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Abstract
Artificial intelligence has been implemented widely. Many of household products are designed based on artificial intellegence concept. One of them is fuzzy logic system. This paper describes on how a fuzzy logic system can also be implemented in controling the speed of a car in the road.
The fuzzy inference system was designed according to Tsukamoto inferencing method and for the defuzzyfication method is used weighted average method. There are three inputs for the system. The are distance between controled car and the car infront of the controled car, distance between controled car and turning point in front of the car and the last is the current speed of the controled car. The output of the system is the next speed of the controled car. For every inputs, three predicates fuzzy are used. Therefore, there are 27 ruler of inference.
From the experiment, it can be concluded that the system works well. The performance of the system closely relates with the membership function of each variabel.
Keywords: Fuzzy logic, Fuzzy inference, Defuzzyfication
The fuzzy inference system was designed according to Tsukamoto inferencing method and for the defuzzyfication method is used weighted average method. There are three inputs for the system. The are distance between controled car and the car infront of the controled car, distance between controled car and turning point in front of the car and the last is the current speed of the controled car. The output of the system is the next speed of the controled car. For every inputs, three predicates fuzzy are used. Therefore, there are 27 ruler of inference.
From the experiment, it can be concluded that the system works well. The performance of the system closely relates with the membership function of each variabel.
Keywords: Fuzzy logic, Fuzzy inference, Defuzzyfication