# update

Update fuzzy rule using fuzzy inference system

## Description

example

ruleOut = update(ruleIn,fis) updates the fuzzy rule ruleIn using the information in fuzzy inference system fis and returns the resulting fuzzy rule in ruleOut.

## Examples

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Create a fuzzy rule using a verbose text description.

rule = fisrule("if service is poor and food is delicious then tip is average (1)");

Alternatively, you can specify the same rule using a symbolic text description.

rule = fisrule("service==poor & food==delicious => tip=average")
rule =
fisrule with properties:

Description: "service==poor & food==delicious => tip=average (1)"
Antecedent: []
Consequent: []
Weight: 1
Connection: 1

Before using rule with a fuzzy system, update the rule Antecedent and Consequent properties using the update function.

rule = update(rule,fis)
rule =
fisrule with properties:

Description: "service==poor & food==delicious => tip=average (1)"
Antecedent: [1 2]
Consequent: 2
Weight: 1
Connection: 1

Create a fuzzy rule using a numeric description. Specify that the rule has two input variables.

rule = fisrule([1 2 2 0.5 1],2)
rule =
fisrule with properties:

Description: "input1==mf1 & input2==mf2 => output1=mf2 (0.5)"
Antecedent: [1 2]
Consequent: 2
Weight: 0.5000
Connection: 1

Before using rule with a fuzzy system, update the rule Description property using the update function.

rule = update(rule,fis)
rule =
fisrule with properties:

Description: "service==poor & food==delicious => tip=average (0.5)"
Antecedent: [1 2]
Consequent: 2
Weight: 0.5000
Connection: 1

## Input Arguments

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Fuzzy rule, specified as a fisrule object or an array of fisrule objects. If ruleIn was created using a:

• Text description, its Antecedent and Consequent properties are updated using the input and output membership function indices in fis that correspond to the membership function names in the Description property of ruleIn

• Numeric description, its Description property is updated using the input and output membership function names in fis that correspond to the membership function indices in the Antecedent and Consequent properties of ruleIn

If you specify ruleIn as an array of fisrule objects, then all of the rules are updated accordingly.

Fuzzy inference system, specified as one of the following:

• mamfis object — Mamdani fuzzy inference system

• sugfis object — Sugeno fuzzy inference system

• mamfistype2 object — Type-2 Mamdani fuzzy inference system (since R2019b)

• sugfistype2 object — Type-2 Sugeno fuzzy inference system (since R2019b)

## Output Arguments

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Fuzzy rule, returned as a fisrule object or an array of fisrule objects.

## Version History

Introduced in R2018b