aris; Setiyono, Budi
Transmisi Vol 17, No 3 Juli (2015): TRANSMISI
Publisher : Departemen Teknik Elektro, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (553.842 KB) | DOI: 10.12777/transmisi.17.3.113-121

Abstract

Abstrak   Automatic Antilock Braking System menawarkan sebuah solusi pilihan dibidang system keamanan pengereman kendaraan, khususnya mobil, untuk melakukan pengereman secara otomatis. Automatic antilock braking system mengukur slip roda sebagai variabel dikontrol dan torsi rem sebagai variable dimanipulasi. Dalam penelitian ini, didesain kontroler Genetic-Fuzzy untuk menjaga slip sesuai ratio slip referensi. Algoritma genetika diaplikasikan untuk mengoptimasi parameter himpunan keanggotaan fuzzy. Pengujian kondisi aspal kering, kontroler Genetic-Fuzzy berhasil mencapai  pemberhentian sempurna pada jarak 15,52 m dan IAE sebesar 0,095, sedangkan kontroler Fuzzy mencapai pemberhentian  pada jarak 15,45 m dan IAE sebesar 0,099. Pengujian kondisi aspal basah, kontroler Genetic-Fuzzy berhasil mencapai  pemberhentian pada jarak 17,46 m dan IAE sebesar 0,0806, sedangkan kontroler Fuzzy mencapai pemberhentian pada jarak 17,39 m dan IAE sebesar 0,0802. Abstract   The Automatic Antilock Braking System offers an optional solution in vehicle safety braking system, particularly cars to brake automatically. Automatic antilock braking system works to measure wheel slip as controlled variable and applies braking torque as manipulated variable. In this final assignment, Genetic-Fuzzy controller has been designed to maintain measured wheel slip fit to the reference slip. Genetic algoritm was applied to optimize a membership function parameter of fuzzy. In dry asphalt simulation, Genetic-Fuzzy  controller has succeed to achieve perfect stoppage distance by 15,52 m and IAE value of 0,095, whereas the fuzzy controller achieved stoppage distance by 15,45 m and IAE value of 0,099. In wet asphalt simulation, Genetic-Fuzzy  controller achieved stoppage distance by 17,46 m and IAE value of 0,0806, whereas the fuzzy achieved stoppage distance by 17,39m and IAE value of 0,0802.   Keywords: Genetic Fuzzy, Genetic Algoritm, Fuzzy, Automatic Antilock Braking System