Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL...
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Transcript of Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL...
![Page 1: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/1.jpg)
Lecture 12
Introduction to Neural Networksand Fuzzy Logic
President University Erwin Sitompul NNFL 12/1
Dr.-Ing. Erwin SitompulPresident University
http://zitompul.wordpress.com
2 0 1 3
![Page 2: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/2.jpg)
President University Erwin Sitompul NNFL 12/2
Solution: Homework 8Fuzzy ControlFuzzy Logic
![Page 3: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/3.jpg)
President University Erwin Sitompul NNFL 12/3
FC with 5 Rules
Solution: Homework 8 (Cont.)Fuzzy ControlFuzzy Logic
Rule 1: IF level is okay, THEN valve is no change.Rule 2: IF level is low, THEN valve is open fast.Rule 3: IF level is high, THEN valve is close fast.Rule 4: IF level is okay AND rate is negative,
THEN valve is open slow.Rule 5: IF level is okay AND rate is positive,
THEN valve is close slow.
Rule 1: IF error is zero, THEN valve is no change.Rule 2: IF error is positive,THEN valve is open fast.Rule 3: IF error is negative,THEN valve is close fast.Rule 4: IF error is zero AND error rate is positive,
THEN valve is open slow.Rule 5: IF error is zero AND error rate is negative,
THEN valve is close slow.
error = reference – levelrate of error = – rate of level
![Page 4: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/4.jpg)
President University Erwin Sitompul NNFL 12/4
Solution: Homework 8 (Cont.)Fuzzy ControlFuzzy Logic
Valve control signal [%/s]
no
chan
ge
ope
n fa
st
clos
e fa
st
–30 –20 –10 0 10 20 30
1 o
pen
slow
clos
e slow
Rate of level error [cm/s]
zero positivenegative
–4 –0.5 0 0.5 4
1
Level error [cm]
zero positivenegative
–5 –4 0 4 5
1
1st Set of Membership Functions
![Page 5: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/5.jpg)
President University Erwin Sitompul NNFL 12/5
Solution: Homework 8 (Cont.)Fuzzy ControlFuzzy Logic
![Page 6: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/6.jpg)
President University Erwin Sitompul NNFL 12/6
Solution: Homework 8 (Cont.)Fuzzy ControlFuzzy Logic
Level error [cm]
zero positivenegative
–5 1 0 1 5
1
2nd Set of Membership Functions
Valve control signal [%/s]
no
chan
ge
ope
n fa
st
clos
e fa
st
–30 –20 –10 0 10 20 30
1 o
pen
slow
clos
e slow
Rate of level error [cm/s]
zero positivenegative
–4 –0.5 0 0.5 4
1
![Page 7: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/7.jpg)
President University Erwin Sitompul NNFL 12/7
Solution: Homework 8 (Cont.)Fuzzy ControlFuzzy Logic
![Page 8: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/8.jpg)
President University Erwin Sitompul NNFL 12/8
Solution: Homework 8 (Cont.)Fuzzy ControlFuzzy Logic
Level error [cm]
zero positivenegative
–10 –4 0 4 10
1
3rd Set of Membership Functions
Valve control signal [%/s]
no
chan
ge
ope
n fa
st
clos
e fa
st
–30 –20 –10 0 10 20 30
1 o
pen
slow
clos
e slow
Rate of level error [cm/s]
zero positivenegative
–4 –0.5 0 0.5 4
1
![Page 9: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/9.jpg)
President University Erwin Sitompul NNFL 12/9
Solution: Homework 8 (Cont.)Fuzzy ControlFuzzy Logic
![Page 10: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/10.jpg)
President University Erwin Sitompul NNFL 12/10
PID-like Fuzzy Controllers
Fuzzy P Controller
u+–
e r y
Fuzzy ControlFuzzy Logic
![Page 11: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/11.jpg)
President University Erwin Sitompul NNFL 12/11
PID-like Fuzzy Controllers
Fuzzy PD Controller
u+–
e ry
Fuzzy ControlFuzzy Logic
![Page 12: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/12.jpg)
President University Erwin Sitompul NNFL 12/12
PID-like Fuzzy Controllers
Fuzzy PID Controller
ue r y+–
• Weakness: too many rules
Fuzzy ControlFuzzy Logic
![Page 13: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/13.jpg)
President University Erwin Sitompul NNFL 12/13
PID-like Fuzzy Controllers
Fuzzy PD+I Controller
r+–
eyDu
Fuzzy ControlFuzzy Logic
![Page 14: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/14.jpg)
President University Erwin Sitompul NNFL 12/14
PID-like Fuzzy Controllers
r u+–
e y++
Du
Fuzzy PD+I Controller
Fuzzy ControlFuzzy Logic
![Page 15: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/15.jpg)
President University Erwin Sitompul NNFL 12/15
PID-like Fuzzy Controllers
Fuzzy PD+I Controller
r u+–
e y++
Fuzzy ControlFuzzy Logic
![Page 16: Lecture 12 Introduction to Neural Networks and Fuzzy Logic President UniversityErwin SitompulNNFL 12/1 Dr.-Ing. Erwin Sitompul President University .](https://reader036.fdocuments.us/reader036/viewer/2022071710/56649dbc5503460f94aaef09/html5/thumbnails/16.jpg)
President University Erwin Sitompul NNFL 12/16
End of the LectureFuzzy ControlFuzzy Logic