Chemical Engineering August 2014 - 38

Feature Report
Prohibited area
T
it is a new direction of mathematical
set theory called " fuzzy logic. "
Artificial neural networks are very
effective when the learning capabilities
and methods of the human
brain need to be applied on the basis
of corresponding input and output
data sets of a system. Although several
similarities exist between these
two intelligent control methods, and
their combined application is a popular
solution, they will be discussed
further separately.
The central element of a fuzzy
controller is a " rule base, " containing
rules formulated on an " if ... then ... "
logic scheme. (Example: " if the mixture
temperature is very high, then
set coolant valve to totally open. " )
The previous fuzzy control element
is called " fuzzification, " while the
following one is " defuzzification. "
In the prior one, analog quantities
(such as temperature) will be fuzzified;
that is, ordered into the disReferences
1.
Lackner, Maximilian, Árpád B. Palotás, Franz
Winter, " Combustion: From Basics to Applications, "
Wiley-VCH Verlag GmbH & Co.
KGaA, Weinheim, Germany, ISBN: 9783527333516.
2013.
2. Lackner, Maximilian, Franz Winter, Avinash
K. Agarwal, " Handbook of Combustion, " Wiley-VCH
Verlag GmbH & Co. KGaA, ISBN:
978-3527324491, 2010.
3. Carlucci, A.P., and others, Advanced closed
loop combustion control of a LTC diesel engine
based on in-cylinder pressure signals,
Energy Conversion and Management, 77, pp.
193-207, January 2014.
4. Al-Durra, Ahmed, and others, A real-time
pressure estimation algorithm for closedloop
combustion control, Mechanical Systems
and Signal Processing, 38 (2), pp. 411-427,
July 2013.
5. Tan, K.K., Qing-Guo Wang, Chang C. Hang, Tore
Haggl, " Advances in PID Control, " Springer,
London, ISBN: 9781447112198, 2012.
6. Baukal, Charles E., " Industrial Combustion
Pollution and Control, " Taylor & Francis,
ISBN: 9780824746940, 2003.
7. Advanced Combustion. http://www.carbontrust.com/media/147147/j7971_ctl058_advanced_combustion_aw.pdf.
2014.
8. Haraldsson, Göran; Tunestål, Per; Johansson,
Bengt; Hyvönen, Jari, HCCI Closed-Loop
Combustion Control Using Fast Thermal
Management, In SAE Transactions, Journal
of Engines 113(3). pp. 599-610, 2004.
9. Syred, Nick, Artem Khalatov, " Advanced
Combustion and Aerothermal Technologies:
Environmental Protection and Pollution
Reductions " (NATO Science for Peace and
Security Series C: Environmental Security),
Springer, ISBN: 978-1402065132, 2007.
10. Webpage: http://www.analyticjournal.de/
images_firmenregister/siemens_sitrans_sl_
aufbau.jpg, 2008.
11. Webpage: http://www.analyticjournal.de/images_siemens_user_2004/siemens_haefller_
sum_2004_5_gr.jpg,
2004.
Conventional control
t
crete groups (sets) that correspond
to " intermediate, " " high, " and " very
high. " An important point is that
the borders of these groups (or sets)
are not crisp, like they would be in
classical set theory. This grouping
is much closer to human thinking,
which generally does not draw a
crisp borderline between the sets
distinguishing the age of a person
to sets like " youth " or " middle-aged, "
for example. Defuzzification is a
procedure in the opposite direction.
The characteristics of a fuzzy controller
make it effective for controller
design. The simple realizability
of each element of the fuzzy controller
is another advantage. This
simplicity of operation allows the
12. Gouldin, F.C., J.L. Edwards, Infrared absorption
tomography for active combustion control,
Chapter 2 in " Combustion Processes in
Propulsion, " Taylor and Francis Group, pp.
9-20, 2005.
13. Docquier, Nicolas, and others, Closed-loop
equivalence ratio control of premixed combustors
using spectrally resolved chemiluminescence
measurements, Proceedings of the
Combustion Institute, 29 (1), pp. 139-145,
2002.
14. Glavmo, Magnus, Peter Spadafora and Russell
Bosch, Closed Loop Start of Combustion
Control Utilizing Ionization Sensing in a
Diesel Engine, International Congress and
Exposition, Detroit, Michigan, SAE paper
1999-01-0549, March 1-4, 2009.
15. Samad, T. and A. Annaswamy, (Eds.), The
Impact of Control Technology: Overview,
Success Stories, and Research Challenges.
Available at www.ieeecss.org. IEEE Control
Systems Society, 2011.
16. Chen, Junghui, Yu-Hsiang Chang, Yi-Cheng
Cheng, Chen-Kai Hsu, Design of imagebased
control loops for industrial combustion
processes, Applied Energy, 94, pp. 13-21,
June 2012.
17. Docquier, Nicolas and Sébastien Candel,
Combustion control and sensors: a review,
Progress in Energy and Combustion Science,
28 (2), pp. 107-150, 2002.
18. Smuts, J.F. and A. Hussey, Requirements for
Successfully Implementing and Sustaining
Advanced Control Applications. Presented at
the 2011 ISA POWID Symposium, 06/05/11
-06/10/11, Concord, NC, presented at the 2011
ISA POWID Symposium, Concord, N.C., 2011.
19. Dittmar, R. and B.-M. Pfeiffer, Modellbasierte
prädiktive Regelung in der industriellen
Praxis, Automatisierungstechnik, 54 (12), pp.
590-601, 2006.
20. Qin, S.J. and T.A. Badgwell, A survey of industrial
model predictive control technology,
Control Eng. Pract., 11(7), pp. 733-764,
2003.
21. Szentannai, P., " Power Plant Applications of
Advanced Control Techniques, Process Engi38
ChemiCal engineering www.Che.Com august 2014
Advanced control
Figure 4. Conventional
control (left) and advanced
control (right) of a power
plant. The latter allows a
higher average boiler operating
temperature, which translates
into efficiency gains [21]
possibility of using it in low-cost applications.
Limitations of fuzzy controllers
arise from the basic principle,
which may result in unsmooth
outputs. Clear stability criteria for
those are still lacking.
The basic concept behind artificial
neural networks (ANN) was
inspired by the human nervous
system, the basic element of which
is the neuron. Like its biological
counterpart, an artificial neuron
is a multi-input, single-output element,
which is organized into networks
that give rise to multi-input,
multi-output (MIMO) systems. The
strengths between the neuron interconnections
can be varied, which
establishes the basis for the ability
neering, " ISBN: 978-3902655110, 2010.
22. Banaszuk, A. and A. Annaswamy, Control
of Combustion Instability, in The Impact of
Control Technology: Overview, Success Stories,
and Research Challenges. Available at
www.ieeecss.org ., IEEE Control Systems Society,
pp. 207-208, 2011.
23. Krstic, M. and A. Banaszuk, Multivariable
adaptive control of instabilities arising in jet
engines, Control Eng. Pract., vol. 14, no. 7, pp.
833-842, 2006.
24. Sardarmehni, T., and others, Robust predictive
control of lambda in internal combustion
engines using neural networks, Arch. Civ.
Mech. Eng., 13(4), pp. 432-443, 2013.
25. Hangos, K.M., J. Bokor, and G. Szederkényi,
" Analysis and Control of Nonlinear Process
Systems, " 2004th ed. London : New York:
Springer, 2004.
26. Tatjewski, P., " Advanced Control of Industrial
Processes: Structures and Algorithms. "
Springer, 2007.
27. Astrom, K.J. and D. B. Wittenmark, " Adaptive
Control, " 2nd ed., Mineola, N.Y: Dover
Publications, 2008.
28. Astrom K. and B. Wittenmark, " ComputerControlled
Systems: Theory and Design, " 3rd
ed., Mineola, N.Y: Dover Publications, 2011.
29. Grüne, L. and J. Pannek, " Nonlinear Model Predictive
Control: Theory and Algorithms, " 2011
edition. London ; New York: Springer, 2011.
30. Zelei, A. and G. Stépán, Case studies for computed
torque control of constrained underactuated
systems, Mech. Eng., 56 (1), pp. 73-80,
2012.
31. Magyar, B. and G. Stépán, Time-optimal computed-torque
control in contact transitions,
Mech. Eng., 56 (1), pp. 43-47, 2012.
32. Siqueira, D., P. Paglione, and F. J. O. Moreira,
Robust fixed structure output feedback flight
control law synthesis and analysis using singular
structured value, Aerosp. Sci. Technol.,
30 (1), pp. 102-107, 2013.
33. Havlena, V., J. Findejs, Application of model
predictive control to advanced combustion
control, Control Engineering Practice, 13 (6),
pp. 671-680, June 2005.
http://www.ieeecss.org http://www.ieeecss.org http://www.carbon http://www.trust.com/media/147147/j7971_ctl058_ad http://www.analyticjournal.de/ http://www.analyticjournal.de/im http://www.Che.Com
Chemical Engineering August 2014

Table of Contents for the Digital Edition of Chemical Engineering August 2014
