Engineering Information Technology

Application of Fuzzy Logic in Fully Automatic Washing Machine

noreply@blogger.com (fooartz) — Mon, 30 Jul 2007 06:47:00 +0000

Fuzzy control, which directly uses fuzzy rules is the most important application in fuzzy theory. Using a procedure originated by Ebrahim Mamdani in the late 70s, three steps are taken to create a fuzzy controlled machine:

1.Fuzzification(Using membership functions to graphically describe a situation)
2.Rule evaluation(Application of fuzzy rules)
3.Defuzzification(Obtaining the crisp results)

To build a more fully automatic washing machine with self determining wash times, we are going to focus on two subsystems of the machine: (1) the sensor mechanism and (2) the controller unit. The sensor system provides external input signals into the machine from which decisions can be made. It is the controller's responsibility to make the decisions and to signal the outside world by some form of output. 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.

Input/Output of Controller

Fuzzy logic controller have two inputs: (1) one for the degree of dirt on the clothes and (2) one for the type of dirt on the clothes. These two inputs can be obtained from a single optical sensor. The degree of dirt is determined by the transparency of the wash water. The dirtier the clothes, the lower the transparency for a fixed amount of water. On the other hand, the type of dirt is determined from the saturation time, the time it takes to reach saturation. Saturation is the point at which the change in water transparency is close to zero (below a given number). Greasy clothes, for example, take longer for water transparency to reach saturation because grease is less water soluble than other forms of dirt. Thus a fairly straightforward sensor system can provide the necessary inputs for our fuzzy controller.

Definition of Input/Output Variables

Before designing the controller, we must determine the range of possible values for the input and output variables. These are the membership functions used to translate real world values to fuzzy values and back. Figure below shows the labels of input and output variables and their associated membership functions. Note that wash time membership functions are singletons (crisp numbers) in this example. We can use fuzzy sets or singletons for output variables. Singletons are simpler than fuzzy sets. They need less memory space and work faster. If we could not be satisfied by the result when output values are given by singletons we could change them into fuzzy sets. We should use Mandani's method for inference if we want to define output values as fuzzy sets.

Linguistic variables & their ranges

Fuzzy logic for Dirtiness &Type of dirt input

Linguistic variable: Dirtiness, D
Linguistic value Notation Numerical range
Small S [0.00, 50.00]
Medium M [0.00, 100.00]
Large L [50.00, 150.00]

Linguistic variable: Type of dirt, TD
Linguistic value Notation Numerical range
Not greasy NG [0.00, 50.00]
Medium M [0.00, 100.00]
Greasy G [50.00, 150.00]

Rules

The decision making capabilities of a fuzzy controller are codified in a set of rules. In general, the rules are intuitive and easy to understand, since they are qualitative statements written in English like if-then sentences. Rules for our washing machine controller are derived from common sense, data taken from typical home use, and experimentation in a controlled environment. A typical intuitive rule is as follows:

The rule table

Rule	D	TD	Wash time
1	S	NG	VS
2	M	NG	S
3	L	NG	L
4	S	M	S
5	M	M	M
6	L	M	L
7	S	G	M
8	M	G	L
9	L	G	VL
10	S	NG	VS
11	S	M	S
12	S	G	M
13	M	NG	S
14	M	M	M
15	M	G	L
16	L	NG	L
17	L	M	L
18	L	G	VL
19	S	NG	VS
20	M	M	M
21	L	G	VL

How Fuzzy Logic is Applied

noreply@blogger.com (fooartz) — Sat, 21 Jul 2007 08:00:00 +0000

Fuzzy logic usually uses IF/THEN rules, or constructs that are equivalent, such as fuzzy associative matrices.

Rules are usually expressed in the form:
IF variable IS set THEN action

For example, an extremely simple temperature regulator that uses a fan might look like this:

IF temperature IS very cold THEN stop fan
IF temperature IS cold THEN turn down fan
IF temperature IS normal THEN maintain level
IF temperature IS hot THEN speed up fan

Notice there is no "ELSE".

All of the rules are evaluated, because the temperature might be "cold" and "normal" at the same time to differing degrees.

The AND, OR, and NOT operators of Boolean logic exist in fuzzy logic, usually defined as the minimum, maximum, and complement; when they are defined this way, they are called the Zadeh operators, because they were first defined as such in Zadeh's original papers. So for the fuzzy variables x and y:

NOT x = (1 - truth(x))
x AND y = minimum(truth(x), truth(y))
x OR y = maximum(truth(x), truth(y))

There are also other operators, more linguistic in nature, called hedges that can be applied. These are generally adverbs such as "very", or "somewhat", which modify the meaning of a set using a mathematical formula.

Human beings make decisions based on rules. Even though, we may not be aware of it, all the decisions we make are based on computer like if-then statements. If the weather is fine, then we may decide to go out. If the forecast says the weather will be bad today, but fine tomorrow, then we make a decision not to go today, and postpone it till tomorrow. Rules associate ideas and relate one event to another.

Fuzzy machines which always tend to mimics the behavior of man work the same way. Only this time the decision and the means of choosing that decision are replaced by fuzzy sets and the rules are replaced by fuzzy rules. Fuzzy rules also operate using a series of if-then statements. For instance, X then A, if y then b, where A and B are all sets of X and Y. Fuzzy rules define fuzzy patches, which is the key idea in fuzzy logic.

A machine is made smarter using a concept designed by Bart Kosko called the Fuzzy Approximation Theorem (FAT). The FAT theorem generally states a finite number of patches can cover a curve as seen in the figure below. If the patches are large, then the rules are sloppy. If the patches are small then the rules are fine.

The Fuzzy Logic

noreply@blogger.com (fooartz) — Thu, 19 Jul 2007 00:06:00 +0000

Fuzzy logic is an extension of Boolean logic dealing with the concept of partial truth. Whereas classical logic holds that everything can be expressed in binary terms (0 or 1, black or white, yes or no), fuzzy logic replaces Boolean truth values with degrees of truth.

Degrees of truth are often confused with probabilities, although they are conceptually distinct, because fuzzy truth represents membership in vaguely defined sets, not likelihood of some event or condition. Fuzzy logic allows for set membership values between and including 0 and 1, shades of gray as well as black and white, and in its linguistic form, imprecise concepts like "slightly", "quite" and "very". Specifically, it allows partial membership in a set. It is related to fuzzy sets and possibility theory. It was introduced in 1965 by Prof. Lotfi Zadeh at the University of California, Berkeley.

Fuzzy logic is controversial despite wide acceptance: it is rejected by some control engineers for validation and other reasons, and by some statisticians who hold that probability is the only rigorous mathematical description of uncertainty. Critics also argue that it cannot be a superset of ordinary set theory since membership functions are defined in terms of conventional sets.

Many people would note that fuzzy logic sounds good, but how is it being used. A good example is a fuzzy washing machine. Using yes and no logic to make a washing machine that would automatically handle all the controls on a load of wash, would add hundreds of dollars to the cost of the machine. Dozens of special sensors and the equivalent of a small computer would have to be added to the machine. The fuzzy washing machines being sold in Japan for the last few years cost about twenty dollars more, use a handful of inexpensive sensors and a small logic chip. All you have to do to use the machine, in many cases, is put the clothes in and turn it on.
Most scientists refused to look closely at the logic, when it was first talked about. The ideas seemed too radical to them. It took engineers first in Europe, but mainly in Japan to start using fuzzy logic before scientists started to take it seriously.

Other applications of Fuzzy logic such as:

Automobile subsystems, such as ABS and cruise control
Air conditioners
Cameras
Digital image processing, such as edge detection
Rice cookers
Dishwashers
Washing machines and other home appliances.

Role of Sensor in CIM

noreply@blogger.com (fooartz) — Sat, 14 Jul 2007 14:45:00 +0000

This post will tell about the role of sensor in computer integrated in manufacturing. Since we know that the computer integrated manufacturing is based on the manufacturing system that has been implemented by the computer based knowledge. Since the sensor is the most linkable to the automation, the sensor is applying their role in manufacturing system through the computer integrated manufacturing. Based on the role of sensor, we can see that the sensor is actually give the most function to the system to make it work as an automation in computer integrated manufacturing.

Process measurands associated with sensor signal types

Signal Output Type

Associated Process Measurands

Mechanical (includes acoustic)

Position (linear, angular)

Velocity

Acceleration

Force

Stress. pressure

Strain

Mass. density

Moment, torque

Flow velocity, rate of transport

Shape, roughness, orientation

Stiffness, compliance

Viscosity

Crystallinity, structural integrity

Wave amplitude. phase, polarization, spectrum

Wave velocity

Electrical

Charge, current

Potential. potential difference

Electric field (amplitude, phase. polarization. spectrum)

Conductivity

Permittivity

Magnetic

Magnetic field (amplitude. phase. polarization, spectrum) Magnetic flux

Permeability

Chemical (includes biological)

Components (identities, concentrations, states) Biomass (identities, concentrations, states)

Radiation

Type

Energy

Intensity

Emissivity

Reflectivity

Transmissivity

Wave amplitude, phase, polarization, spectrum

Wave velocity

Thermal

Temperature

Flux

Specific heat

Thermal conductivity

Role of Sensor in Computer Integrated Manufacturing

The role of sensor systems for computer integrated manufacturing is generally composed of sensing, transformation / conversion signal processing, and decision making, as shown in figure below. The output of the sensor system is either given to the operator via a human-machine interface or directly utilized to control the machine. Objectives, requirements, demands, boundary conditions, signal processing, communication techniques, and the human-machine interface of the sensor system are described in this section.

Role of sensor in computer integrated manufacturing.

Manufacturing system part	Role of sensors
Machine tools and robot	Position measurement Sensor of orientation Calibration of machine tools and robot Collision detection Machine tools monitoring and diagnosis
Workpiece	Optical measuring Light-section method Tactile measuring
Process monitoring	Temperature controlling Dosage and level controlling Process quantity Process quality

MTAB Aristo Robot

noreply@blogger.com (fooartz) — Tue, 10 Jul 2007 05:54:00 +0000

This MTAB Aristo robot is the first robot that i have been operated during my calss session. From the robot operation that I obtain, I have finished the tasks and able to program the Aristo 6-axes robot according to their required tasks or problem. From the task I must select the low speed of the robot arm because of the high speed will cause a momentum to the robot arm that makes the arm cannot go to the point or position exactly like what we have been write in the program. The high speed also dangerous for the robot because if the robot arm is hit object or human with high speed it will cause severe damage.

In every program, I have put the command HOME ALL and the end of the program is to make sure that the robot is already home the initial position and this will make easy to the robot in making the next movement or execute the other programs. HOME ALL command is use to make the robot arm to come back to the initial position and reset the position of origin in every joint.

The program of the robot is like as C or C++ program that include the command of looping process by using conditional commands like IF, JUMP and LABEL. This all commands is use to loop or repeat the program again. If 'S' is equal to "zero" the program is execute once than the command ADD S = S + 1 is to add the S = "zero" with one and overwrite the answer in 'S' so that for the conditional command IF, when the answer of 'S' is lower that the value of the conditional set the program is execute again and jump to the LABEL declared. While the S will add again and when the conditional command is not fulfill, so that the program will pass the conditional command and execute the next command.

Below is the procedure or safety guide to be taken during operate a robot:

a) All connections to PC, power control unit and robot is in place.
b) The power and air pressure is on.
c) Safety:
i. Be careful not to collide or being touched by the robot to avoid injury
ii. Be aware of robot movement, close monitoring is given to the robot when it makes a move to prevent
from damaging the structure of the robot.
d) Caution:
i. All programs is test at low speed.
ii. Emergency press of is pressed when necessary.
iii. All axes are homed (HOME ALL) every time before running in the new programs.
iv. The robot is don’t to be touched during their operation or movement.

Intelligent Robot

noreply@blogger.com (fooartz) — Thu, 05 Jul 2007 11:24:00 +0000

What is an intelligent robot? Intelligent robot is the machine that can think their operation by itself. Since the machine have a ‘brain’ to think like a machine (robot) with neuro-fuzzy system or genetic algorithm to implement the input to get their output according to the programmed system of the machine (robot).

The vedeo below is one of the robot arm that been use during my CIM laboratory session. the robot procedure as stated below

The vedeo show the robot movement during bolting process. the operation done for 4 bolt operation but the operation shown is not fully bolt feeding process, just the movement of the end effector of the robot arm to each point.

Robotized Bolting Module
Uploaded by fooartz

System Stability Using MATLAB Software 2

noreply@blogger.com (fooartz) — Wed, 04 Jul 2007 11:14:00 +0000

In this chapter we explored the concepts of system stability from both the classical and the state-space viewpoints. We found that for linear systems, stability is based on a natural response that decays to zero as time approaches infinity. On the other hand, if the natural response increases without bound, the forced response is overpowered by the natural response, and we lose control. This condition is known as instability. A third possibility exists: the natural response may neither decay nor grow without bound but oscillate. In this case the system is said to be marginally stable.

We also used an alternative definition of stability when the natural response is not explicitly available. This definition is based on the total response and says that a system is stable if every bounded input yields a bounded output (BIBO) and unstable if any bounded input yields an unbounded output.

Mathematically, stability for linear, time-invariant systems can be determined from the location of the closed-loop poles:

• If the poles are only in the left half-plane, the system is stable.
• If the poles are only in the right half-plane, the system is unstable.
• If the poles are on the jω-axis and in the left half-plane, the system is marginally stable as long as the
poles on the jω-axis are of unit multiplicity; it is unstable if there are any multiple jω-axis.

In this post we will look for the stability in aeroplane by looking to the control system block diagram below

The block diagram represent the system for determining the angle (theta) of the aerofoil in aeroplane system in order to produce the output from the desire input.

After getting the equation from the diagram, with matlab we can find the stability of the system by determining the value K (Gain) from Routh-Hurwitz Criterion

From the program and result above, we can use the MATLAB Simulation program to look either the gain that we get from the calculation can be use through the system. the value K (gain) is inserted through the simulated block diagram and the graph will show the final value which consist the transient response and the stready state error of the system

System Stability Using MATLAB Software 1

noreply@blogger.com (fooartz) — Mon, 02 Jul 2007 03:55:00 +0000

Stability is the most important system specification. If a system is unstable, transient response and steady-state errors are moot points. An unstable system cannot be designed for a specific transient response or steady-state error requirement. There are many definitions for stability, depending upon the kind of system or the point of view.

A linear, time-invariant system is stable if the natural response approaches zero as time approaches infinity.
A linear, time-invariant system is unstable if the natural response grows without bound as time approaches infinity.
A linear, time-invariant system is marginally stable if the natural response neither decays nor grows but remains constant or oscillates as time approaches infinity.

Thus, the definition of stability implies that only the forced response remains as the natural response approaches zero. a stable system needed because in order to build certain system such as an aerofoil in aeroplane system a stable system play most important part in building in because the unstable system will make the whole part of the object that we will build is dangerous to human.

Workspace

noreply@blogger.com (fooartz) — Fri, 29 Jun 2007 13:49:00 +0000

One of the software that ihave been learn in my college to program the robot is using Workspace. There are three main methods to move a robot model using “Workspace”: with the Pendant, the Follow Mouse command or moving to GPs. Below is the Pendant in workspace in controlling the movement of the robot.

First method byusing the Pendant to move a robot model there are six joint values that can be change from 1 to 6. By changing the any value from 1 to 6 the corresponding joint moves. If the value beyond the limit of that joint, a warning error appears. By clicking button Home, the robot returns to its Home position. Second method, the robot moves to the position of the mouse click if it’s within reach, otherwise a warning is given in the message section of the pendant.

Second method is by Learn GP on the Pendant. A GP is set of axes in the main view port shown as green color axes in the picture and it’s listed in the GP folder of the robot. By clicking button Home, the robot returns to its Home position. The robot will returns to GP when select Move to by right click on the name of the GP.

Sumo Robot Competition (SumoBOT)

noreply@blogger.com (fooartz) — Thu, 28 Jun 2007 12:17:00 +0000

In 2004 I had been participated a competition in my faculty call Sumo Robot Competition Interfaculty. in this competition, the robot that have been use are from parallax manufacturer. Below is the picture of the robot that have been use.

The robot components which contain whells, DC servo motor, Battery pack and the other components are being installed together. The robot program of the sumo robot is using the Basic Stamp Editor as shown in figure below:

Robot which defined as device that imitiate human action ussually being programmed by computer is giving us many benefit in order in replacing human work.

PLC Animation Studio 2

noreply@blogger.com (fooartz) — Tue, 26 Jun 2007 15:38:00 +0000

As stated before, the Animation Studio is software that uses to implement the PLC operation through the system (pneumatic, electrical). This post showed another program of PLC using ladder diagram in the Animation Studio. The application of this operation is use for delay counter operation. During my session lab for this experiment, the Animation Studio Software is using library button which the symbol with their tags are given. it easy to use and understand as long as we know the usage of the symbol through the system that we must use. the other thing is, the connection between the rung and the PLC modules in this software must be right in order to avoid any failure.

Figure 1

Figure 1 show the ladder diagram and the PLC connection. Which is the input is at IN0 (push button) and the output is at OUT0 (light) the ladder diagram use the delay counter in which the delay counter will count down in ten times before the current can be go through the system.

Figure 2

In which the Figure 2 show the current cannot go through the delay counter since it have the 9 more times to activate.

Figure 3

The Figure 3 shows that the light is on (yellow color when the delay counter is reach the zero (0) value. Which mean, after the switch in IN0 is switch 9 times, the light will turn ON.

PLC Animation Studio 1

noreply@blogger.com (fooartz) — Mon, 25 Jun 2007 11:34:00 +0000

This post will show the simulation of the PLC system and learn the PLC simulation using Animation Studio software. All of the grafic are developed by myself during my PLC lab session using this Animation Studio software. Animation Studio is a software that use to implement the PLC operation through the system (pneumatic, electrical) in which the animation studio give an opportunity to the student to look the PLC system and study it in simulation.

Figure 1

Figure 1 show the ladder diagram and the PLC connection as reprehensive by the pneumatic system. Which is the input is at IN0, IN1, and IN2 (push button) and the output is at OUT1 (solenoid) the ladder diagram use the countdown delay counter in which the countdown delay counter will count down in ten times before the current can be go through the system. The Countdown delay have 3 input which IN0 (Countdown), IN1 (Reset), and IN2 (Set).

Figure 2

In which the Figure 2 show the system is set when the IN2 push button is pushed. It gives the solenoid on and activates the 3/2 way DCV valve in which allow the suction cup to suck up (vacuum on).

Figure 3

In which the Figure 3 show the system is reset when the IN1 push button is pushed. It stops the solenoid and deactivates the 3/2 way DCV valve in which the valve will go to its initial position and makes the pneumatic system off.

Figure 4

Figure 4 show the delay counter will count down in ten times before the system will off rather than reset it.

OMRON PLC

noreply@blogger.com (fooartz) — Mon, 25 Jun 2007 02:12:00 +0000

Programming Logic Controller as known as PLC is a tool of automation. Automation is one of the importance part in robot and CIM. The automation process replace human operator, and use of control system such as computers to control industrial machinery and process and also reduce need of human sensory and mental requirement as well. One of the PLC that i've been met is an OMRON PLC. Below in the picture of it.

OMRON PLC

This OMRON PLC is used by me during my laboratory section for industrial automation subject. This OMRON PLC can be program by using:

•Ladder diagram
•Functional block diagram
•Sequential block diagram

But, the most popular program is the ladder diagram which use symbol in order to create the program. The ladder diagram example is shown below:

Example of ladder diagram

CIM Robot Video 2

noreply@blogger.com (fooartz) — Sun, 24 Jun 2007 04:49:00 +0000

The system of the bearing supply module is using the Omron PLC control features model CPM2C-S110C-DRT with 15 inputs and 13 outputs. The function of the control features makes the actuator works, by referring to the sensing input. The PLC also make the system is run in sequence for the bearing supply processes.

The other control features that control the system in sequential process is microcontroller.
The inputs that have been used in this system are:
• Reed type magnetic detector (D-C73L)
• Proximity detector micro switch (Omron V-166-1C5)
• Reed type magnetic detector (D-A93L)
• Linear potentiometer (NOVOTECHNIK TR25)

The function of the sensor is to detect the input in which the sensing input then is transferred to the PLC. The reed type magnetic detector is use to check the extension and retraction of the pneumatic actuator and the Proximity detector micro switch is used to detect the appearance of the bearing. While the linear potentiometer is used to check the bearing thickness.

Bearing Supply Module 1
Uploaded by fooartz

CIM Robot Video 1

noreply@blogger.com (fooartz) — Sat, 23 Jun 2007 05:17:00 +0000

As stated before here are the video containing the operation in CIM system. This video i'd recorded during my lab session. the robot will transfer the part to the conveyor after chechking procedure. just take a look...

Body Supply Module 2
Uploaded by fooartz

The function of this station (Body Supply Module) is to supply the correct part of body (position and orientation) to the pallet on the conveyor or transfer system.
Below is the flowchart of handling process of the body supply module station:

1. The pallet is brought to sensor (limit switch) through the conveyor. The sensor will detect the existence of the pallet. Next the machine is run after the PLC is receiving the input that there have a pallet on the conveyor in limit switch.

2. The cylinder will extend and retract to push the body to the position verification part(First cylinder moved)

3. Cylinder (which is located above the position verification part) will extend to check whether the body is in the correct orientation or not, by fitting the end of the extended cylinder into housing of the body.

4. If the body is not in the correct orientation, the sensor on the cylinder will not blinking (red) and send an input to PLC. The cylinder will retract. Then, the body will be extended and guide the the rejection of incorrect body (transfer point) part. The body will be push down the ramp and throwned out from the operating system (reject).

5. Next, the process is started again (the process is repeated by using a new body from the 2nd step).

6. If the body is in the correct orientation, the sensor will blinking (red) and send an input to PLC.

7. Cylinder (Robot end effector) which has 4 suction cups (terminal element), is then being extended on to the body. The vacuum will sucked the body up. The cylinder will retract and bring up the body.

8. Finally the robot arm will extend to transfer the body to the pallet

What Inside???

noreply@blogger.com (fooartz) — Fri, 22 Jun 2007 07:27:00 +0000

This blog contents will discuss about the information technology about engineering technology, which contribute the information about computer, electronic and mechanical engineering. This blog hopefully can be share with other worlds so that my information can be share through the university students who involved in this field (engineering) especially and others (individual). This blog is use by me to share and improve my knowledge in the engineering field and to get friends all over the world. Others blogger also can share their knowledge from the suggestions or comments about the contents of this blog. We also can share problem or experience related so that it won't be wasted. Are U lost if your problem or experience is shared with the others??? Think about it as you explore my blog... Thank you