Main Content


Tunable parameter settings for fuzzy membership functions

Since R2019a


A MembershipFunctionSettings object contains tunable parameter settings for a type-1 membership function. Using this object, you can specify the tunability settings for the parameters of the corresponding membership function.

For more information on the tunable settings of a type-2 membership function, see MembershipFunctionSettingsType2.


Create MembershipFunctionSettings objects using the getTunableSettings function with a mamfis, sugfis, or fistree object. The first and second outputs of getTunableSettings contain VariableSettings objects for input and output variables, respectively. If a VariableSettings object corresponds to a variable with type-1 membership functions, then its MembershipFunctions property contains MembershipFunctionSettings objects.


expand all

Membership function parameter tunable settings, specified as a NumericParameters object.

Object Functions

setTunableSet specified parameter settings as tunable or nontunable


collapse all

Create a fuzzy inference system.

fis1 = mamfis('Name','fis1','NumInputs',2,'NumOutputs',1);

Obtain the tunable settings of input and output variables of the fuzzy inference system.

[in,out] = getTunableSettings(fis1);

You can use dot notation to specify the tunable settings of input and output variables.

For the first membership function of input 1, set the first and third parameters to tunable.

in(1).MembershipFunctions(1).Parameters.Free = [1 0 1];

For the first membership function of input 2, set the minimum parameter range to 0.

in(2).MembershipFunctions(1).Parameters.Minimum = 0;

For the first membership function of the output variable, set the maximum parameter range to 1.

out(1).MembershipFunctions(1).Parameters.Maximum = 1;

Version History

Introduced in R2019a