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#### Presentation Slides & Transcript

Supervised by:

Dr. Habib ur-Rehman

Dr. Hazem Nounou

United Arab Emirates University

Faculty of Engineering

Industrial Training and Graduation Projects Unit

Graduation Project I

Water Tank Level Control System

Group members

Amna Khamis

Batul Mostafa

Eman Osman

Moza Hashel

Overview

Tasks done through this semester.

Budget Estimate.

The project Environmental Impact.

Conclusion.

Tasks done

Gantt Chart of the above mentioned tasks.

Idea of the project:

Scope of the project.

Project description.

Design of the project:

Design methodology.

Hardware designing:

Project specifications

Control designing:

Simple case study.

Type of controllers.

Control techniques.

Software techniques implementation

Gantt chart

Searching Literature

Project background

MATLAB/SIMULINK

Linearization by MATLAB

Checking feasibility

Design system layout

Investigate control techniques

Generate MATLAB code for control techniques

Combining results

Preparing final presentation

Preparing final report

Ordering equipments

Scope of Project

The project focuses on enhancing the student's experiences in the following fields:

Product development.

Design and construction.

Computer modeling and analysis.

Testing and experimental investigations.

The System Layout and Description

Design Methodologies

A controller will be designed and simulated using MATLAB/Simulink software.

A prototype of the Water Tank System will be built.

The prototype will be interfaced to the computer via dSPACE (digital-Signal-Processor-Based) control board.

Project specifications

It is supposed to build a middle sized prototype.

Searching for Equipment:

Devices: pumps, tanks, hoses and sensors.

Software package: Simulink/MATLAB.

Interfacing board: dSPACE.

Pumps

The quantity of water to be handled is approximately three liters. This yields to get small pumps.

Pressure and frictional losses are negligible due to the size of layout and the nature of the used liquid (water).

High-speed centrifugal (rotary pumps) are preferred due to direct coupling to the internal motor.

Corrosion factor is negligible due to the layout nature.

Pumps

Hoses

Volume of tanks and power of used pumps are essential factors for choosing hoses.

Hoses should be as smooth as possible to avoid friction which leads to slow down the flow rate of water.

Flexibility and ability of connecting chosen hoses to other components should be taken into consideration.

Hoses’ length must be compatible with the system layout.

Hoses

Tanks

Capacity of tanks should be chosen so that three liters of water are accommodated.

Tanks should be of light materials (i.e: plastic) in order to be portable and easy to move.

Tanks should be transparence in order to notice the water level.

Also, they should be covered to avoid any disturbances that come from outside.

Tanks

Sensors

Pressure of water and tanks’ specifications, such as volume and height, should be considered while choosing sensors.

Volume of sensors must be compatible with the system layout.

Sensitivity of sensors has to be as high as possible.

Sensors

MATLAB / Simulink

The dSpace Board

Case Study (Process Control)

The case study introduced the simple control concepts to be generalized to our project. They are:

Linearization.

Types of controllers.

Process control experiment.

Linearization and control concepts

All real systems are non-linear.

Linearization is a method at which non-linear system is converted to linear systems to simplify dealing with systems.

Simple experiment of a temperature control system

Design of a simple experiment by MATLAB/Simulink.

Controlling temperature by ON-OFF controller.

MATLAB/Simulink model of the Temperature Experiment

Resultant temperature

ON-OFF Controller

Simplest control method.

Easy to be developed.

Effective for most disturbances.

Drawback: uses a lot of energy.

PI Controller

PI stands for Proportional-Integral Control.

It depends on two parameters:

Proportional gain (Kp).

Integral gain (KI).

Easy to be developed.

Consumes less energy than ON-OFF controller.

State variable feedback

When the control signal for the process is a direct function of all the state variables.

Fuzzy Controller

An intelligent and complicated controller.

Will be studied later according to the availability of time.

Control Techniques

A system was used from a reference book to apply the following techniques.

The technique implemented are:

Regulation:

With observer.

Without observer.

Tracking:

With observer.

Without observer.

Regulation with observer

X’ = AX + BU,

noting that X is the state to be estimated

Y = CX,

Y is the output desired from the system described in these equations

Here we are assuming having a new equation for the error. This error gives a value that describes how far we are from the desired state variable value.

Depending on the following set of equations:

E = X – X^, E represents the error

E’ = (A-LC) E L is a matrix form factor that appears in the X^ equation

as:

X^ = AX + BU + L(Y-Y^)

The goal here is to choose the following parameters with accordance to the following constrains:

Select K such that (A-BK < 0)

Select L such that (A-LC < 0)

Regulation with observer system

Regulation without observer

X’ = AX + BU,

noting that X is the state.

Y = CX,

Y is the output desired from the system described in these equations.

X’ = AX – BKX

as: U = -KX

Then:

X’ = (A-BK) X

select K such that (A-BK < 0)

Regulation without observer

Tracking without observer

X’ = AX + BU,

noting that X is the state to be estimated.

Y = CX,

Y is the output desired from the system described in these equations.

U = -KX + JR R is the desired trajectory.

After some algebraic steps, the closed loop system can be stated as:

X’ = Abar X+ Bbar R

Y = Cbar X + Dbar U

Where:

Abar = A- BK

Bbar = BJ

Cbar = C and Dbar = 0.

Tracking without observer system

Tracking with observer system

X’ = AX + BU X is the state

Y = CX Y is the output

U = -KX + JR R is the desired trajectory.

The closed-loop system is:

Tracking with observer

The generated MATLAB code is available in the Appendix if needed.

Budget Estimation

Some descriptive pictures for the components used in the prototype are shown in this Appendix

Environmental Impact

Control the level of any liquid in any container.

Example: Chemical industrial environment used in factories that pack drinks or medicines.

The designed control system has almost no bad effect on the environment, except if the subjects remaining of building the prototype are to be thrown in the environment.

Conclusion

Software experience is to be gained throughout working on this project on different scales.

Working in team, organizing project timings and dealing with products are essentials for good engineer. Hopefully, they will be well-covered.

Learned Ethics and lessons.

Any Questions Please

Regulation without observer

A=[1 1 -1;4 3 0;-2 1 10];

B=[0;0;1];

n=length(B);

p=[-2 -3 -1];

k=place(A,B,p);

Abar=A-B*k;

t=0:0.1:10;

D=[0];

u=0*ones(1,length(t));

C=[1 0 0];

sys=ss(Abar,zeros(n,1),C,D);

lsim(sys,u,t,[1,2,3])

hold on

C=[0 1 0];

sys=ss(Abar,zeros(n,1),C,D);

lsim(sys,u,t,[1,2,3])

C=[0 0 1];

sys=ss(Abar,zeros(n,1),C,D);

lsim(sys,u,t,[1,2,3])

Regulation with observer

A = [-2 -2.5 -0.5; 1 0 0; 0 1 0];

B = [1; 2; 3];

C = [1 4 3.5];

D = [0];

[n,n]=size(A);

p = [-3 -5 -7];

Lt= place(A',C',p);

L = Lt';

K=place(A,B,p);

Abar = [A -B*K ; L*C A-B*K-L*C];

t=0:0.1:2.5;

u=0*ones(1,length(t));

figure

sys3=ss(Abar,ones(2*n,1),[1 0 0 0 0 0],[0]);

lsim(sys3,u,t,[1,2,3,1,2,3])

hold on

sys3=ss(Abar,ones(2*n,1),[0 1 0 0 0 0],[0]);

lsim(sys3,u,t,[1,2,3,1,2,3])

hold on

sys3=ss(Abar,ones(2*n,1),[0 0 0 0 0 1],[0]);

lsim(sys3,u,t,[1,2,3,1,2,3])

title('Regulation with observer - states estimates')

sys3=ss(Abar,ones(2*n,1),[0 0 1 0 0 0],[0]);

lsim(sys3,u,t,[1,2,3,1,2,3])

title('Regulation with observer - actual states')

figure

sys3=ss(Abar,ones(2*n,1),[0 0 0 1 0 0],[0]);

lsim(sys3,u,t,[1,2,3,1,2,3])

hold on

sys3=ss(Abar,ones(2*n,1),[0 0 0 0 1 0],[0]);

lsim(sys3,u,t,[1,2,3,1,2,3])

Tracking without observer

A = [-2 -2.5 -0.5; 1 0 0; 0 1 0];

B = [1; 2; 3];

C = [1 4 3.5];

D = [0];

[n,n]=size(A);

p = [-3 -5 -7];

K=place(A,B,p);

Abar =A-B*K ;

Cbar=C;

Dbar=[0];

sysx=tf(ss(Abar,B,Cbar,Dbar));

J=1/dcgain(sysx);

Bbar=B*J;

t=0:0.1:7;

lt=length(t);

r=[1*ones(1,(lt-1)/2) 3*ones(1,((lt-1)/2)+1)];

figure

sys4=ss(Abar,Bbar,Cbar,Dbar);

lsim(sys4,r,t,[0.1,0.2,0.3])

Tracking with observer

A = [-2 -2.5 -0.5; 1 0 0; 0 1 0];

B = [1; 2; 3];

C = [1 4 3.5];

D = [0];

[n,n]=size(A);

p = [-3 -5 -7];

K=place(A,B,p);

Lt= place(A',C',p);

L = Lt';

Abar = [A -B*K ; L*C A-B*K-L*C];

Bbar=[B;B];

Cbar=[C 0 0 0];

Dbar=[0];

sysx=tf(ss(Abar,Bbar,Cbar,Dbar));

J=1/dcgain(sysx);

B2bar=Bbar*J;

t=0:0.1:7;

lt=length(t);

r=[1*ones(1,(lt-1)/2) 3*ones(1,((lt-1)/2)+1)];

figure

sys4=ss(Abar,B2bar,Cbar,Dbar);

lsim(sys4,r,t,[0.1;0.2;0.3;0.1;0.2;0.3])h

1.22 X 2.44 m2

P.V.C. sheet

Hose Fittings

Nipple ½”

Non-return Valve

Clamps ½”

Relays

Silicon Glue

PVC Glue

Tapes

Pipe wrench (Resemble adjustable spanner)

Drill

Drill, Hale Saw & Hale Saw bit

Hale Saw

Hale Saw bit