A fuzzy system is used to control the temperature in a room. The inputs to the c
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A fuzzy system is used to control the temperature in a room. The inputs to the control are the 'Temperature' and 'Temperature change'. The outputs are the 'Fan Speed' and 'Heater The membership functions arc shown in the following figures and the rule base is described by the following table If the temperature is 22 degree C and the change of temperature is 4 degree C/hr, answer the following questions: What is the result of fuzzification of those inputs? Use the rules and Mamdani inference to specify the output fuzzy membership functions. Calculate the 'Heater power' and 'Fan speed' using your choice of defuzzification method.Explanation / Answer
The process comprises of a heater, fan and a temperature sensor. The amount of current passing through the coil decides the temperature of the thin metal plate.
Temperature detection of this metal plate can be done by dedicated temperature sensors.
A fan is placed near to the heating mechanism. Amount of power delivered to both heater and fan can be controlled by passing a command through serial port via microcontroller
. A fuzzy logic system consists of four main parts:
• Fuzzifier
• Rules
• inference engine
• defuzzifier.
In the fuzzification process, a real scalar value changes into a fuzzy value. Arrangements of Fuzzy variables ensure that real values get translated into fuzzy values. After translating those real values into fuzzy values, the possible outcome is called “linguistic terms”.
The input linguistic variables for Fuzzy Logic Temperature Controller (FLTC) suggest two things.
First it shows linguistically the difference between the set point and second it also express the measured and calculated signals from a temperature sensor. Input to FLTC is Error= (Set point-Temperature sensed). For fuzzified input, two functions including trapezoidal and triangular are used. To determine the range of fuzzy variables according to the crisp inputs is the primary requirement for proper running of the fuzzier program.
Temperature difference which was sensed previously, is restricted to positive value. The following fuzzy sets are used: NEG =negative, SNEG=small negative, ZERO= zero, SPOZ=small positive, POZ= positive. Table suggests the Membership function for input linguistic variable. Membership function for input linguistic variable.
Defuzzification The outcome of defuzzification has to be in a numeric form so that it defines the PWM Wave of the MOSFET which is used toforce the fan and heater. Out of the number of ways to execute defuzzification; in the given scenario, weighted average defuzzification is the best technique to obtain the crisp output. It can be further described by following equation
The fuzzy variable can be converted into crisp output using C code fragment. One example of that is given below.
{
The degree of each membership function which was computed in the previous step of fuzzificationis encountered by the subprogram called “Defuzzify” and this after certain process it returns defuzzified output. This defuzzify output is employed to restraint the pulse width modulation wave of MOSFET
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