![]() If the measured value is below 10, the room is too cold. If the measured value is 10 to 20⁰C, the room is cold If the measured value is 22 to 28⁰C, the room is moderate If the measured value is between 30⁰C to 40⁰C, the room is quite hot The fuzzifier assigns linguistic variables for each measured value and the rate of change of measured value.įor example, if the measured value is 40⁰C and above, then the room is too hot.The obtained values are taken and then given to the fuzzifier. The temperature sensor measures the temperature values of the rooms.This is how we can achieve this: Controlling Fan Speed based on Temperature Input If he/she feels too cold, the fan speed is decreased drastically. If he/she feels a bit hot, then the fan speed is increased moderately. For a normal layman if the temperature of the room is such that he/she feels too hot, then the fan speed is increased to the full value. Suppose you want to control the speed of the fan depending on the temperature of the room. A Simple Control System using Fuzzy Logic to Control the Speed of the Fan Depending on the Temperature of the Input. The Defuzzifier converts this fuzzy output to the required output to control the system. The knowledge base consists of the membership functions and the fuzzy rules, which are obtained by knowledge of the system operation according to the environment. ![]() The controller consists of the knowledge base and the inference engine. It performs approximate reasoning based on the human way of interpretation to achieve control logic. Fuzzy Control SystemĪ fuzzy control system consists of the following components: A Fuzzy Logic Control SystemĪ Fuzzifier which transforms the measured or the input variables in numerical forms into linguistic variables.Ī Controller performs the fuzzy logic operation of assigning the outputs based on the linguistic information. For a multi-input system, the variables can also be the different inputs and the output can be the possible result of the AND operation between the variables. Generally, the variables of the set are the state of the inputs and the degrees of changes of the input and the membership of the output depends on the logic of AND operation of the state of the input and the rate of change of the input. The membership of the sets is decided by the IF-Else logic. These fuzzy sets are represented graphically using membership functions and the output is decided based on the degree of membership in each part of the function. This assigning of membership depends on the assumption of the outputs depending on the inputs and the rate of change of the inputs. The output is decided based on the degree of membership of x in the set. The set A is known as a fuzzy set and the value of f A(x) at x denotes the degree of membership of x in that set. Consider a particular set A which is a subset of X such that all members of A belong to the interval 0 and 1. Suppose we want to control a system where the output can be anywhere in the set X, with a generic value x, such that x belongs to X. It works on the principle of If-else-the, i.e. ![]() Each possible state of the input and the degrees of change of the state are a part of the set, depending upon which the output is predicted. Each set represents some linguistic variables defining the possible state of the output. Fuzzy logic works on the concept of deciding the output based on assumptions.
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