Returns the antecedents, consequents, and relationships for a rule in a fuzzy system.


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Inputs/Outputs

  • ccclst.png fuzzy system in —

    fuzzy system in specifies the complete information for a fuzzy system. Wire the fuzzy system out output from another VI to the fuzzy system in input of this VI.

  • ci32.png rule index —

    rule index specifies the index of the rule whose information you want to return. rule index corresponds to the order in which the rule was created.

  • cerrcodeclst.png error in (no error) —

    error in describes error conditions that occur before this node runs. This input provides standard error in functionality.

  • iu16.png antecedent connective —

    antecedent connective indicates how this VI calculates the truth value of the aggregated rule antecedent.

    0AND (Minimum)—Indicates that this VI uses the smallest degree of membership of the antecedents.
    1AND (Product)—Indicates that this VI uses the product of the degrees of membership of the antecedents.
    2OR (Maximum)—Indicates that this VI uses the largest degree of membership of the antecedents.
    3OR (Probabilistic)—Indicates that this VI uses the probabilistic sum of the degrees of membership of the antecedents. The fuzzy logic controller uses the following equation to calculate the probabilistic sum: (A + B) – (A * B), where A and B are the antecedents.
  • i1dnclst.png antecedents —

    antecedents returns the antecedents, or IF portions, of the rule. Each antecedent consists of three parts: the index of an input linguistic variable, an operator that specifies whether to calculate the degree of membership or the degree of non-membership of the input linguistic variable within a linguistic term, and the index of the linguistic term. The indexes correspond to the order in which the variables or linguistic terms were created.

  • ii32.png Var Index —

    The index of an input linguistic variable.

  • ii32.png MF Index —

    The index of the linguistic term.

  • iu16.png Cond —

    An operator that specifies whether to calculate the degree of membership or the degree of non-membership of the linguistic variable within a linguistic term.

  • icclst.png fuzzy system out —

    fuzzy system out returns the complete information for a fuzzy system. Wire this output to the fuzzy system in input of another VI.

  • idbl.png degree of support —

    degree of support returns the weight, between 0 and 1, that you want to apply to the rule. Multiply the degree of support by the truth value of the aggregated rule antecedent to calculate the rule weight.

  • ierrcodeclst.png error out —

    error out contains error information. This output provides standard error out functionality.

  • i1dnclst.png consequents —

    consequents returns the consequents, or THEN portions, of the rule. Each consequent consists of three parts: the index of an output linguistic variable, an operator that specifies whether to calculate the degree of membership or the degree of non-membership of the output linguistic variable within a linguistic term, and the index of the linguistic term. The indexes correspond to the order in which the variables or linguistic terms were created.

  • ii32.png Var Index —

    The index of an output linguistic variable.

  • ii32.png MF Index —

    The index of the linguistic term.

  • iu16.png Cond —

    An operator that specifies whether to calculate the degree of membership or the degree of non-membership of the linguistic variable within a linguistic term.

  • iu16.png consequent implication —

    consequent implication returns the implication method this VI uses to scale the membership functions of the output linguistic variable based on the rule weight.

    0Minimum—Indicates that this VI uses the Minimum implication method.
    1Product—Indicates that this VI uses the Product implication method.