1. Automation in howitzer
Present by
1. Gajanan S. Gunjal
2. Prathmesh R. Kumbhare
3. Rohan J. Bobhate
Guided by
Prof. N M KARAJANGI
2. History of howitzer
Scenario
* without automation
* with automation
How automation can be brought into the picture
* Fuzzy
* servo mechanism & Math modelling
Simulation and compensation
Advantages / disadvantages
Future modification
AGENDA
3. Indirect projectile firing mechanism
Based on Principle of Projectile motion
* Formula
iN brief
Range = (velocity) sin2(angle) /2*gravity
2
5. 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
6. 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
9. Fuzzifier
Fuzzy
Knowledge base
Fuzzy
Knowledge base
Input Fuzzifier
Inference
Engine
Defuzzifier OutputInput Fuzzifier
Inference
Engine
Defuzzifier Output
Converts the crisp input to a linguistic variable using
the membership functions stored in the fuzzy
knowledge base.
10. Inference Engine
Fuzzy
Knowledge base
Fuzzy
Knowledge base
Input Fuzzifier
Inference
Engine
Defuzzifier OutpInput Fuzzifier
Inference
Engine
Defuzzifier Outp
Using If-Then type fuzzy rules converts the fuzzy
input to the fuzzy output.
11. Defuzzifier
Fuzzy
Knowledge base
Fuzzy
Knowledge base
Input Fuzzifier
Inference
Engine
Defuzzifier OutputInput Fuzzifier
Inference
Engine
Defuzzifier Output
Converts the fuzzy output of the inference engine
to crisp using membership functions analogous to
the ones used by the fuzzifier.
12. Defuzzifier
Fuzzy
Knowledge base
Fuzzy
Knowledge base
Input Fuzzifier
Inference
Engine
Defuzzifier OutputInput Fuzzifier
Inference
Engine
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)
14. Defuzzifier
Fuzzy
Knowledge base
Fuzzy
Knowledge base
Input Fuzzifier
Inference
Engine
Defuzzifier OutputInput Fuzzifier
Inference
Engine
Defuzzifier Output
( )
,
( )
A
Z
COA
A
Z
z zdz
z
z dz
( ) ( ) ,
BOA
BOA
z
A A
z
z dz z dz
*
,
{ ; ( ) }
Z
MOM
Z
A
zdz
z
dz
where Z z z
19. 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
21. 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.
22. 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.
23. METHOD OF DIFFERENTIAL EQUATION
Trajectory in realistic model with firing angle of vacuum model
30. METHOD OF READING FIRING TABLE
Angle of firing extracted from the firing table of army manual
31. 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.
