getTunableSettings
Obtain tunable settings from fuzzy inference system
Syntax
Description
Examples
Obtain Tunable Settings from FIS
Create a fuzzy inference system.
fis1 = mamfis('Name','fis1','NumInputs',2,'NumOutputs',1);
Obtain the tunable settings of the inputs, outputs, and rules of the fuzzy inference system.
[in,out,rule] = getTunableSettings(fis1);
You can use dot notation to specify tunable settings.
For the first membership function of input 1:
Do not tune parameter 1.
Set the minimum ranges of the last two parameters to 0.
Set the maximum ranges of the last two parameters to 1.
in(1).MembershipFunctions(1).Parameters.Free(1) = false; in(1).MembershipFunctions(1).Parameters.Minimum(2:end) = 0; in(1).MembershipFunctions(1).Parameters.Maximum(2:end) = 1;
For the first rule:
Set the input 1 membership function index as nontunable.
Allow NOT logic for input 2 membership function index.
Do not ignore the output 1 membership function index.
rule(1).Antecedent.Free(1) = false; rule(1).Antecedent.AllowNot(2) = true; rule(1).Consequent.AllowEmpty(1) = false;
Obtain Tunable Settings of Input and Output Variables from FIS
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;
Obtain Tunable Settings for FIS Rules
Create a fuzzy inference system.
fis = mamfis("Name","fis1","NumInputs",2,"NumOutputs",1);
Obtain rule parameter settings from the FIS.
[~,~,rule] = getTunableSettings(fis);
Each rule parameter setting includes the FIS name, the index of the rule in the FIS, and parameter settings for the rule antecedent and consequent (the rule clauses). For each clause, you can specify the tunability settings.
View the default tunable settings for the antecedent of the first rule.
rule(1).Antecedent(1)
ans = ClauseParameters with properties: AllowNot: [0 0] AllowEmpty: [1 1] Free: [1 1]
You can use dot notation to specify the tunable settings for each rule.
Allow NOT logic in the antecedent of rule 1.
rule(1).Antecedent.AllowNot = true;
Make the consequent of rule 2 not available for tuning.
rule(2).Consequent.Free = 0;
Do not allow absence of a variable in the consequent of rule 3.
rule(3).Consequent.AllowEmpty = false;
Obtain Tunable Settings of Input and Output Variables from Type-2 FIS
Create a type-2 fuzzy inference system.
fis = mamfistype2('Name','fis1','NumInputs',2,'NumOutputs',1);
Obtain the tunable settings of the input and output variables of the fuzzy inference system.
[in,out] = getTunableSettings(fis);
You can use dot notation to specify the tunable settings of the membership functions of the input and output variables.
For the first membership function of input 1, set the first and third upper membership function parameters as tunable.
in(1).MembershipFunctions(1).UpperParameters.Free = [1 0 1];
For the first membership function of input 2, set the tunable range of the lower membership function scale to be between 0.7
and 0.9
.
in(2).MembershipFunctions(1).LowerScale.Minimum = 0.7; in(2).MembershipFunctions(1).LowerScale.Maximum = 0.9;
For the first membership function of output 1, set the tunable range of the lower membership function lag to be between 0.1
and 0.4
.
in(2).MembershipFunctions(1).LowerLag.Minimum = 0.1; in(2).MembershipFunctions(1).LowerLag.Maximum = 0.4;
By default, the tunable settings for a type-2 FIS produce symmetric lag results in the tuned system. To allow for asymmetric lag results, specify the AsymmetricLag
name-value argument.
[in2,out2] = getTunableSettings(fis,'AsymmetricLag',true);
Specify Tunability of Parameter Settings
Create a fuzzy inference system, and define the tunable parameter settings of inputs, outputs, and rules.
Create a FIS, and obtain its tunable settings.
fis = mamfis("NumInputs",2,"NumOutputs",2); [in,out,rule] = getTunableSettings(fis);
You can specify all the input variables, output variables, or rules as tunable or nontunable. For example, set all the output variable settings as nontunable.
out = setTunable(out,0);
You can set the tunability of individual variables or rules. For example, set the first input variable as nontunable.
in(1) = setTunable(in(1),0);
You can set individual membership functions as nontunable. For example, set the first membership function of input 2 as nontunable.
in(2).MembershipFunctions(1) = setTunable(in(2).MembershipFunctions(1),0);
You can also specify the tunability of a subset of variables or rules. For example, set the first two rules as nontunable.
rule(1:2) = setTunable(rule(1:2),0);
Obtain Tunable Settings for FIS Tree
Since R2023a
Create a FIS tree that contains three FIS objects.
fis1 = mamfis(Name="fis1",NumInputs=2,NumOutputs=1); fis2 = mamfis(Name="fis2",NumInputs=2,NumOutputs=1); fis3 = mamfis(Name="fis3",NumInputs=2,NumOutputs=1); connections = [ "fis1/output1" "fis3/input1"; "fis2/output1" "fis3/input2"]; fisT = fistree([fis1 fis2 fis3],connections);
You can obtain the tunable settings for all of the FIS objects in a FIS tree or any subset of FIS objects.
Obtain the tunable settings for all FIS objects in fisT
.
[in,out,rule] = getTunableSettings(fisT);
The settings objects in
, out
, and rule
contain variable and rule tunability settings for all FIS objects sorted alphabetically by FIS name.
Obtain the tunable settings for the variables and rules in fis3
.
[in3,out3,rule3] = getTunableSettings(fisT,FIS="fis3");
You can also obtain tunable settings for multiple FIS objects in a FIS tree. Obtain the tunable settings for the rules in fis1
and fis2
.
[~,~,rule12] = getTunableSettings(fisT,FIS=["fis1" "fis2"]);
When you specify tunable settings for a subset of the FIS objects in a FIS tree, the tunefis
function treats the remaining FIS objects as nontunable.
Input Arguments
fis
— Fuzzy inference system
mamfis
object | sugfis
object | mamfistype2
object | sugfistype2
object | fistree
object
Fuzzy inference system, specified as one of the following:
mamfis
object — Mamdani fuzzy inference systemsugfis
object — Sugeno fuzzy inference systemmamfistype2
object — Type-2 Mamdani fuzzy inference systemsugfistype2
object — Type-2 Sugeno fuzzy inference systemfistree
object — Tree of interconnected fuzzy inference systems (since R2023a)
Name-Value Arguments
Specify optional pairs of arguments as
Name1=Value1,...,NameN=ValueN
, where Name
is
the argument name and Value
is the corresponding value.
Name-value arguments must appear after other arguments, but the order of the
pairs does not matter.
Example: FIS="fis1"
Before R2021a, use commas to separate each name and value, and enclose
Name
in quotes.
Example: "AsymmetricLag",true
FIS
— Names of component FIS objects from FIS tree
string | string array
Since R2023a
Names of component FIS objects from FIS tree, specified as a string or string
array. When you specify this argument, in
,
out
, and rule
contain the tunable settings
for the variables and rules that apply to the specified component FIS objects.
This argument is supported when fis
is a
fistree
object.
AsymmetricLag
— Option to use asymmetric lag
false
(default) | true
Option to use asymmetric lag when tuning the membership functions of a type-2 FIS.
This argument is supported when fis
is a:
mamfistype2
orsugfistype2
objectfistree
with at least one component FIS that is amamfistype2
orsugfistype2
object.
Output Arguments
in
— Tunable settings of input variables
array of VariableSettings
objects
Tunable settings for input variables, returned as an array of VariableSettings
objects. Each
VariableSettings
object contains
tunability settings for the input variable indicated by its FISName
and VariableName
properties.
Specify the tunability settings of the membership functions for this variable, using
its MembershipFunctions
property.
out
— Tunable settings of output variables
array of VariableSettings
objects
Tunable settings for input variables, returned as an array of VariableSettings
objects. Each
VariableSettings
object contains
tunability settings for the output variable indicated by its
FISName
and VariableName
properties.
Specify the tunability settings of the membership functions for this variable, using
its MembershipFunctions
property.
rule
— Tunable settings of rules
array of RuleSettings
objects
Tunable settings for rules, returned as an array of RuleSettings
object. Each
RuleSettings
object contains tunability settings for a rule from the
FIS indicated by its FISName
property.
Specify the tunability settings of the antecedent and consequent for this variable,
using its Antecedent
and Consequent
properties, respectively.
Version History
Introduced in R2019aR2023a: Obtain tunable settings for component FIS in FIS tree
You can obtain tunable settings for a subset of FIS objects in a FIS tree using the
FIS
name-value argument.
R2019b: Tune asymmetric lag for type-2 FIS
When tuning a type-2 FIS, you can tune MFs to use asymmetric lag values. To do so, you
must specify the AsymmetricLag
name-value argument when obtaining
tunable settings using getTunableSettings
.
See Also
setTunable
| getTunableValues
| setTunableValues
| tunefis
| VariableSettings
| RuleSettings
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