1.W: Consider about a washing machine equipped with fuzzy logic controller. There are two inputs applied in the machine and one output. The first input is amount of clothes and the second input is type of dirt. The rules applied in the system is shown below: 1.IF amount of clothes is LARGE and type of dirt is GREASY THEN wash time is LONG; 2.IF amount of clothes is MEDIUM and type of dirt is MEDIUM THEN wash time is MEDIUM; 3.IF amount of clothes is SMALL THEN wash time is SHORT. The membership of each input is as shown in Figure 1. The output of the system is as shown in Figure 2. If you have a 4.5 kg of cloths to be washed, and your clothes are in level 3 of greasiness, then calculate the washing time needed using Mamdani style inference. ·XX-X 1-XX IX-X 0.5 0.5 Not medium greasy small medium large greasy Short medium Long O 1 2 3 4 5 6 02 4 6 8 10 Level of greasiness 10 20 30 40 50 60 Dirty cloths, kg Washing time, minutes (₂) (b) Degree of Membership
1.W: Consider about a washing machine equipped with fuzzy logic controller. There are two inputs applied in the machine and one output. The first input is amount of clothes and the second input is type of dirt. The rules applied in the system is shown below: 1.IF amount of clothes is LARGE and type of dirt is GREASY THEN wash time is LONG; 2.IF amount of clothes is MEDIUM and type of dirt is MEDIUM THEN wash time is MEDIUM; 3.IF amount of clothes is SMALL THEN wash time is SHORT. The membership of each input is as shown in Figure 1. The output of the system is as shown in Figure 2. If you have a 4.5 kg of cloths to be washed, and your clothes are in level 3 of greasiness, then calculate the washing time needed using Mamdani style inference. ·XX-X 1-XX IX-X 0.5 0.5 Not medium greasy small medium large greasy Short medium Long O 1 2 3 4 5 6 02 4 6 8 10 Level of greasiness 10 20 30 40 50 60 Dirty cloths, kg Washing time, minutes (₂) (b) Degree of Membership
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
Transcribed Image Text:H.W: Consider about a washing machine equipped with fuzzy logic controller. There are two inputs applied in the machine and
one output. The first input is amount of clothes and the second input is type of dirt. The rules applied in the system is shown
1.IF amount of clothes is LARGE and type of dirt is GREASY THEN wash time is LONG;
below:
2.IF amount of clothes is MEDIUM and type of dirt is MEDIUM THEN wash time is MEDIUM;
3.IF amount of clothes is SMALL THEN wash time is SHORT.
The membership of each input is as shown in Figure 1. The output of the system is as shown in Figure 2. If you have a 4.5 kg
of cloths to be washed, and your clothes are in level 3 of greasiness, then calculate the washing time needed using
Mamdani style inference.
FXX XX XX
0.5
0.5
0.5
Not
medium greasy
small
medium
large
greasy
Short V
medium
O
1
2
3
4
5
6
2
4
6 8 10
Level of greasiness
Dirty cloths, kg
60
Washing time, minutes
(a)
(b)
Figure 1 Input of the system (a) dirty clothes (b) level of greasiness
Figure 2: Output, washing time
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