The article discusses the automatic control system of the Diamond DA42 aircraft anti-icing system. The project was created in MATLAB environment equipped with the Fuzzy Logic Toolbox package. The discussion revolves around the problem of preventing icing. In the analysis four parameters were taken into account: air temperature, cloud water content, temperature of the aircraft and precipitation. On the basis of the initial parameters, ice intensity likely to occur on the air-craft was determined. By automating the activities related to the programming of the anti-icing system, it is possible to significantly relieve the pilot and increase the safety of air operations, particularly in conditions which are conducive to the formation of icing. Currently, the Diamond DA42 aircraft is not authorized to fly into known icing conditions. The use of a fuzzy expert system to control the anti-icing system would greatly increase the scope of operations of the Diamond DA42 aircraft.

Topics
Thermal instruments, Icing conditions, Aircraft, Fuzzy logic
1.
G.
 
Anderson
, “
Applying fuzzy logic in the real world
”, Reprinted with permission of Sensor magazine (www.sensormag.com),
Helmers Publishing. Inc.
,
1992
.
Google Scholar
 
2.
A.
 
Azadeh
,
V.
 
Ebrahimipour
,
P.
 
Bavar
, “
A fuzzy inference system for pump failure diagnosis to improve maintenance process: The case of a petrochemical industry
”,
Expert Systems with Applications
 
37
, (
2010
), pp.
627
–
639
.
https://doi.org/10.1016/j.eswa.2009.06.018
Google Scholar
Crossref
Search ADS
 
3.
M.
 
Baban
,
C.F.
 
Baban
,
F.S.
 
Blaga
, “
Maintenance planing of cold plastic deformation tools using fuzzy logic
”,
Eksploatacja i Niezawodnosc - Maintenance and Reliability
,
3
:
21
–
26
, (
2010
), pp.
1507
–
2711
.
Google Scholar
 
4.
S.
 
Chaudhari
 and
M.
 
Patil
, “
Study and Review of Fuzzy Inference Systems for Decision Making and Control”, American International Journal of Research in Science, Technology
,
Engineering & Mathematics
. ISSN (Print): , ISSN (Online): , ISSN (CD-ROM):
2328
–
3629
, (
2014
).
Google Scholar
 
5.
S.
 
Demirci
,
Ch.
 
Hajiyev
,
A.
 
Schwenke
, “
Fuzzy logic-based automated engine health monitoring for commercial aircraft
”,
Aircraft Engineering and Aerospace Technology
, Vol.
80
Iss:
5
, (
2008
), pp.
516
–
525
.
https://doi.org/10.1108/00022660810899883
Google Scholar
Crossref
Search ADS
 
6.
Diamond
 
Aircraft
, “
Supplement S02 to The Airplane flight manual DA42 NG Ice Protection System
”,
Austria
, (
2016
).
Google Scholar
 
7.
Diamond
 
Aircraft
, “
The Airplane flight manual
”,
Austria
, (
2016
).
Google Scholar
 
8.
J.
 
Domicz
 and
L.
 
Szutowski
,
„An airplane pilot’s guide”, wydawnictwo Avia-Test
,
Poznań
, (
2008
) (in Polish).
Google Scholar
 
9.
N.
 
Grzesik
,
„Basics of fuzzy control. Designing fuzzy expert systems in the Matlab-Simulink environment
”,
Wyższa Szkoła Oficerska Sił Powietrznych
, (
2012
) (in Polish).
Google Scholar
 
10.
M.
 
Hadjimichael
, “
A fuzzy expert system for aviation risk assessment
”,
Expert Systems with Applications
Volume
36
, Issue
3
,
Part 2
, (
2009
), pp.
6512
–
6519
.
https://doi.org/10.1016/j.eswa.2008.07.081
Google Scholar
Crossref
Search ADS
 
11.
Z-H.
 
Huang
, “
Structural reliability analysis using fuzzy sets theory
”,
Eksploatacja i Niezawodnosc - Maintenance and Reliability
,
4
:
284
–
294
, (
2012
), pp.
1507
–
2711
.
Google Scholar
 
12.
Jeppesen
, “
Meteorology JAA ATPL Training
”,
Atlantic Flight Training Ltd
,
Germany
, (
2004
).
Google Scholar
 
13.
L.
 
Jia
 and
L.
 
Edward
, “
Fuzzy Logic Controllers for Aircraft Flight Control
”,
Fuzzy Logic and Intelligent Systems International Series in Intelligent Technologies
Volume
3
:
85
–
124
, (
1995
).
https://doi.org/10.1007/978-0-585-28000-4_4
Google Scholar
Crossref
Search ADS
 
14.
J.
 
Kacprzyk
 and
R.R.
 
Yager
, “
Emergency-Oriented expert systems. A fuzzy approach
”,
Information Sciences
, Volume
37
, Issues
1–3
, December (
1985
), pp.
143
–
155
.
https://doi.org/10.1016/0020-0255(85)90009-X
Google Scholar
Crossref
Search ADS
 
15.
N.
 
Kyungmoon
, and
Ramesh K
 
Agarwal
, “
Automatic Landing System Design Using Fuzzy Logic
”,
Journal of Guidance, Control, and Dynamics
, Vol.
23
, No.
2
, (
2000
), pp.
298
–
304
.
https://doi.org/10.2514/2.4522
Google Scholar
Crossref
Search ADS
 
16.
E.H.
 
Mamdani
 and
S.
 
Assilian
, “
An Experiment in Linguistic Synthesis with a Fuzzy Logic Controller
”,
International Journal of Man-Machine Studies
, Vol.
7
, No.
1
,
1975
, pp.
1
–
13
. doi:
https://doi.org/10.1016/S0020-7373(75)80002-2
.
Google Scholar
Crossref
Search ADS
 
17.
W.
 
Pedrycz
, “
Fuzzy multimodels
”,
IEEE Transactions on Fuzzy Systems
. Vol.
4
. No.
2
, (
1996
), pp
139
–
148
.
https://doi.org/10.1109/91.493908
Google Scholar
Crossref
Search ADS
 
18.
Phan H
 
Giang
, “
Decision making under uncertainty comprising complete ignorance and probability
”,
International Journal of Approximate Reasoning
Volume
62
, (
2015
), pp.
27
–
45
.
https://doi.org/10.1016/j.ijar.2015.05.001
Google Scholar
Crossref
Search ADS
 
19.
R.
 
Scorer
,
“Clouds of the World”. Lothian
,
Melbourne
, (
1972
).
Google Scholar
 
20.
P.
 
Szewczak
,
„36/5000 Meteorology for an airplane pilot
”,
Wyd. Avia-Test, Poznań
, (
2007
) (in Polish).
Google Scholar
 
21.
J.
 
Żurek
,
N.
 
Grzesik
, “Fuzzy expert aircraft onboard control systems assistant. Safety reliability and risk analysis: Beyond the horizon”,
ESREL conference proceedings
,
London
,
Taylor & Francis Group
, (
2013
) pp.
250
–
251
.
Google Scholar
 
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