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Dynamical analysis of fractional-order chemostat model

  • Received: 03 March 2021 Accepted: 20 April 2021 Published: 22 April 2021
  • The fractional-order differential equations is studied to describe the dynamic behaviour of a chemostat system. The integer-order chemostat model in the form of the ordinary differential equation is extended to the fractional-order differential equations. The stability and bifurcation analyses of the fractional-order chemostat model are investigated using the Adams-type predictor-corrector method. The result shows that increasing or decreasing the value of the fractional order, α, may stabilise the unstable state of a chemostat system and also may destabilised the stable state of the chemostat system depend on the predefined parameter values. The increasing the value of the initial substrate concentration, S0 may destabilise the stable state of a chemostat system and stabilise the unstable state of the system. Therefore, the running state of a fractional-order chemostat system is affected by the value of α and the value of the initial substrate concentration, S0. In actual application, the value of the initial substrate should remain at S02.54 to ensure that the chemostat system is unstable state. There will be some change in the amount of the cell mass concentration whether increase or decrease when the system is unstable. Therefore, the chemostat system can be well-controlled for the production of cell mass.

    Citation: Nor Afiqah Mohd Aris, Siti Suhana Jamaian. Dynamical analysis of fractional-order chemostat model[J]. AIMS Biophysics, 2021, 8(2): 182-197. doi: 10.3934/biophy.2021014

    Related Papers:

  • The fractional-order differential equations is studied to describe the dynamic behaviour of a chemostat system. The integer-order chemostat model in the form of the ordinary differential equation is extended to the fractional-order differential equations. The stability and bifurcation analyses of the fractional-order chemostat model are investigated using the Adams-type predictor-corrector method. The result shows that increasing or decreasing the value of the fractional order, α, may stabilise the unstable state of a chemostat system and also may destabilised the stable state of the chemostat system depend on the predefined parameter values. The increasing the value of the initial substrate concentration, S0 may destabilise the stable state of a chemostat system and stabilise the unstable state of the system. Therefore, the running state of a fractional-order chemostat system is affected by the value of α and the value of the initial substrate concentration, S0. In actual application, the value of the initial substrate should remain at S02.54 to ensure that the chemostat system is unstable state. There will be some change in the amount of the cell mass concentration whether increase or decrease when the system is unstable. Therefore, the chemostat system can be well-controlled for the production of cell mass.



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    Acknowledgments



    We would like to express our gratitude sincere for the financial support by the Universiti Tun Hussein Onn Malaysia through the grant H426.

    Conflict of interest



    No conflict of interest is declared by the authors.

    [1] Nelson MI, Sidhu HS (2005) Analysis of a chemostat model with variable yield coefficient. J Math Chem 38: 605-615. doi: 10.1007/s10910-005-6914-2
    [2] Harmand J, Lobry C, Rapaport A, et al.The chemostat: Mathematical theory of microorganism cultures, John Wiley & Sons. (2017) .
    [3] Elettreby MF, Al-Raezah AA, Nabil T (2017) Fractional-order model of two-prey one-predator system. Math Probl Eng 2017: 6714538. doi: 10.1155/2017/6714538
    [4] Cui X, Yu Y, Wang H, et al. (2016) Dynamical analysis of memristor-based fractional-order neural networks with time delay. Mod Phys Lett B 30: 1650271. doi: 10.1142/S0217984916502717
    [5] Zeinadini M, Namjoo M (2016) A numerical method for discrete fractional-order chemostat model derived from nonstandard numerical scheme. B Iran Math Soc 43: 1165-1182.
    [6] Zeinadini M, Namjoo M (2017) Approximation of fractional-order chemostat model with nonstandard finite difference scheme. Hacet J Math Stat 46: 469-482.
    [7] Garrappa R (2018) Numerical solution of fractional differential equations: A survey and a software tutorial. Mathematics 6: 16. doi: 10.3390/math6020016
    [8] Islam MR, Peace A, Medina D, et al. (2020) Integer versus fractional order seir deterministic and stochastic models of measles. Int J Env Res Pub He 17: 2014. doi: 10.3390/ijerph17062014
    [9] Nelson MI, Sidhu HS (2009) Analysis of a chemostat model with variable yield coefficient: tessier kinetics. J Math Chem 46: 303-321. doi: 10.1007/s10910-008-9463-7
    [10] Ahmed E, Hashish A, Rihan FA (2012) On fractional order cancer model. J Fract Calc Appl Anal 3: 1-6.
    [11] Sidhu HS, Nelson MI, Balakrishnan E (2015) An analysis of a standard reactor cascade and a step-feed reactor cascade for biological processes described by monod kinetics. Chem Prod Process Model 10: 27-37. doi: 10.1515/cppm-2014-0022
    [12] Alqahtani RT, Nelson MI, Worthy AL (2015) Analysis of a chemostat model with variable yield coefficient and substrate inhibition: contois growth kinetics. Chem Eng Commun 202: 332-344. doi: 10.1080/00986445.2013.836630
    [13] Ezz-Eldien SS (2018) On solving fractional logistic population models with applications. Comput Appl Math 37: 6392-6409. doi: 10.1007/s40314-018-0693-4
    [14] D'Ovidio M, Loreti P, Ahrabi SS (2018) Modified fractional logistic equation. Physica A 505: 818-824. doi: 10.1016/j.physa.2018.04.011
    [15] Khater M, Attia RAM, Lu D (2019) Modified auxiliary equation method versus three nonlinear fractional biological models in present explicit wave solutions. Math Comput Appl 24: 1.
    [16] Sayari S, El Hajji M (2019) How the fractional-order improve and extend the well-known competitive exclusion principle in the chemostat model with n species competing for a single resource? Asian Res J Math 12: 1-12. doi: 10.9734/arjom/2019/v12i330085
    [17] Isah A, Phang C (2018) Operational matrix based on Genocchi polynomials for solution of delay differential equations. J Ain Sham Eng 9: 2123-2128. doi: 10.1016/j.asej.2016.09.015
    [18] Li X, Wu R (2014) Hopf bifurcation analysis of a new commensurate fractional-order hyperchaotic system. Nonlinear Dynam 78: 279-288. doi: 10.1007/s11071-014-1439-5
    [19] De Oliveira EC, Tenreiro Machado JA (2014) A review of definitions for fractional derivatives and integral. Math Probl Eng 2014: 238459. doi: 10.1155/2014/238459
    [20] Diethelm K, Freed AD (1999) On the solution of nonlinear fractional-order differential equations used in the modeling of viscoplasticity. Scientific Computing in Chemical Engineering II Berlin: Springer, 217-224.
    [21] Toh YT, Phang C, Loh JR (2019) New predictor-corrector scheme for solving nonlinear differential equations with Caputo-Fabrizio operator. Math Method Appl Sci 42: 175-185. doi: 10.1002/mma.5331
    [22] Diethelm K, Ford NJ, Freed AD (2002) A predictor-corrector approach for the numerical solution of fractional differential equations. Nonlinear Dynam 29: 3-22. doi: 10.1023/A:1016592219341
    [23] Ghrist ML, Fornberg B, Reeger JA (2015) Stability ordinates of Adams predictor-corrector methods. BIT Numer Math 55: 733-750. doi: 10.1007/s10543-014-0528-7
    [24] Matignon D (1996) Stability results for fractional differential equations with applications to control processing. Comput Eng Syst Appl 2: 963-968.
    [25] Vinagre BM, Monje CA, Caldern AJ, et al. (2007) Fractional PID controllers for industry application. A brief introduction. J Vib Control 13: 1419-1429. doi: 10.1177/1077546307077498
    [26] Ahmed E, El-Sayed AMA, El-Saka HAA (2006) On some Routh–Hurwitz conditions for fractional order differential equations and their applications in Lorenz, Rssler, Chua and Chen systems. Physics Letters A 358: 1-4. doi: 10.1016/j.physleta.2006.04.087
    [27] Karaaslanli CC (2012) Bifurcation analysis and its applications. Numerical simulation from theory to industry Croatia: INTECH open access publisher.
    [28] Ma J, Ren W (2016) Complexity and Hopf bifurcation analysis on a kind of fractional-order IS-LM macroeconomic system. Int J Bifurcat Chaos 26: 1650181. doi: 10.1142/S0218127416501819
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