ILLUMINATION CONTROL USING FUZZY LOGIC
description
Transcript of ILLUMINATION CONTROL USING FUZZY LOGIC
![Page 1: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/1.jpg)
ILLUMINATION CONTROL USINGFUZZY LOGIC
PRESENTED BY: VIVEK RAUNAK reg:
13090260
![Page 2: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/2.jpg)
CONTENTS• INTRODUCTION OF FUZZY LOGIC• HISTORIC BACKGROUND• ILLUMINATION CONTROL SYSTEM• ARCHITECTURE OF FLC• DESIGN STEPS OF FLC• HARDWARE DESCRIPTION • ADVANTAGE OF FLC• DISADVANTAGE OF FLC• APPLICATION OF ILLUMINATION CONTROL SYSTEM• CONCLUSION
![Page 3: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/3.jpg)
INTRODUCTIONHUMAN LIKE THINKING
“THINKING”……………… * DIGITAL LOGIC * FUZZY LOGIC
DIGITAL LOGIC: 0 OR 1 (Y OR N)FUZZY LOGIC: [0,1]
![Page 4: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/4.jpg)
HISTORIC BACKGROUND
LOTFI ZADEH
• Fuzzy logic was born in 1965 father of fuzzy logic –
LOTFI ZADEHFristly used in control system
in 1974 by - EBRAHAM MAMDANI • The international fuzzy system
association (IFSA) was established in 1984
• It is too much famous in japan. laboratory of international fuzzy engineering (LIFE) was
inaugurated in 1989.
![Page 5: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/5.jpg)
ARCHITECTURE OF FLC
![Page 6: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/6.jpg)
DESIGN OF FLCCLASSIFICATION AND SCALING
OF INPUT(FUZZY PLANE)
FUZZIFICATION
RULE FORMATION
RULE FIRING
DEFUZZIFICZTION
![Page 7: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/7.jpg)
CLASSIFICATION AND SCALING OF INPUT input error = set point –
actual
Change in error = pre error - current error
Ep=(error / setpoint)100
∆Ep =(change in error / pre. error ) 100
![Page 8: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/8.jpg)
DYNAMIC RANGE Ep [-100,100] ; ∆Ep [-
100,100] Z [0,100];
LINGUAL VARIABLE Fuzzy variable are called lingual
variable. It may have infinite no. of values, each value is
associated with distinct membership value.
![Page 9: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/9.jpg)
LINGUAL VARIABLES Input Output NB -Negative Big DK -DarkNM -Negative Medium ST -StreakNS -Negative Small SP -SparkZE -ZeroM -MinimumPS -Positive Small MD -mediumPM -Positive Medium H -High
BrightnessPB -Positive Big VH-Very High
Brightness
![Page 10: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/10.jpg)
RANGES OF LINGUAL VARIABLE
Input lingual rangeNB -100 - -45NS -90 - 0
ZE -45 - 45PS 0 - 90 PB 45 - 100
output lingual rangeVH 0 - 35HI 20 - 50MD 35 - 65M 50 - 80DK 65 - 100
![Page 11: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/11.jpg)
Membership function• It is function through which we get membership
value of the element of lingual variable. Ranges from 0 to 1. types…TriangularGaussion functionϒ function S function
Generally trianguler membershipfunction is used.
![Page 12: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/12.jpg)
FUZZY PLANE
![Page 13: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/13.jpg)
FUZZIFICATION It is process to change crisp input into fuzzy
input.
![Page 14: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/14.jpg)
Rule formation “if(A=x) then (z=y)” antecedent conclusion
Rule formation needs knowledge and experiment.
4 rules in single iterationIf (l1 = x1 AND l3 = y1) then U = Z1
If (l1 = x1 AND l4 = y2) then U = Z2
If (l2 = x2 AND l3 = y1) then U = Z3
If (l2 = x2 AND l4 = y2) then U = Z4
![Page 15: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/15.jpg)
Rule matrix•For the given input the lingual variable in which output will lie is determined by knowledge and experience.•Total 49 possible rule
![Page 16: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/16.jpg)
Rule firing•Rule firing mean…to apply the pre-determined rule to get the output.There are many methods for rule firingMinimum compositionProduct of maximum compositionMaximum of minimum compositionMinimum of minimum compositionMaximum of maximum composition
•We use max-min composition for inferring output.
![Page 17: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/17.jpg)
Max-min composition
![Page 18: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/18.jpg)
DefuzzificationIt is process to convert fuzzy output into
crisp output.Various method:Centre of gravity defuzzificationCentre of sums defuzzificationCentre of largest area defuzzificationFirst of maxima defuzzificationMiddle of maxima defuzzificationHeight defuzzification
![Page 19: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/19.jpg)
COG most commonly used defuzzification method.
COG = ∫zµdz ∫µdz
![Page 20: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/20.jpg)
Hardware description
![Page 21: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/21.jpg)
ADVANTAGES OF FLCHumen like thinkingEfficient design for non-linear control systemCheaperReduces tedious mathematical calculationReliable
DISADVANTAGES
FORMATION OF RULE IS VERY TEDIOUS
OBEYS NEW LOGIC
![Page 22: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/22.jpg)
APPLICATION OF ILLUMINATION CONTROLLERsensitive photosynthesis LCD brightness controlStreet lightAutomatic room light control
![Page 23: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/23.jpg)
CONCLUSIONThe Presentation aimed towards fuzzy logic
control system. we saw all aspects of FLC by taking a control system used for illumination control. Illumination control system controls the environment wherevere unpredictable change in illumination is expected.
![Page 24: ILLUMINATION CONTROL USING FUZZY LOGIC](https://reader035.fdocuments.us/reader035/viewer/2022062310/56816335550346895dd3bf46/html5/thumbnails/24.jpg)