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ITS » Research Report » Teknik Fisika S1
Posted by dwi at 14/01/2008 18:01:16  •  20178 Views


PERANCANGAN KONTROLER LOGIKA FUZZY DENGAN METODE INPUT DAN OUTPUT MAPPING FAKTOR STUDI KASUS MODEL MESIN OTOMOTIF

Author :
Aulia Siti A. 




ABSTRAK

Perkembangan kontrol dengan berdasar logika fuzzy mulai diterapkan dalam berbagai industri dan salah satunya dalam sistim kontrol kecepatan idle mesin engine. Suatu metode diajukan disini untuk merancang sistim kontrol dengan dua masukan yaitu eror dan delta eror yang membentuk PID Fuzzy Proporsioal Integral dan Integral Fuzzy. Dengan perbaikan dalam hal kuantisasi terhadap dua masukan tersebut dan outputnya yaitu kuantisasi secara eksponensial yang dikenal sebagai Input Output Mapping Faktor. Strategi ini diterapkan pada sistim nonlinier dengan menggunakan paradigma kontrol intelegent secara langsung dengan tujuan untuk memperoleh maximum benefit manfaat maximal yaitu suatu sistim pengendalian yang dinamis mampu melakukan pembelajaran serta tetap menjaga kestabilan dan robustness sistem. PID Fuzzy dengan Input Output Mapping Factor IOMF sebagai suatu FLC Fuzzy Logic Controller yang tersusun atas komponen Knowledge Base Fuzzifikasi dan Defuzzifikasi dimana masing masing komponen terbentuk dari keanggotaan variabel eror dan perubahan eror dengan fungsi keanggotaan adalah segitiga dan tujuh set fuzzy yaitu NB negative Big NM Negative Medium NS Negative Small ZE Zero PS Positive Small PM Positive Medium dan PB Positive Big. Fuzzifikasi berfungsi merubah variabel terukur menjadi variabel fuzzy sedang dalam Knowledge Base tersusun atas Basis Data dan Basis Aturan yang berisi set fuzzy dari variabel kontrol dan kumpulan aturan-aturan kontrol yang berlaku dan Defuzzifikasi merupakan proses balik yang memetakan dari ruang inferensi fuzzy ke ruang non fuzzy berupa sinyal kontrol yang diumpankan ke plant. Perancangan FLC dengan pasangan variabel kontrol dan variabel termanipulasi yang terbaik adalah kecepatan putar N dengan bukaan throtel 6 dan tekanan manifold dengan derajad sudut engkol 8 dengan perancangan Knowledge base dengan variabel input eror e dan perubahan eror de dibagi dalan tujuh set fuzzy strategi defuzzifikasi dengan metode COA center of area. Selanjutnya dengan FLC IOMF yang dirancang dilakukan simulasi dengan berbagai kondisi. Yang pertama dengan dibandingkan terhadap penelitian terdahulu diperoleh parameter yang lebih baik pada Total Distance Square Laju Konvergensi dan Error Steady State. Dari kondisi perubahan torsi beban diperoleh settling time untuk besaran laju aliran udara laju aliran bahan bakar rasio udara - bahan bakar tekanan manifold kurang dari 01 detik. Simulasi selanjutnya digunakan untuk kerobustan dari system dengan melakukan uji perubahan parameter system. Hasil simulasi menunjukkan besarnya error maksimum 5 dengan settling time untuk berbagai uji kurang dari 30 detik.


ABSTRACT

The development of fuzzy control engineering is applied in many field of industry and one of them is control strategy idle speed engine. This research proposes one method in order to design control system which has two inputs which are error and delta error which form PID Fuzzy controller Proportional - integral and derivative. The enhancement of the quantifying exponentially named as Input Output Mapping Factor. This strategy is applied in nonlinear system using an intelligent direct control paradigm with the purpose of achieving maximum benefit that is a stable and robust dynamic control system. PID Fuzzy with Input output mapping factor IOMF as a Fuzzy Logic Controller which is composed of Knowledge Base Fuzzification and defuzzification components in which each component is formed from a set of error and delta error variables and the set function are triangle and seventh set of fuzzy such as NB negative Big NM Negative Medium NS Negative Small ZE Zero PS Positive Small PM Positive Medium and PB Positive Big. The function of the Fuzzification is to change the measured variable into fuzzy variable whereas Knowledge base consists of data Base and rule base in which there are control variable and a set of control rules. Defuzzification is a reversed process which maps from inference fuzzy space to non fuzzy space in form of control signal send to the plant. FLC design which the best pair of control variable and manipulated control are radial speed N and throttle 0 and the manifold pressure P crankshaft angle5 with the design of knowledge base with variable input error and delta error divide into seventh fuzzy set the defuzzification strategy is using COA center of area method. The simulation of the designing FLC IOMF is performed in various conditions. The first simulation is done by comparing the previous research then obtained better parameter in Total distance square rate of convergence and error steady state. From the condition of the difference of load torque it is found settling time less than 0.1 second for air mass flow fuel flow ratio air - fuel manifold pressure. Further simulation is used to examine the system robustness that is by parameter change test. The result of the simulation shows that the maximum error 5 and the settling time for all testing are less than 30 seconds.



KeywordsLogika fuzzy
 
Subject:  Otomasi
Date Create: 14/01/2008
Type: Text
Format: pdf ; 54 pages
Language: Indonesian
Identifier: ITS-Research-3100005066008
Collection ID: 3100005066008
Call Number: ITS 629.801 511 313 Aul p


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