artificial light tracking system

7/30/2019 Artificial Light Tracking System

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4/20/2013

SUBMITTED TO:

SIR SALMAN IJAZSUBMITTED BY:

MUHAMMAD MUZAMMIL MUKHTAR(10-ME-117)

QAZI SAMIE SAEED(10-ME-120)

MALIK AHMED NADIR(10-ME-132)

LAB

PROJECTCONTROLLENGGLAB


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10-ME-117,120,132 Page 1

ARTIFICIAL LIGHT TRACKING SYSTEM:

PHYSICS OF THE SYSTEM:

When equal light intensities are detected by the two photodiodes, the electrical bridge is

balanced, and zero voltage is applied to the drive motor. When one photodiodes receives more

light then the other, the bridge is unbalanced, and a nonzero voltage is amplified and applied to

the drive motor, which then moves the photodiodes toward the equal-light intensity position.

Similar systems are used for precision machine tool alignment, where the light is reflected from

calibrated scale or transmitted through a tiny hole in the tool or the work. Variations of this

system are used to track the sun or another star in navigation systems, to follow aircraft in

collision avoidance systems, and to track the recording path on optical videodisks as shown

below

.

ARTIFICIAL LIGHT TRACKING SYSTEM

BLOCK DIAGRAM:

Summing junction Photodiode circuit Dc motor and gears Position velocityAnd amplifier relation

L(s) + motor R(s)

voltage

_

K 0.1

s+2

1

S


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TRANSFER FUNCTION:

It is denoted by T.F

As we know

T.F= OUTPUT = R(s)

INPUT L(s)

REDUCED BLOCK DIAGRAM:

L(s) R(s)

So our transfer function will be

T.F = 0.1

S^2+2S+0.1K

Characteristics equation will be For checking the stability of the system we will apply the ROUTHS HURWITZ TECHNIQUE

1 0.1k 2 0

0

The system transfer function is ,in terms of the gain constant K,

which is stable for all K>0

k>0

Here we can see that there is no sign change in the system during R.H.T. This means system is stable.

We will take the values of K>0

0.1K

S^2+2s 0.1k


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MATLAB CODING:

%lab project Artificial Light Tracking Systema=[0.1]b=[1 2 0.1]t=tf(a,b)step(t)stepinfo(t)a =

0.1000

b =

1.0000 2.0000 0.1000

Transfer function:

0.1

---------------

s^2 + 2 s + 0.1

SYSTEMS PARAMETRES:

RiseTime: 42.8218

SettlingTime: 76.7539

SettlingMin: 0.9015

SettlingMax: 0.9983

Overshoot: 0

Undershoot: 0

Peak: 0.9983

Peak Time: 124.5266

RESPONSE OF THE SYSTEM:


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Hence this system having maximum setting time so it is not suitable for our system.

RESPONSE OF THE SYSTEM AT DIFFERENT VALUES OF K:

MATLAB CODING:

%lab project Artificial Light Tracking Systemk=500a=[0.1*k]b=[1 2 0.1*k]t=tf(a,b)step(t)stepinfo(t)


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SYSTEMS PARAMETERS:

Rise Time: 0.1650

Settling Time: 3.7008

Settling Min: 0.5933

Settling Max: 1.6381

Overshoot: 63.8069

Undershoot: 0

Peak: 1.6381

Peak Time: 0.4443

This value of K having overshoot >20% hence it is not suitable.

MATLAB CODING AT K=20:

%lab project Artificial Light Tracking Systemk=20a=[0.1*k]b=[1 2 0.1*k]t=tf(a,b)step(t)


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stepinfo(t)

SYSTEMS PARAMETER AT K=20:

Rise Time: 1.5225




Overshoot: 4.3155

Undershoot: 0

Peak: 1.0432

Peak Time: 3.1790

Hence this system having the overshoot and its settling time is relatively long so it is not suitable.

MATLAB CODING AT K=5:

%lab project Artificial Light Tracking Systemk=5a=[0.1*k]b=[1 2 0.1*k]t=tf(a,b)step(t)stepinfo(t)


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SYSTEMS PARAMETERS AT K=5:

Rise Time: 7.7014




Overshoot: 0

Undershoot: 0

Peak: 1.0000

Peak Time: 35.8174

By checking the different responses of values of K we see that it give the settling time relatively long in

consequence of the small degree of relative stability.

BY THE ADDITION OF TACHOMETER (sensor or velocity feed back):

The performance of this system can be improved substantially by the addition of velocity feedback as

well as the position feedback. A tachometer coupled to the drive motor shaft will produce a voltage

nearly proportional to the motor speed, which in turn is proportional to the photodiode velocity. Adding afraction of this voltage to the bridge voltage (which is amplified to drive the motor) results in the block

diagram of fig as shown below.


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Light position

L(s)

P(s)

- -

Using the Masons gain rule on the systems signal flow graph in fig below, we can write

L(s) 1

1 P(s)

(-4K)

(-1)

By theMasons rule

the following equation we can write as shown below

()

() ()(())()

By solving the above equation we will get,

() ()

Now from the above equation the characteristics equation will be ( ())

(s+2)^2= = ()Is achieved with K=250, K=0.08

With these values of K and K, the system response is critically damped and has a relative stability of 5units. This step response is shown below.

Amplifier

K

Dc motor and

gears

Velocity-position

relation

Tachometer

and gears 4

Gain

Adjustment

K


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MATLAB CODING AT M-FILE:

%lab project Artificial Light Tracking System By the addition of tachometerk=250c=0.08a=[0.1*k]b=[1 2+0.4*k*c 0.1*k]t=tf(a,b)step(t)stepinfo(t)

ANS

>> k=250c=0.08

a=[0.1*k]b=[1 2+0.4*k*c 0.1*k]t=tf(a,b)step(t)stepinfo(t)

k =

250

c =

0.0800

a =

25

b =

1 10 25

Transfer function:

25---------------

s^2 + 10 s + 25

RESPONSE OF THE SYSTEM:


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Hence system response at K=250 AND K=0.08 is critically damped.

SYSTEMS PARAMETERS:

Rise Time: 0.6718




Overshoot: 0

Undershoot: 0

Peak: 1.0000

Peak Time: 2.7339

Hence now this system is acquired at our desired value where,

1. Settling time


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artificial light tracking system

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