In classical set theory there is two options for an element. It is either a member of a set, or not. But in fuzzy set theory there are membership functions to define rate of an element being a member of a set. In other words, classical logic says it is all black or white, but fuzzy logic offers that there is also grey which has shades between white and black.Matlab Simulink Library is very easy to design and helpful in practice. And it has good examples on its own like deciding about tip for a dinner looking at service and food quality. In the figure below some various membership functions from Matlab's library are shown:My question: How do we decide about choosing membership functions while designing a fuzzy controller system? I mean in general, not only in Matlab Simulink. I have seen Triangular and Gaussian functions are used mostly in practise, but how can we decide which function will give a better result for decision making? Do we need to train a neural network to decide which function is better depending on problem and its rules? What are other solutions?
Fuzzy Logic Controller: Choosing Membership Function
neural networks;fuzzy logic