Fuzzy logic is a form of logic that deals with the concept of partial truth, that is, truth values that range in degree between completely true and completely false. It is used to model and control systems that are difficult to model using traditional Boolean logic.
Fuzzy logic is different from conventional control methods in several ways. First, fuzzy logic systems are based on the use of fuzzy sets, which are sets that have no clear boundaries. This allows fuzzy logic systems to represent the uncertainty that is often present in real-world systems. Second, fuzzy logic systems use fuzzy rules, which are rules that are expressed in natural language. This makes fuzzy logic systems easier to understand and use than conventional control systems. Third, fuzzy logic systems use fuzzy inference, which is a process of reasoning that is based on fuzzy sets and fuzzy rules. This allows fuzzy logic systems to make decisions that are more robust and adaptable than those made by conventional control systems.
The correct answer to the question “How is Fuzzy Logic different
from conventional control methods?” is A. IF and THEN Approach. Fuzzy logic systems use fuzzy sets and fuzzy rules, which are expressed in the form of IF-THEN statements. For example, a fuzzy rule might state that “IF the temperature is high THEN the fan should be turned on.” Fuzzy logic systems use these rules to make decisions about how to control a system.The other options are incorrect because they do not describe the way that fuzzy logic systems work. Option B, FOR Approach, is a programming construct that is used to iterate over a set of values. Option C, WHILE Approach, is another programming construct that is used to iterate over a set of values as long as a condition is true. Option D, DO Approach, is a programming construct that is used to execute a block of code repeatedly.