I realise that the difference lies in the way the defuzzification happens but I don't fully understand it. I've read some papers comparing the outputs from the two models but I'm still not really sure how they are different.
What is the difference between mamdani and sugeno in fuzzy logic?
3
$\begingroup$
fuzzy-logic
3 Answers
2
These are the primary differences between Mandani FIS and Sugeno FIS:
Mamdani FIS
- Output membership function is present
- Crisp result is obtained through defuzzification of rules’ consequent
- Non-continuous output surface
- MISO (Multiple Input Single Output) and MIMO (Multiple Input Multiple Output) systems
- Expressive power and Interpretable rule consequents
- Less flexibility in system design
Sugeno FIS
- No output membership function is present
- No defuzzification: crisp result is obtained using weighted average of the rules’ consequent
- Continuous output surface
- Only MISO systems
- Loss of interpretability
- More flexibility in system design
3
Mamdani- It entails a substantial computational burden. Sugeno - It is computationally efficient. Mamdani- It is well suited to human input. Sugeno- It its well suited to mathematically analysis.
-
0Thanks, been watching this for a while and no-one summarized it quite so succinctly. – 2015-12-09
2
Mamdani type fuzzy inference gives an output that is a fuzzy set. Sugeno-type inference gives an output that is either constant or a linear (weighted) mathematical expression.
e.g Mamdani: If A is X1, and B is X2, then C is X3. (X1, X2, X3 are fuzzy sets).
Sugeno: If A is X1 and B is X2 then C = ax1 + bx2 + c (linear expression) (a,b,and c are constants)
-
0For some basic information about writing math at this site see e.g. [here](http://meta.math.stackexchange.com/questions/5020/), [here](http://meta.stackexchange.com/a/70559/155238), [here](http://meta.math.stackexchange.com/questions/1773/) and [here](http://math.stackexchange.com/help/notation). – 2013-12-28