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International Journal of Turbo & Jet-Engines

Ed. by Sherbaum, Valery / Erenburg, Vladimir


IMPACT FACTOR 2018: 0.863

CiteScore 2018: 0.66

SCImago Journal Rank (SJR) 2018: 0.211
Source Normalized Impact per Paper (SNIP) 2018: 0.625

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0334-0082
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Volume 36, Issue 2

Issues

Model Predictive Control and Controller Parameter Optimisation of Combustion Instabilities

I. Yazar
  • Corresponding author
  • Eskisehir Vocational School, Department of Mechatronics, Eskisehir Osmangazi Univesity, Industrial Zone Campus, Eskisehir 26110, Turkey
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  • Other articles by this author:
  • De Gruyter OnlineGoogle Scholar
/ F. Caliskan
  • Faculty of Electrical and Electronics Engineering, Istanbul Technical University, Ayazaga Campus, Istanbul, Turkey
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  • De Gruyter OnlineGoogle Scholar
/ R. Vepa
Published Online: 2018-04-18 | DOI: https://doi.org/10.1515/tjj-2017-0062

Abstract

In this paper the application of model predictive control (MPC) to a two-mode model of the dynamics of the combustion process is considered. It is shown that the MPC by itself does not stabilize the combustor and the control gains obtained by applying the MPC algorithms need to be optimized further to ensure that the phase difference between the two modes is also stable. The results of applying the algorithm are compared with the open loop model amplitude responses and to the closed loop responses obtained by the application of a direct adaptive control algorithm. It is shown that the MPC coupled with the cost parameter optimisation proposed in the paper, always guarantees the closed loop stability, a feature that may not always be possible with an adaptive implementations.

Keywords: combustion instability; thermosacoustic wave; active combustion control; adaptive control; model predictive control; particle swarm optimization

PACS: 2010; Flow control; 47.85.L-; Flow instabilities general; 47.20.-k; Control theory in mathematical physics; 02.30.Yy; Combustion reactive flows; 47.70.Pq

Present address: I. Yazar, Department of Mechatronics, Eskisehir Osmangazi University, Eskisehir Vocational School, Industrial Zone Campus, Eskisehir, Turkey

References

  • 1.

    Rijke PL. Notiz über eine neue Art, die in einer an beiden Enden offenen Röhre enthaltene Luft in Schwingungen zu versetzen. Annalen der Physik und Chemie. 1859;183(6):339–43.CrossrefGoogle Scholar

  • 2.

    Vepa R. Dynamic modelling, simulation and control of energy generation, Lecture notes in Energy 20, 1st ed. London: Springer-Verlag, 2013:359–60. ISBN 978-1-4471-5400-6.Google Scholar

  • 3.

    Feldman KT. Review of the literature on Rijke thermoacoustic phenomena. J Sound Vib. 1968;7(1):83–89.CrossrefGoogle Scholar

  • 4.

    Bisio G, Rubatto G. Sondhauss and Rijke oscillations – thermodynamic analysis, possible applications and analogies. Energy. 1999;24(2):117–31.CrossrefGoogle Scholar

  • 5.

    Raun RL, Beckstead MW, Finlinson JC, Brooks KP. Review of Rijke tubes, Rijke burners and related devices. Prog Energy Combustion Sci. 1993;19(4):313–64.CrossrefGoogle Scholar

  • 6.

    Heckl MA. Active control of the noise from a Rijke tube. J Sound Vib. 1988;124(1):117–33.CrossrefGoogle Scholar

  • 7.

    Hantschk CC, Vortmeyer D. Numerical simulation of self-excited thermoacoustic instabilities in a Rijke tube. J Sound Vib. 1999;227(3):511–22.CrossrefGoogle Scholar

  • 8.

    Matveev K. Thermoacoustic Instabilities in the Rijke tube, experiments and modeling. Ph. D. Dissertation, Pasadena, Ca., USA: California Institute of Technology, 2003.Google Scholar

  • 9.

    Ćosić B, Bobusch BC, Moeck JP, Paschereit CO. Open-loop control of combustion instabilities and the role of the flame response to two-frequency forcing. J Eng Gas Turbines Power. 2012;134(6):061502.Web of ScienceCrossrefGoogle Scholar

  • 10.

    Annaswamy AM, Ghoniem AF. Active control of combustion instability: theory and practice. IEEE Control Syst Mag. 2002;22(6):37–54.CrossrefGoogle Scholar

  • 11.

    Dowling AP, Morgans AS. Feedback control of combustion oscillations. Annu Rev Fluid Mech. 2005;37:151–82.Web of ScienceCrossrefGoogle Scholar

  • 12.

    Hong BS, Ray A, Yang V. Wide-range robust control of combustion instability. Combust Flame. 2002;128(3):242–58.CrossrefGoogle Scholar

  • 13.

    Annaswamy AM, Fleil M, Rumsey JW, Prasanth R, Hathout JP, Ghoniem AF. Thermoacoustic instability: model-based optimal control designs and experimental validation. IEEE Trans Control Syst Technol. 2000;8(6):905–18.CrossrefGoogle Scholar

  • 14.

    Jain H, Ananthkrishnan N, Culick F. Feedback-linearization-based adaptive control and estimation of a nonlinear combustion instability model. AIAA Guidance, Navigation, and Control Conference and Exhibit, 2005. DOI:.CrossrefGoogle Scholar

  • 15.

    Guyot D, Rößler M, Bothien MR, Paschereit CO. Active control of combustion instability using pilot and premix fuel modulation, 14th International Congress on Sound and Vibration, ICSV14, Cairns, Australia, 2007. Available at: https://www.acoustics.asn.au/conference_proceedings/ICSV14/papers/p235.pdf

  • 16.

    Krstic M, Krupadanam A, Jacobson C. Self-tuning control of a nonlinear model of combustion instabilities. IEEE Trans Control Syst Tech. 1999;7(4):424–36.CrossrefGoogle Scholar

  • 17.

    Yi T, Santavicca DA. Flame transfer functions for liquid-fueled swirl-stabilized turbulent lean direct fuel injection combustion. J Eng Gas Turbines Power. 2010;132(2):021506.Web of ScienceCrossrefGoogle Scholar

  • 18.

    Rosentsvit L, Levy Y, Erenburg V, Sherbaum V, Ovcharenko V, Chudnovsky B, et al. Extension of the combustion stability range in dry low NOx lean premixed gas turbine combustor using a fuel rich annular pilot burner. J Eng Gas Turbines Power. 2014;136(5):051509.CrossrefWeb of ScienceGoogle Scholar

  • 19.

    Hervas JR, Zhao D, Reyhanoglu M. Observer–based control of Rijke-type combustion instability, AIP Conference Proceedings. 2014; 1637: 899. DOI: .CrossrefGoogle Scholar

  • 20.

    Akhmadullin AN, Ahmethanov EN, Iovleva OV, Mitrofanov GA. Combustion instability control in the model of combustion chamber. J Phys Conf Ser. 2013;479:012004.CrossrefGoogle Scholar

  • 21.

    Culick FE. Combustion instabilities in liquid-fueled propulsion systems – AGARD, 1988. Available at: https://authors.library.caltech.edu/22028/1/307_Culick_FEC_1988.pdf. Accessed: 3 Apr 2018.

  • 22.

    Culick FE. Nonlinear behavior of acoustic waves in combustion chambers – I. Acta Astronaut. 1976;3(9–10):715–34.CrossrefGoogle Scholar

  • 23.

    Fung YT, Yang V, Sınha A. Active control of combustion instabilities with distributed actuators. Combustion Sci Technol. 1991;78(4–6):217–45.CrossrefGoogle Scholar

  • 24.

    Paparizos L, Culick FE. The two-mode approximation to nonlinear acoustics in combustion chambers I. Exact solution for second order acoustics. Combustion Sci Technol. 1989;65(1):39–65.CrossrefGoogle Scholar

  • 25.

    Fung YT, Yang V. Active control of nonlinear pressure oscillations in combustion chambers. J Prop Power. 1992;8:1282–89.CrossrefGoogle Scholar

  • 26.

    Yang V, Kim SI, Culick FE. Third-order nonlinear acoustic waves and triggering of pressure oscillations in combustion chambers, Part I: longitudinal modes, AIAA-87-1873, AIAA/SAE/ASME/ASEE 23rd Joint Propulsion Conf., San Diego, CA, USA, 1987:1–9.Google Scholar

  • 27.

    Culick FE. Some recent results for nonlinear acoustics in combustion chambers. AIAA J. 1994;32(1):146–69.CrossrefGoogle Scholar

  • 28.

    Hong BS, Yang V, Ray A. Robust feedback control of combustion instability with modeling uncertainty. Combust Flame. 2000;120(1–2):91–106.CrossrefGoogle Scholar

  • 29.

    Wijewardana S, Shaheed MH, Vepa R. Optimum power output control of a wind turbine rotor. Int J Rotating Mach. 2016;1–8. DOI:CrossrefWeb of ScienceGoogle Scholar

  • 30.

    Kennedy J, Eberhart R. Particle swarm optimization. Proceedings of ICNN’95 – International Conference on Neural Networks. DOI:.CrossrefGoogle Scholar

  • 31.

    Parsopoulos KE, Vrahatis MN. Recent approaches to global optimization problems through particle swarm optimization. Nat Comput. 2002;1:235–306. Available at: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.301.8319&rep=rep1&type=pdf.Crossref

  • 32.

    Gharghory SM, Kamal HA. Optimal tuning of PID controller using adaptive hybrid particle swarm optimization algorithm. Int J Comput Commun Control. 2012;7(1):101.CrossrefWeb of ScienceGoogle Scholar

  • 33.

    Mohammadi E, Montazeri-Gh M, Khalaf P. Metaheuristic design and optimization of fuzzy-based gas turbine engine fuel controller using hybrid invasive weed optimization/particle swarm optimization algorithm. J Eng Gas Turbines Power. 2013;136(3):031601.Web of ScienceCrossrefGoogle Scholar

  • 34.

    Zhang Q, Ogren RM, Kong SC. Application of improved artificial bee colony algorithm to the parameter optimization of a diesel engine with pilot fuel injections. J Eng Gas Turbines Power. 2017;139(11):112801.Web of ScienceCrossrefGoogle Scholar

  • 35.

    Culick FE. Unsteady motions in combustion chambers for propulsion systems. RTO AGARDograph, AG-AVT-039, 2006. Available at: www.dtic.mil/get-tr-doc/pdf?AD=ADA466461. Accessed: 3 Apr 2018.

About the article

Received: 2017-12-18

Accepted: 2018-02-01

Published Online: 2018-04-18

Published in Print: 2019-05-27


This study was supported from Eskisehir Osmangazi University fund of scientific research project No. 2015-975.


Citation Information: International Journal of Turbo & Jet-Engines, Volume 36, Issue 2, Pages 185–194, ISSN (Online) 2191-0332, ISSN (Print) 0334-0082, DOI: https://doi.org/10.1515/tjj-2017-0062.

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