based Washing Machine
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.
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.
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
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
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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