Abstract
Time delay, where it depends on the current state and on the past situation, is often occurred in biological activities, for example, the process by which microorganism consume nutrients into their available biomass is not instantaneous. This investigation inspects the dynamic behavior of stochastic turbidostat model coupled with distributed delay and degenerate diffusion, including sufficient conditions of the extinction and the existence of a unique stationary distribution. What’s more, the existence and uniqueness of globally positive equilibrium of the exploited model are studied. The findings manifest that the turbidostat system is ergodic only when the intensity of white noise is very small. Finally, some numerical examples are proposed to indicate the validity of the theoretical results.
Similar content being viewed by others
References
Guo, H., Chen, L.: Qualitative analysis of a variable yield turbidostat model with impulsive state feedback control. J. Appl. Math. Comput. 33(1–2), 193–208 (2010)
Hu, X., Li, Z., Xiang, X.: Feedback control for a turbidostat model with ratio-dependent growth rate. J. Appl. Math. Inform. 31(3–4), 385–398 (2013)
Li, B.: Competition in a turbidostat for an inhibitory nutrient. J. Biol. Dyn. 2(2), 208–220 (2008)
Li, Z., Chen, L.: Periodic solution of a turbidostat model with impulsive state feedback control. Nonlinear Dyn. 58(3), 525–538 (2009)
Yao, Y.: Dynamics of a delay turbidostat system with contois growth rate. Math. Biosci. Eng. 16(1), 56–77 (2018)
Yao, Y., Li, Z., Xiang, H., et al.: Dynamic behaviors of a turbidostat model with Tissiet functional response and discrete delay. Adv. Differ. Equ. 2018(1), 106 (2018)
Yao, Y., Li, Z., Liu, Z.: Hopf bifurcation analysis of a turbidostat model with discrete delay. Appl. Math. Comput. 262, 267–281 (2015)
Yu, T., Yuan, S., Zhang, T.: The effect of delay interval on the feedback control for a turbidostat model. J. Frankl. Inst. (2021). https://doi.org/10.1016/j.jfranklin.2021.08.003
Mu, Y., Li, Z., Xiang, H., et al.: Bifurcation analysis of a turbidostat model with distributed delay. Nonlinear Dyn. 90, 1315–1334 (2017)
Macdonald, N.: Time lags in biological models. In: Lecture notes in biomathematics. Springer, Heidelberg (1978)
Xu, C., Yuan, S., Zhang, T.: Stochastic sensitivity analysis for a competitive turbidostat model with inhibitory nutrients. Int. J. Bifurc. Chaos 26(10), 707–723 (2016)
Yu, M., Lo, W.: Dynamics of microorganism cultivation with delay and stochastic perturbation. Nonlinear Dyn. 101(6), 501–519 (2020)
Shang, Y.: The limit behavior of a stochastic logistic model with individual time-dependent rates. J. Math. 2013, 1–7 (2013)
Li, Z., Mu, Y., Xiang, H., et al.: Mean persistence and extinction for a novel stochastic turbidostat model. Nonlinear Dyn. 97(1), 185–202 (2019)
Ma, W., Luo, X., Zhu, Q.: Practical exponential stability of stochastic age-dependent capital system with Lévy noise. Syst. Control Lett. (2020). https://doi.org/10.1016/j.sysconle.2020.104759
Xu, C., Yuan, S., Zhang, T.: Competitive exclusion in a general multi-species chemostat model with stochastic perturbations. Bull. Math. Biol. 83(1), 4 (2021)
Yu, X., Yuan, S., Zhang, T.: Asymptotic properties of a stochastic chemostat model with two distributed delays and nonlinear perturbation. Discrete Contin. Dyn. Syst. Ser. B 25(7), 2273–2290 (2020)
Rudnicki, R., Pichór, K., Tyran-Kamińska, M.: Markov Semigroups and their Applications. Dynamics of Dissipation. Springer, Berlin (2002)
Rudnicki, R., Pichór, K.: Influence of stochastic perturbation on prey–predator systems. Math. Biosci. 206(1), 108–119 (2007)
Rudnicki, R.: Asymptotic Properties of the Fokker–Planck Equation, vol. 457. Springer, Berlin, pp 517–521 (1995)
Mao, X.: Stochastic Differential Equations and Applications, 2nd edn. Horwood Publishing, Cambridge (1997)
Bao, K., Rong, L., Zhang, Q.: Analysis of a stochastic SIRS model with interval parameters. Discrete Contin. Dyn. Syst. B 24(9), 4827–4849 (2019)
Ben Arous, G., Léandre, R.: Décroissance exponentielle du noyau de la chaleur sur la diagonale (II). Probab. Theory Relat. Fields 90, 377–402 (1991)
Pichór, K., Rudnicki, R.: Stability of Markov semigroups and applications to parabolic systems. J. Math. Anal. Appl. 215, 56–74 (1997)
Higham, D.: An algorithmic introduction to numerical simulation of stochastic differential equations. SIAM Rev. 433, 525–546 (2001)
Gao, M., Jiang, D., Hayat, T.: The threshold of a chemostat model with single-species growth on two nutrients under telegraph noise. Commun. Nonlinear Sci. Numer. Simul. 75, 160–173 (2019)
Acknowledgements
The research is supported by the Natural Science Foundation of China (No. 11871473), Shandong Provincial Natural Science Foundation (Nos. ZR2019MA010, ZR2019MA006, ZR2020MA039) and the Fundamental Research Funds for the Central Universities (No. 19CX02055A).
Author information
Authors and Affiliations
Contributions
DJ designed the research and methodology. XM wrote the original draft. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflict of interest.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Mu, X., Jiang, D., Alsaedi, A. et al. A stochastic turbidostat model coupled with distributed delay and degenerate diffusion: dynamics analysis. J. Appl. Math. Comput. 68, 2761–2786 (2022). https://doi.org/10.1007/s12190-021-01639-1
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12190-021-01639-1