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Automation in howitzer Present by 1. Gajanan S. Gunjal 2. Prathmesh R. Kumbhare 3. Rohan J. Bobhate Guided by Prof. N M KARAJANGI

Automation In HOWITZER (Presentation)

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Page 1: Automation In HOWITZER (Presentation)

Automation in howitzer

Present by

1. Gajanan S. Gunjal

2. Prathmesh R. Kumbhare

3. Rohan J. Bobhate

Guided by

Prof. N M KARAJANGI

Page 2: Automation In HOWITZER (Presentation)

History of howitzerScenario * without automation * with automation How automation can be brought into the picture * Fuzzy * servo mechanism & Math modelling Simulation and compensationAdvantages / disadvantagesFuture modification

AGENDA

Page 3: Automation In HOWITZER (Presentation)

Indirect projectile firing mechanism

Based on Principle of Projectile motion * Formula

iN brief

Range = (velocity) sin2(angle) /2*gravity 2

Page 4: Automation In HOWITZER (Presentation)

Traditional howitzer firing process

Page 5: Automation In HOWITZER (Presentation)

Draw backs in manual firing methods

1) Low firing rate

2) Manual error can’t be eliminated

3) Accuracy depend on how experience solder is

4)Time consuming during moving howitzer vertically and horizontally

Page 6: Automation In HOWITZER (Presentation)

From manual to automatic

Replace all the manual operated wheel by servo motor

Design a drivers for servo motor

Assign an intelligent controller for precise “motion control” such as

Fuzzy

Page 7: Automation In HOWITZER (Presentation)

GENERAL BLOCK DIAGRAM

Page 8: Automation In HOWITZER (Presentation)

Fuzzy Systems

Fuzzy Knowledge base

Input Fuzzifier InferenceEngine Defuzzifier Output

Page 9: Automation In HOWITZER (Presentation)

Fuzzifier

Fuzzy Knowledge base

Fuzzy Knowledge base

I nput Fuzzifier I nferenceEngine Defuzzifier OutputInput Fuzzifier I nferenceEngine Defuzzifier Output

Converts the crisp input to a linguistic variable using

the membership functions stored in the fuzzy

knowledge base.

Page 10: Automation In HOWITZER (Presentation)

Inference EngineFuzzy

Knowledge baseFuzzy

Knowledge base

I nput Fuzzifi er I nf erenceEngine Defuzzifier OutputInput Fuzzifi er I nf erenceEngine Defuzzifier Output

Using If-Then type fuzzy rules converts the fuzzy input to the fuzzy output.

Page 11: Automation In HOWITZER (Presentation)

Defuzzifier

Fuzzy Knowledge base

Fuzzy Knowledge base

I nput Fuzzifi er I nferenceEngine Defuzzifier OutputI nput Fuzzifi er I nferenceEngine Defuzzifier Output

Converts the fuzzy output of the inference engine

to crisp using membership functions analogous to

the ones used by the fuzzifier.

Page 12: Automation In HOWITZER (Presentation)

DefuzzifierFuzzy

Knowledge baseFuzzy

Knowledge base

I nput Fuzzifier I nferenceEngine Defuzzifier OutputI nput Fuzzifier I nferenceEngine Defuzzifier Output

• Converts the fuzzy output of the inference engine to crisp using membership functions analogous to the ones used by the fuzzifier.

• Five commonly used defuzzifying methods:– Centroid of area (COA)– Bisector of area (BOA)– Mean of maximum (MOM)– Smallest of maximum (SOM)– Largest of maximum (LOM)

Page 13: Automation In HOWITZER (Presentation)

DefuzzifierFuzzy

Knowledge baseFuzzy

Knowledge base

I nput Fuzzifi er I nferenceEngine Defuzzifier OutputI nput Fuzzifi er I nferenceEngine Defuzzifier Output

Page 14: Automation In HOWITZER (Presentation)

DefuzzifierFuzzy

Knowledge baseFuzzy

Knowledge base

I nput Fuzzifi er I nferenceEngine Defuzzifier OutputI nput Fuzzifi er I nferenceEngine Defuzzifier Output

( ),

( )

AZ

COAA

Z

z zdzz

z dz

( ) ( ) ,BOA

BOA

z

A Az

z dz z dz

*

,

{ ; ( ) }

ZMOM

Z

A

zdzz

dz

where Z z z

Page 15: Automation In HOWITZER (Presentation)

Rule's

Page 16: Automation In HOWITZER (Presentation)

Aggregate

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All Steps Together looks like

Page 18: Automation In HOWITZER (Presentation)

Defuzzification

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Introduction

● MATLAB fuzzy logic toolbox provides facility for the development of fuzzy-logic systems using− graphical user interface (GUI) tools− command line functionality

● There are five primary GUI tools− Fuzzy Inference System (FIS) Editor− Membership Function Editor− Rule Editor− Rule Viewer− Surface Viewer

Page 20: Automation In HOWITZER (Presentation)

GUI Tools

Page 21: Automation In HOWITZER (Presentation)

Methods for computing firing angle

● Three different methods are implemented for computing firing angle of the HOWITZER:

● 1. Differential equation trajectory method.● 2. Fuzzy logic method.● 3. Firing table reading method.

● The values obtained are compared and conclusions are made.

Page 22: Automation In HOWITZER (Presentation)

Particular case for the experiment

● Taking one case for taking readings :● Projectile of 155mm standards is fired at 3500 meters and

wind velocity of 5 knots.

Page 23: Automation In HOWITZER (Presentation)

METHOD OF DIFFERENTIAL EQUATION Trajectory in realistic model with firing angle of vacuum model

Page 24: Automation In HOWITZER (Presentation)

SIMULINK model to compute final firing angle

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Trajectory for the final firing angle computed using SIMULINK model

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Database compiled in excel sheet

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METHOD OF FUZZY LOGIC Fuzzy logic toolbox in MATLAB

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Fuzzy rule viewer

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SIMULINK model for fuzzy system

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METHOD OF READING FIRING TABLE Angle of firing extracted from the firing table of army manual

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Software Results

● For the particular case following results are obtained:

● 1. Firing angle for differential equation method is 9.4 degree.

● 2. Firing angle for fuzzy logic method is 9.5 degree.● 3. Firing angle extracted from firing table is 9.7 degree.

● These all results are in close agreement with each other.

Page 32: Automation In HOWITZER (Presentation)

Thank you