What Is Fuzzy Logic?

Working from the Command Line
Specifying Custom Membership and Inference Functions
You can create custom membership and inference functions as described in
“Specifying Custom Membership Functions” on page 2-60, and “Specifying
Custom Inference Functions” on page 2-66, and specify them for building
fuzzy inference systems at the command line.
To include a custom membership function, specify the name of the custom
membership function, as shown in the following example:
a=addmf(a,'input',1,'customMF1','custmf1',[0 1 2 4 6 8 9 10]);
To include a custom inference function, specify the name of the custom
inference function, as shown in the following example:
a.defuzzMethod='customdefuzz';
FIS Evaluation
To evaluate the output of a fuzzy system for a given input, use the function
evalfis. For example, the following script evaluates tipper at the input,
[1 2].
a = readfis('tipper');
evalfis([1 2], a)
ans =
5.5586
This function can also be used for multiple collections of inputs, because
different input vectors are represented in different parts of the input
structure.
evalfis([3 5; 2 7], a)
ans =
12.2184
7.7885
The FIS Structure
The FIS structure is the MATLAB object that contains all the fuzzy inference
system information. This structure is stored inside each GUI tool. Access
functions such as getfis and setfis make it easy to examine this structure.
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