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The Caputo vs. Caputo-Fabrizio operators in modeling of heat transfer process

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In the paper two non-integer order, state space models of heat transfer process are compared. The first uses a known Caputo operator and the second – a new operator proposed by Caputo and Fabrizio in 2015. Both discussed models are modifications of a known, integer order, state space, semigroup model of heat transfer process. Parameters of both models were identified by means of optimization of MSE cost function with the use of simplex method, available in MATLAB. Both proposed models have been compared in the aspect of accuracy and convergence. Analytical and numerical results show that the Caputo-Fabrizio model is faster convergent and easier to implement than the Caputo model. However, its accuracy in the sense of MSE cost function is worse.
Rocznik
Strony
501--507
Opis fizyczny
Bibliogr. 25 poz., rys., wykr., tab.
Twórcy
  • AGH University, 30 Mickiewicza Ave., 30-059 Krakow, Poland
autor
  • AGH University, 30 Mickiewicza Ave., 30-059 Krakow, Poland
autor
  • HVS in Tarnow, 8 Mickiewicza St., 33-100 Tarnow, Poland
autor
  • AGH University, 30 Mickiewicza Ave., 30-059 Krakow, Poland
Bibliografia
  • [1] R. Caponetto, G. Dongola, L. Fortuna, and I. Petras, Fractional Order Systems. Modeling and Control Applications, World Scientific Series on Nonlinear Science, Series A, vol. 72, World Scientific Publishing, 2010.
  • [2] S. Das, Functional Fractional Calculus for System Identification and Controls, Springer, Berlin, 2008.
  • [3] S. Das and I. Pan, Intelligent Fractional Order Systems and Control. An Introduction, Springer, 2013.
  • [4] A. Dzielinski, D. Sierociuk, and G. Sarwas, “Some applications of fractional order calculus”, Bull. Pol. Ac.: Tech. 58(4), 583–592 (2010).
  • [5] I. Podlubny, Fractional Differential Equations, Academic Press, San Diego, 1991.
  • [6] D. Sierociuk, T. Skovranek, M. Macias, I. Podlubny, I. Petras, A. Dzielinski, and P. Ziubinski, “Diffusion process modeling by using fractional-order models”, Applied Mathematics and Computation 257(1), 2–11 (2015).
  • [7] E. Popescu, “On the fractional Cauchy problem associated with a Feller semigroup”, Mathematical Reports 12(2), 181–188 (2010).
  • [8] M. Dlugosz and P. Skruch, “The application of fractional-order models for thermal process modelling inside buildings”, Journal of Building Physics 1(1), 1–13 (2015).
  • [9] W. Mitkowski, “Approximation of fractional diffusion-wave equation”, Acta Mechanica et Automatica 5(2), 65–68 (2011).
  • [10] R. Brociek and D. Slota, “Application and comparison of the intelligent algorithms to solve the fractional heat conduction inverse problem”, Journal of Information Technology and Control 45(2), 184–194 (2016).
  • [11] R. Brociek and D. Slota, “Application of real ant colony optimization algorithm to solve space and time fractional heat conduction inverse problem”, Journal of Information Technology and Control 46(2), 171–182 (2017).
  • [12] K. Oprzędkiewicz, W. Mitkowski, and E. Gawin, “Modeling heat distribution with the use of a non-integer order, state space model”, International Journal of Applied Mathematics and Computer Science 26(4), 749–756 (2016).
  • [13] K. Oprzędkiewicz, W. Mitkowski, and E. Gawin, “Parameter identification for non integer order, state space models of heat plant”, in: MMAR 2016: 21th International Conference on Methods and Models in Automation and Robotics: 29 August – 01 September 2016, Miedzyzdroje, Poland ISBN: 978-1-5090-1866-6. – ISBN: 978-83-7518-791-5, 184–188.
  • [14] K. Oprzędkiewicz and E. Gawin, “Non integer order, state space model for one dimensional heat transfer process”, Archives of Control Sciences, ISSN 1230-2384, 26(2), 261–275 (2016), full text avalilable at: https://www-1degruyter-1com- 1atoz.wbg2.bg.agh.edu.pl/downloadpdf/j/acsc.2016.26.issue-2/acsc-2016-0015/acsc-2016-0015.xml.
  • [15] K. Oprzędkiewicz, “Non integer order, state space model of heat transfer process using Caputo-Fabrizio operator”, Bull. Pol. Ac.: Tech. 66(3), 249–255 (2018).
  • [16] N.A. Sheikh, F. Ali, M. Saqib, I. Khan, S.A.A. Jan, A.S. Alshomrani, and M.S. Alghamdi, Comparison and analysis of the Atangana-Baleanu and Caputo–Fabrizio fractional derivatives for generalized Casson fluid model with heat generation and chemical reaction”, Results Phys. 7, 789–800 (2017).
  • [17] A. Atagana and R.T. Alqahtani, “Numerical approximation of the space-time Caputo-Fabrizio fractional derivative and application to groundwater pollution equation”, Advances in Difference Equations 156 (2016), DOI: 10.1186/s13662-016-0871-x.
  • [18] N. Al-Salti, E. Karimov, and S. Kerbal, “Boundary-value problems for fractional heat equation involving Caputo-Fabrizio derivative”, New Trends in Mathematical Sciences 4, 79–89 (2016).
  • [19] T. Kaczorek, Selected Problems in Fractional Systems Theory, Springer-Verlag, 2011.
  • [20] T. Kaczorek and K. Rogowski, Fractional Linear Systems and Electrical Circuits, Bialystok University of Technology, Bialystok, 2014.
  • [21] M. Caputo and M. Fabrizio, “A new definition of fractional derivative without singular kernel”, Progress in Fractional Differentiation and Applications 1(2), 1–13 (2015).
  • [22] T. Kaczorek and K. Borawski, “Fractional descriptor continuous-time linear systems described by the Caputo-Fabrizio derivative”, Int. J. Appl. Math. Comput. Sci. 26(3), 533–541 (2016).
  • [23] J. Paneva-Konovska, “Convergence of series in three parametric Mittag-Leffler functions”, Mathematica Slovaca 64(1), 73–84 (2014).
  • [24] P. Bania, J. Baranowski, and M. Zagorowska, “Convergence of Laguerre impulse response approximation for noninteger order systems”, Mathematical Problems in Engineering, Vol 2016, Article ID 9258437, 13 pages http://dx.doi.org/10.1155/2016/9258437.
  • [25] R. Isermann and M. Muenchhof, Identification of Dynamic Systems. An Introduction with Applications, Springer 2011.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-e1727174-7cb6-48d0-9e46-d0f2f946f708
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