01-06-2016, 09:27 PM
Hello
Is there is any difference of using other membership function
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fuzzy based washing machine seminars report
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Hello
Is there is any difference of using other membership function
03-06-2016, 04:28 PM
Abstract
Fuzzy Logic has played a pivotal part in this age of rapid technological development .In this paper we have elaborated on the automation process used in a washing machine. This paper has focused on the two subsystems of the washing machine namely the sensor mechanism and the controller unit.
It also discuss on the use of singletons for fuzzy sets. This paper also highlights the use of a fuzzy controller to give the correct wash time. The use of fuzzy controller has the advantage of managing time, increasing equipment effiency and diagnosing malfunctions.
INTRODUCTION
Classical feedback control theory has been the basis for the development of simple automatic control systems .It is easily comprehensible principle and relatively simple implementation has been the main reason for its wide applications in industry. Such fixed-gain feedback controllers are insufficient, however to compensate for parameter variations in the plant as well as to adapt to changes in the environment. The need to overcome such problems and to have a controller well-tuned not just for one operating point for a whole range of operating points has motivated the idea of an adaptive controller.
In order to illustrate some basic concepts in fuzzy logic consider a simplified example of a thermostat controlling a heater fan illustrated in fig.1.The room temperature detected through a sensor is input to a controller which outputs a control force to adjust the heater fan speed.
A conventional thermostat works like an ON/OFF switch. If we set it at 78F then the heater is activated only when the temperature falls below 75F.When it reaches 81F the heater is turned off .As a result the desired room temperature is either too warm or too hot.
A fuzzy thermostat works in shades of gray where the temperature is treated as a series of overlapping ranges .For example, 78F is 60% warm and 20% hot .The controller is programmed with simple if-then rules that tell the heater fan how fast to run. As a result, when the temperature changes the fan speed will continuously adjust to keep the temperature at desired level. Our first step in designing such a fuzzy controller is to characterize the range of values for the input and output variables of the controller.
Then we assign labels such as cool for the temperature and high for the fan speed, and we write a set of simple English-like rules to control the system. Inside the controller all temperature regulating actions will be based on how the current room temperature falls into these ranges and the rules describing the system behavior .The controller's output will vary continuously to adjust the fan speed.
The temperature controller described above can be defined in four simple rules:
If temperature is COLD then fan speed is HIGH
If temperature is COOL then fan speed is MEDIUM
If temperature is WARM then fan speed is LOW
If temperature is HOT then fan speed is ZERO
Here the linguistic variables cool; warm, high, etc. are labels, which refer to the set of overlapping values. These triangular shaped values are called membership functions.
Fuzzy Logic has played a pivotal part in this age of rapid technological development .In this paper we have elaborated on the automation process used in a washing machine. This paper has focused on the two subsystems of the washing machine namely the sensor mechanism and the controller unit.
It also discuss on the use of singletons for fuzzy sets. This paper also highlights the use of a fuzzy controller to give the correct wash time. The use of fuzzy controller has the advantage of managing time, increasing equipment effiency and diagnosing malfunctions.
INTRODUCTION
Classical feedback control theory has been the basis for the development of simple automatic control systems .It is easily comprehensible principle and relatively simple implementation has been the main reason for its wide applications in industry. Such fixed-gain feedback controllers are insufficient, however to compensate for parameter variations in the plant as well as to adapt to changes in the environment. The need to overcome such problems and to have a controller well-tuned not just for one operating point for a whole range of operating points has motivated the idea of an adaptive controller.
In order to illustrate some basic concepts in fuzzy logic consider a simplified example of a thermostat controlling a heater fan illustrated in fig.1.The room temperature detected through a sensor is input to a controller which outputs a control force to adjust the heater fan speed.
A conventional thermostat works like an ON/OFF switch. If we set it at 78F then the heater is activated only when the temperature falls below 75F.When it reaches 81F the heater is turned off .As a result the desired room temperature is either too warm or too hot.
A fuzzy thermostat works in shades of gray where the temperature is treated as a series of overlapping ranges .For example, 78F is 60% warm and 20% hot .The controller is programmed with simple if-then rules that tell the heater fan how fast to run. As a result, when the temperature changes the fan speed will continuously adjust to keep the temperature at desired level. Our first step in designing such a fuzzy controller is to characterize the range of values for the input and output variables of the controller.
Then we assign labels such as cool for the temperature and high for the fan speed, and we write a set of simple English-like rules to control the system. Inside the controller all temperature regulating actions will be based on how the current room temperature falls into these ranges and the rules describing the system behavior .The controller's output will vary continuously to adjust the fan speed.
The temperature controller described above can be defined in four simple rules:
If temperature is COLD then fan speed is HIGH
If temperature is COOL then fan speed is MEDIUM
If temperature is WARM then fan speed is LOW
If temperature is HOT then fan speed is ZERO
Here the linguistic variables cool; warm, high, etc. are labels, which refer to the set of overlapping values. These triangular shaped values are called membership functions.
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