An improved system to be presented through utilization of theories of fuzzy sets and fuzzy logic.

1. Modernization of a cooling
water control system for the
production of plastic pipes
using fuzzy logic
Marin Kochev and Malinka Ivanova
Technical University of Sofia
46th International Conference Applications of Mathematics in Engineering and Economics, 7-13 June 2020

2. Outline
• Fuzzy logic in control systems
• The problem and the aim
• Schematic diagram and functioning
• The proposed solution with Fuzzy logic
• The Fuzzy Associative Memory
• Simulation and results
• Conclusions

3. Fuzzy logic in control systems
• Oltean and Dulau, Design and simulation of fuzzy based
temperature control for a plasma nitriding process, 2014
• Isizoh et al., Temperature Control System Using Fuzzy Logic
Technique, 2012
• Gao et al., A Stable Self-Tuning Fuzzy Logic Control System for
Industrial Temperature Regulation, 2002
• Gouda, Thermal comfort based fuzzy logic controller, 2001
• Aguilar et al. Control Application Using Fuzzy Logic: Design of a
Fuzzy Temperature Controller , 2012

4. The problem and aim
• The problem - Conventional cooling systems are reliable but
largely unprofitable in terms of energy consumption! This is
due to the need for constant switching on and off of the freon
compressor, and when it is switched on, it always operates at
maximum power!
• The aim – An improved system to be modelled for effective
regulation of the load on the freon compressor and flexible
energy consumption to be achieved

5. Schematic diagram and functioning
The cooling water system in the production of
plastic pipes functioning includes:
• A sensor connected to a controller monitors
the temperature of the water
• The controller sets the temperature to be
maintained in the cold part of the tank
(The control system works with hysteresis ± 3 ͦC)
• If the controller is set to 15 ͦC,
• Then, the freon compressor turns on at full
power and the water begins to cool
• When the water temperature in the cold part
of the tank reaches 12 ˚C
• The compressor stops working
• The water begins to warm and when it
reaches 18 ˚C, the compressor switches on
again at full power
• This cycle is repeated
The graphics is from the technical documentation of PipeLife

6. The proposed solution
• The temperature monitoring and control system must be improved through applying
the principle of fuzzy logic that will lead to more flexible regulation of the load on
the freon compressor and thus an effective energy consumption will be achieved
• The fuzzy-based control system modelling follows the developed algorithm:
Evaluation
of the
existing
control
system
1
Extracting
the
variables,
values and
rules
2
Fuzzifica-
tion of
input data
3
Construc-
ting the
Fuzzy
Inference
System
4
Applying
defuzzifi-
cation
method
5
Simulation
and
verification
6

7. Water
temperature in
the tank, ͦС
12 ͦС 15 ͦС 18 ͦС
Compressor
load in %
0% 100% 100%
Energy power
in %
0% 100% 100%
Evaluation of
the existing
control system
1 • Ineffective regulation of the compressor load
• Ineffective power consumption

8. Extracting the
variables,
values and
rules
2
Variable2: Temperature change
and its linguistic meaning:
BN - Big Negative (-2°C),
N - Negative (-1°C),
NC – No change (0°C),
P – Positive (+1°C),
BP – Big Positive (+2°C)
Variable1: Water
temperature in the
tank and its meaning:
12 °С
13 °С
14 °С
15 °С
16 °С
17 °С
18 °С
Variable 3:
Freon
Compressor
Load and its
meaning:
0%
10%
50%
90%
100%
Rules type:
IF Water temperature in the tank is Variable 1 AND Temperature change is Variable 2 THEN Freon Compressor load is Variable 3
(IF t °C is Variable 1 AND Δt °C is Variable 2 THEN L % is Variable 3)

9. Using linguistic variables and
defining their meaning
Fuzzification of
input data
3
Level of compliance Extremely
very low
Very low
temperature
Low
temperature
Normal
High
temperature
Very hitgh
temperature
Extremely
very high
Input variable 1
Water temperature in
the tank (ͦC)
12 ͦС
13 ͦС 14 ͦС 15 ͦС 16 ͦС 17 ͦС
18 ͦС
Input variable 2
Temperature change,
(ͦC)
BN
N
NC
P
BP
BN
N
NC
P
BP
BN
N
NC
P
BP
BN
N
NC
P
BP
BN
N
NC
P
BP
BN
N
NC
P
BP
BN
N
NC
P
BP
Output variable
Freon compressor
load (%)
0% 10% 50% 50% 50% 90% 100%

10. Variables and
membership
functions
Constructing the
Fuzzy Inference
System
4
t, °C14 16
0
μ(t)
1
12 18
0
μ(Δt)
1
2-1 0-2 1 Δt, °C
0
μ(L)
1
L, %30 5010 70 90
















cxb
bc
xc
bxa
ab
ax
bxax
xA
,
,
,,0
)(~

















dxc
cd
xd
cxb
bxa
ab
ax
dxax
xA
,
,1
,
,,0
)(~

11. Fuzzy Associative Memory
Temperature t, °C/
Temperature change Δt, °C
BN N NC P BP
Extremely very low -EVL 0% 0% 0% 10% 50%
Very low temperature- VL 0% 0% 10% 50% 50%
Low temperature - L 0% 10% 50% 50% 50%
Normal temperature - N 10% 50% 50% 50% 90%
High temperature - H 50% 50% 50% 90% 100%
Very High temperature -VH 50% 50% 90% 100% 100%
Extremely very high - EVH 50% 90% 100% 100% 100%
Constructing the
Fuzzy Inference
System
4

12. Applying Mamdami implication
Constructing the
Fuzzy Inference
System
4
t, °C14 16
0
μ(t)
1
12 18
0
μ(Δt)
1
2-1 0-2 1 Δt, °C
0
μ(L)
1
L, %30 5010 70 90
t, °C14 16
0
μ(t)
1
12 18
0
μ(Δt)
1
2-1 0-2 1 Δt, °C
0
μ(L)
1
L, %30 5010 70 90
R1: IF t °C is VL AND Δt °C is BP THEN L % is 50%
R2: IF t °C is EVL AND Δt °C is P THEN L % is 10%
12,8 1,2
0
μ(L)
1
L, %30 5010 70 90

13. Using the method Centre of
gravity
Applying
defuzzification
method
5
0
μ(L)
1
L, %30 5010 70 90






 n
i
ii
n
i
iii
tt
ttc
z
1
1
)}(),(min{
)}(),(min{



14. FisPro Software and FIS response
taking into account all rules
Simulation and
verification
6

15. Conclusions
• A model of a cooling water control system for the production
of plastic pipes is developed based on the theories of Fuzzy
sets and Fuzzy logic and it points out that:
– the effective regulation of the freon compressor load could be
achieved and
– the flexible energy consumption of the compressor that leads to
power energy economy could be specified
• Fuzzy theories are a very suitable base for modeling flexible,
adaptable and complex systems

16. Thank you
for your
attention!
The pictures are taken from: https://www.pipelife.bg/bg/