CHAPTER 1
INTRODUCTION
1.1 BACKGROUND STUDY
Temperature Control cuts through a
variety of Industrial and domestic processes such as temperature
controlled heat exchangers, baths, green houses, incubators. A DC motor
may be used as Fan in accomplishing temperature control. An Electric Fan
is basically a device which comprises of three blades at 120 degrees
mounted on the DC motor spindle.An electric fan circulates the air
around its environment while an airconditioning system changes the
temperature of the air in it environment. Many system used in our daily
life which require controlling are nonlinear in nature; hence, a
detailed system dynamics is difficult to represent mathematically.
Temperature control is stochastic and a slowly changing process which
requires heuristic based control. Many authors have proposed Fuzzy Logic
Inference System in dealing with temperature control.ย In households
during summer which is analogous to dry season in West Africa, Air
conditioners are responsible for 6070% of summer electricity bill. A
window airconditioning unit uses 500 to 1440 watts,while a 2.5ton
central system uses 3500 watts .However, an electric fan uses only 90
watts, depending upon the speed and size (Ali Newaz Bahar et al, 2012).
An electric fan is a device that on the long run will on the one hand
help in keeping us cool in summer and on the other hand help in saving
money as well as protecting the environment by limiting the release of
Carbonmonoxide (Lakshya Kumar et al, 2015).
In this project, a Fuzzy logic
controller design is proposed for deployment of the process variable due
to the fact that temperature is a slowly changing variable. Hence, for
precision control of a stochastic process variable Fuzzy logic based
control suffices. While all the regularly used systems are defined by
mathematical equations. The temperature of the metal plate decides the
amount of current that can pass through it. Temperature of the metal
plate is measured with the help of temperature sensors (Lakshya Kumar et
al, 2015). The amount of energy supplied to the fan is to be controlled
by SVM or PWM technique.
The human brain has an unpredictable way
of reasoning and thus has a high adaptive approach with recourse to
control. It does not reason as computers do. Computers reason in a clear
statement that uses true or false (0 or 1)  an element is either a
number of a given set or it is not. There are many complex systems which
do not fit into the precise categories of conventional set theory. This
is because of the fact that there is no way to define a preciseย
thresholdย toย representย theirย complexย boundary,ย andย asย suchย
theirย controlย systemย isย complex.ย Fuzzy logic was developed owing to
this imprecise nature of solving control problems by computer. In aย
fuzzyย logicbasedย system,ย aย variableย can takeย anyย truthย value
fromย aย closeย setย [0,ย 1]ย ofย realย numbersย thusย generalizingย
Boolean truthย values [1]. Butย theย fuzzyย facts areย true onlyย to
someย degreesย betweenย 0ย andย 1,ย andย theyย areย falseย toย someย
degrees ย (Isizoh A. N., et al, 2012). The Fuzzy inference is based on
Human heuristic reasoning pattern. But computersย cannotย doย soย
becauseย itsย logicย isย basedย onย approximateย reasoningย inย aย moreย
familiarย Booleanย formsย ofย logic used in conventional set theory.ย
Fuzzy logic allows theย use of labels like โslightlyโ, โmoderatelyโ,
medium, and โveryโ soย thatย statementsย mayย beย madeย withย varyingย
degreeย of precision. This flexibility is useful in coping with the
imprecision of realworld situations such as designing precision
environmental control systems. In a broad sense, fuzzy logic refers to
fuzzy sets  a set with nonsharp boundaries. Fuzzy logic is widely used
in machine controls, as it allows forย aย generalizationย ofย
conventionalย logicย andย providesย for terms ย betweenย โtrueโย andย
โfalseโ,ย likeย โalmostย trueโย or partiallyย falseโ. This makes the
logic not to be directly processed on computers but must be emulated by
special codes. A fuzzy logic based design control system offers
flexibility inย systemย design and implementation,ย since its
implementation usesย โifย thenโย logicย insteadย ofย sophisticatedย
differential equations.ย Itโs technology that provides room for
graphical user interface, which makes it understandable by people who do
not have process control backgrounds. Another key significance of a
fuzzy logicbased control design is the ability to automatically and
smoothly adjust the priorities of a number of controlled variables.
Finally, itย helpsย toย achieveย a process thatย isย stableย forย a
ย longย periodย ofย timeย withoutย aย needย for intervention. However,
becauseย ofย theย rulebasedย operationย ofย fuzzyย systems, any
reasonable number of inputs can be processed andย numerousย outputsย
generated;ย although definingย theย rulebase quicklyย becomesย complexย
ifย tooย manyย inputsย andย outputsย are chosen for a single
implementation,ย since rules defining their interrelations must also be
defined. There are countless applications of fuzzy logic. In fact manyย
researchersย stillย claimย thatย fuzzyย logicย isย anย encompassing
theory over all types of logic .Fuzzyย logicย canย controlย nonlinearย
systemsย thatย wouldย beย difficultย orย impossibleย toย modelย
mathematically. This opens door for control system that would normally
be deemed unfeasible for automation. There are manyย approachesย toย
implementย fuzzyย logic systems;ย theyย canย beย softwareย only,ย
hardwareย onlyย orย the combination of software and hardware. In recent
years, fuzzy logic has been implemented using several technologies to
solve real world problems such as image processing, robotics/motion
control, pattern recognition, fuzzy database and industrial engineering
applications. Fuzzyย logicย isย alsoย spreadingย applicationsย in the
field of telecommunications, particularly in broadย bandย integratedย
networks,ย basedย onย ATMย Technology.
1.2 STATEMENT OF PROBLEM
The control modes used varies like ON/OFF control, the linear predictive control (LPC) and PID control system.
ย The ON/OFF system regulator is not
accurate enough. This control mode is the simplest form of control Low
accuracy and quality leads the system to become unstable due to mismatch
error generated by inaccurate time delay parameter used in the model.
Transient and overshoot are present when the controller is used to
control the cooling system because it exceeded the required control for
certain period.
ย
Figure 1: Block diagram of a ON/OFF system for temperature control system

ย 
ย
The linear predictive control, is
capable of controlling the indoor temperature within the required limits
most of the time but not all the time, the linear predictive control in
the relative short prediction periods are used which do not cause any
problem, but it is obvious that with larger prediction periods more
computing time is necessary and the linear programming problems require
more memory.
ย
ย
Figure 2: optimal predictive control system for temperature control
The proportional integral derivative
(PID) controller structure is mostly widely used thanks to its
structural simplicity and applicability in solving practical control
problems but is not however almighty in many cases, it provide
disturbance ,this disturbance is unknown ,making it difficult to
attenuate.
ย
Figure 3: Block diagram of a PID controller
Traditional proportional integral
derivative (PID) controller sometimes doesnโt satisfy the control
purpose for the object which has larger inertia delays and non linear
characteristics and uncertain disturbances factor like the tall and big
space, because of the dissatisfaction of the tuning parameter, the
effect of dissatisfying performance and the adaptability to different
medium.
ย But the used PD controller is better
than PID control because the strictly limit and the overshoot and easy
deals gives us good result than PID control.
So in this project we choose to use
fuzzy logic control (FLC) because the fuzzy logic control provides a
good performance without transient and overshoot and the use of
appropriate automatic control strategies such as fuzzy control system is
based on the operational experience of human expert, the system is
robust to changes in environment.
ย
ย
Figure 4: Block diagram of fuzzy logic controller

ย 
ย
The main advantage of fuzzy logic
controller as compared to conventional control approaches resides in the
fact that no mathematical modeling is required for the design of the
controller. Fuzzy controllers are designed on the basis of the human
knowledge of the system behavior.in addition the controllers that
directly regulate humans thermal comfort have advantages over the
thermostatic controller. The main advantages are increased comfort and
energy saving.
1.3 AIM AND OBJECTIVES OF WORK
The aim of the project is to control the
speed of a DC fan using a fuzzy controller based on variation in
temperature, to achieve good response during changes in load demand,
self tuning fuzzy controller is designed to reduce overshoot,
undershoot during command speed variations and transient.
The objectives of this project are:
 To develop a cooling ventilation system integrated with speed controller based on temperature sensor.
 To improve the cooling system in room using fan rather than using
air conditioner associated with sustainability and environmental
friendly using fuzzy control logic
 To design a controller using MATLAB Fuzzy Logic tool box
 To evaluate the performance of the controller for both the experimental and Simulated model
1.4 SIGNIFICANT OF WORK
The needs for the design of an automatic room temperature control fan are as follows:
 It helps in controlling fluctuating room temperature by adjusting Fan to achieve the desired set point.
 It eliminates the need for human intervention as opposed to constant
watching on the device by set controlling the temperature of the system
 It overcomes the disadvantages of thermostatic analogue system in terms of accuracy.
 It is used where it is important to maintain precise temperature.
 It overcome the limitation of conventional control that how to be
operated by physically going near them and switch on the button.
 The designed controller may be deployed for other slowly changing controlled process variable.
1.5 SCOPE OF WORK
The project scopes relates to
 Development of model house included the dimension and high ceiling using solid work
 Design and Construction of the Prototype
 Simulation of the process using MAT LAB AND PROTEUS
 Microcontroller programing of Fuzzy logic Inference
 Construction and Soldering of the Temperature Control Circuitry (e.g Power Supply based SVM or PWM ).