Download presentation

Presentation is loading. Please wait.

Published byKirk Privott Modified about 1 year ago

1
Introduction to Fuzzy Control Lecture 10.1 Appendix E

2
Fuzzy Control Fuzzy Sets Design of a Fuzzy Controller –Fuzzification of inputs: get_inputs() –Fuzzy Inference –Centroid Defuzzification

3
Fuzzy Logic

4
Normal “Crisp” logic where everything must be either True or False leads to PARADOXES

5
The sentence on the other side of the line is false The sentence on the other side of the line is false

6
A barber has a sign that reads: “I shave everyone who does not shave himself” Who shaves the barber?

7
Fuzzy Logic Lotfi Zadeh - Fuzzy Sets - 1965 Membership functions –Degree of membership between 0 and 1 Fuzzy logic operations on fuzzy sets A and B –NOT A => 1 - A –A AND B => MIN(A,B) –A OR B => MAX (A,B)

8
Membership Functions Young Age Not Young

9
Membership Functions Old Age Not Old

10
Membership Functions Age Not Old Not Young Middle Age = Not Old AND Not Young

11
Probabiltiy vs. Fuzziness Probability describes the uncertainty of an event occurrence. Fuzziness describes event ambiguity. Whether an event occurs is RANDOM. To what degree it occurs is FUZZY.

12
Probability: There is a 50% chance of an apple being in the refrigerator. Fuzzy: There is a half an apple in the refrigerator.

13
Fuzzy logic acknowledges and exploits the tolerance for uncertainty and imprecision.

14
Fuzzy Control Fuzzy Sets Design of a Fuzzy Controller –Fuzzification of inputs: get_inputs() –Fuzzy Inference –Centroid Defuzzification

15
Fuzzy Membership Functions

16
Fuzzy Control Map to Fuzzy Sets Fuzzy Rules IF A AND B THEN L * * Defuzzification Inputs Output get_inputs(); fire_rules(); find_output();

17
Algorithm for a fuzzy controller do_forever { get_inputs(); fire_rules(); find_output(); }

18
Fuzzy Control Fuzzy Sets Design of a Fuzzy Controller –Fuzzification of inputs: get_inputs() –Fuzzy Inference –Centroid Defuzzification

19
Fuzzification of inputs

20
get_inputs(); Given inputs x1 and x2, find the weight values associated with each input membership function. ZNMNSPSPM X1 0.2 0.7 W = [0, 0, 0.2, 0.7, 0]

21
Fuzzy Control Fuzzy Sets Design of a Fuzzy Controller –Fuzzification of inputs: get_inputs() –Fuzzy Inference –Centroid Defuzzification

22
Fuzzy Inference

24
Comparing the MAX rule and the SUM rule

25
Fuzzy Control Fuzzy Sets Design of a Fuzzy Controller –Fuzzification of inputs: get_inputs() –Fuzzy Inference –Centroid Defuzzification

Similar presentations

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google