final project fuzzy logic washer...
TRANSCRIPT
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Final Project
Fuzzy Logic Washer Machine
By :
Ibrahim H. Banat
Sameh S. Abu Zer
Mohammad T. Al-Khozondar
Khalil T. Mattar
Supervisor : Discussion by:
Dr. Hatem El Aydi Dr. Iyad Abuhadrous
بسم هللا الرحمن الرحيم
Video
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Definition of Washing Machine:
Washing machine: means an appliance for cleaning and rinsing of textiles using water which may also have a
means of extracting excess water from the textiles.
Automatic washing machine:means a washing machine where the load is fully
treated by the machine without the need for user
intervention at any point during the programme prior to its completion.
Programme duration:means the time from the initiation of the programme until the completion of the programme.
If the end of programme is not indicated, the programme time is equal to the cycle time. the
programme is complete when the power consumption of the appliance drops to some steady
state condition and is not performing any function.
Types of Washing Machine
Washing Machine
Top loading washing
machines
Front loading washing
machines
Depending on the position of loading the clothes in washing machine.
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Washing machines classifications
1. Semi-automatic washing machine
2. Fully automatic washing machine
To wash the clothes you have to put the clothes in the wash vessel, put sufficient quantity
of the water and detergent and then press (On/Off) button. After the specified time, the
washing machine will stop. You can remove the clothes and dry them partially in the drier
vessel by setting suitable time.
There is only one tub that serves as the washer, rinser as well as the drier, the machine takes
in the sufficient amount of water and detergent automatically and sets the timer for wash
and drying automatically.
Simplest graphical model of washer
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Principle of washing machine
To understand how a washing machine cleans, we must understand the components of
washing machines
Important parts of the washing machine:
1) Water inlet control valve
2) Water pump
3) Tube (washer drum)
4) Agitator
5) Motor
6) Door safety sensor
7) Detergent drawer
8) Drain pipe
9) Controller
10) Mechanical programmer
Wash sensor (Optical sensor)
An optical sensor is a device that converts light rays into electronic signals. it
measures the physical quantity of light and translates it into a form read by the
instrument. The features of an optical sensor is its ability to measure the changes from
one or more light beams.
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A washing machine includes an optical sensor for detecting a light permeability of detergent
solution and rinse water in a washer tank.
The optical sensor includes a light emitting element and a light receiving element.
A microprocessor (Fuzzy Controller) is provided for controlling a luminous intensity of the
light emitted from the light emitting element.
How Wash sensor work
The working of the sensors is not a matter of concern. We assume that we have these inputs
at our hand.
1. The degree of dirt is determined by the transparency of the wash water. The dirtier the
clothes, less transparent the water being analyzed by the sensors is.
2. Type of dirt determines the quality of dirt. Greasy cloths, for example, take longer for
water transparency to reach transparency because grease is less soluble in water than
other forms of dirt. type of dirt is determined by the time of saturation.
Saturation is a point, at which there is no more appreciable change in the color of the
water.
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Unfortunately, there is no easy way to formulate a precise mathematical relationship
between volume of clothes and dirt and the length of wash time required.
Because the input/output relationship is not clear, the design of a washing machine controller
has not in the past lent itself to traditional methods of control design.
We address this design problem using fuzzy logic.
Fuzzy logic has been used because a fuzzy logic controlled washing machine controller gives
the correct wash time even though a precise model of the input/output relationship is not
available.
Fuzzy Logic Control
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Fuzzy controller
How is fuzzy logic used?
1) Define the control objectives and criteria?!
2) Determine the inputs and outputs of the plant.
3) Create FL membership functions that define the meaning (values) ofInput/Output terms used in the rules.
4) Assign the fuzzy relationships between inputs and outputs, thus forming therule base IF X AND Y THEN Z .
5) Fuzzify the inputs to the controller.
6) Use one of inference methods for fuzzy systems based on linguistic rules toinfer the output contributed from each rule.
7) Apply defuzzification to form a crisp output.
8) Test the system, evaluate the results, tune the rules and membership functions, and retest until satisfactory results are obtained.
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Problem Definition (Main Idea of the Project)
To automate the project, we use sensors to detect these parameters :1. degree of clothes dirt 2. Type of dirtThe wash time is then determined from this data
Membership function of dirt
Membership Function of type_of_dirt
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Membership Function of wash time
Type of Dirtiness
Dir
tin
ess
Rules in MatLab:
Rules
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FPGA
Introduction
• FPGA: standard for Field Programmable Gate Array.
• They are an integrated circuit that can be configured by the user in order to implement digital logic functions of varying complexities.
• FPGA over DSP or other microprocessors.
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Why we use FPGA?
• PLD: Configured by engineers to perform a variety of different functions. (logic gates limited , functions smaller a simpler) compared to FPGA
• ASIC , ASSP: Customized to specific application (Millions of logic gates ,Functions Complex). Take long time to manufacture and con not be modified.
• FPGA : Middle ground
Trade off between FPGA and ASIC
• Cost.
• Implementing design.
• Time to market.
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History
• PLDs was existed in the market from 1970.
• PLAs
• PAL
• simple version of PLA
• Less flexible than PLA
• Faster
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• SPLD (PLA , PAL)
• At each junction there is a fuse so the programmer can select the junctions how want by software tools.
• CPLD purpose extend density (increase Logic block)
• FPGA provided programmable logic using multi-level logic of arbitrary depth.
Types of FPGA
• There are two types:– SRAM (Static Random Access Memory)
– OTP (One Time Programmable)
• SRAM as – Xilinx ,Altera , Atmel
• OTP as– Actel
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FPGA Architecture
• consists of
– N*N configurable logic block (CLB).
– programmable I/O (IOB) .
– programmable interconnection network.
• Logic cell
– The core building block.
– Consist of:• 4 – input LUT.
• Multiplexer.
• Register.
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• Slice
– Contains two logic block
• CLB
– Xilinx FPGAs have two slices in each CLB, while others have four
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Xilinx Software
• WebPACK ISE Software
– Designed reached by
• Description language as (VHDL , Verilog) .
• Schematic capture package.
• Both.
Xilinx FPGA families
• Old family.
– XC3000, XC4000, XC5200
• High performance family.
– Virtex
• Low cost family.
– Spartan
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Software and Simulation
WebPACK ISE
• Our project module
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• Fuzzy Logic Controller (FLC) module
• LCD (Liquid Crystal Display )
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Matlab Work
• Fuzzy Interference System (FIS) work
Work
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Results table
Output
InputFPGA kit GUI Fuzzy tool Xfuzzy tool
Wash time (min)
Dirt = 50%
20 20.6 20.7 20Type_dirt =50%
result is acceptable and the controller is able to control all hardware components for washing machine effectively.
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Conclusion
1. By the use of fuzzy logic control we have been able to obtain a wash time for different
type of dirt and different degree of dirt.
2. The conventional method required the human interruption to decide upon what should be
the wash time for different cloths.
3. The situation analysis ability has been incorporated in the machine which makes the
machine much more automatic and represents the decision taking power of the new
arrangement.
4. The strength of fuzzy logic is that we are able to model words by the use of fuzzy sets.
Future Work
1. A more fully automatic washing machine is straightforward to design using fuzzy
logic technology.
2. Increasing the controller work that controls only the wash time of a washing machine,
to design process can be extended to other control variables such as water level and
spin speed. The formulation and implementation of membership functions and rules is
similar to that shown for wash time.
3. If the Optical sensor is available in the future, the hardware also will be available to
construct it in the real world.
4. Full "Fuzzy Logic“ automatic control system, includes the correct temperature, washing
time, and washing speed.
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