FL Set Rule VI

Owning Palette: Rules VIs

Requires: Full Development System

Modifies the antecedents, consequents, or relationships of a rule in a fuzzy system.

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	antecedent connective specifies how this VI calculates the truth value of the aggregated rule antecedent. 0 AND (Minimum)—Specifies that this VI uses the smallest degree of membership of the antecedents. 1 AND (Product)—Specifies that this VI uses the product of the degrees of membership of the antecedents. 2 OR (Maximum)—Specifies that this VI uses the largest degree of membership of the antecedents. 3 OR (Probabilistic)—Specifies 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.
	antecedents specifies 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. You can use the Build Array function or a loop to build an array of rule antecedents that you create with the FL Create Antecedent VI. You then can wire the array to this input.
	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.
	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.
	degree of support specifies the weight, between 0 and 1, that you want to apply to the rule. The default is 1. Multiply the degree of support by the truth value of the aggregated rule antecedent to calculate the rule weight.
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	consequents specifies 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. You can use the Build Array function or a loop to build an array of rule consequents that you create with the FL Create Consequent VI. You then can wire the array to this input.
	consequent implication specifies the implication method this VI uses to scale the membership functions of the output linguistic variable based on the rule weight. 0 Minimum—Specifies to use the Minimum implication method. 1 Product—Specifies to use the Product implication method.
	fuzzy system out returns the complete information for a fuzzy system. Wire this output to the fuzzy system in input of another VI.
	error out contains error information. This output provides standard error out functionality.