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Fractional optimal control approach to the diabetics model

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Diabetes mellitus is one of the most critical diseases, affecting millions of people around the world. This work deals with the fractional optimal control of the dynamics of the population model on diabetes. This framework is based on the fractional order differential problems that describe the population before and after diabetes involving some health problems. We consider the Caputo derivatives for the study of the proposed model. The maximum principle of Pontryagin is utilized to derive the necessary conditions for the optimality of a dynamical system. Using a forward-backward sweep approach with the generalized Euler method accomplishes numerical solutions of formulated issues.
Rocznik
Strony
71--82
Opis fizyczny
Bibliogr. 32 poz., tab.
Twórcy
  • School of Mathematics and Statistics, Qujing Normal University, Qujing 655011, China
  • Department of Mathematics, University of Engineering and Technology, Lahore 58400, Pakistan
autor
  • Department of Mathematics, University of Engineering and Technology, Lahore 58400, Pakistan
  • Department of Mathematics, University of Management and Technology, Lahore 54770, Pakistan
Bibliografia
  • [1] Tariq, M., Ahmad, H., Shaikh, A.A., Ntouyas, S. K., Hincal, E., & Qureshi, S. (2023). Fractional Hermite Hadamard-type inequalities for differentiable preinvex mappings and applications to modified Bessel and q-Digamma functions. Mathematical and Computational Applications,28(6), 108.
  • [2] Leon, B.S., Alanis, A.Y., Sanchez, E.N., Ornelas-Tellez, F., & Ruiz-Velazquez, E. (2013). Neural inverse optimal control applied to type 1 diabetes mellitus patients. Analog Integrated Circuits and Signal Processing, 76(3), 343-352.
  • [3] Himsworth, H.P. (1949). The syndrome of diabetes mellitus and its causes. The Lancet, 253(6551), 465-473.
  • [4] Jajarmi, A., Ghanbari, B., & Baleanu, D. (2019). A new and efficient numerical method for the fractional modeling and optimal control of diabetes and tuberculosis co-existence. Chaos: An Interdisciplinary Journal of Nonlinear Science, 29(9), 093111.
  • [5] Sweilam, N.H., Al-Mekhlafi, S.M., & Baleanu, D. (2019). Optimal control for a fractional tuberculosis infection model including the impact of diabetes and resistant strains. Journal of Advanced Research, 17, 125-137.
  • [6] Ameen, I., Baleanu, D., & Ali, H.M. (2020). An efficient algorithm for solving the fractional optimal control of SIRV epidemic model with a combination of vaccination and treatment. Chaos, Solitons & Fractals, 137, 109892.
  • [7] Omame, A., Nwajeri, U.K., Abbas, M., & Onyenegecha, C.P. (2022). A fractional order control model for diabetes and COVID-19 co-dynamics with Mittag-Leffler function. Alexandria Engineering Journal, 61(10), 7619-7635.
  • [8] Ma, H. (2022). Fractal variational principle for an optimal control problem. Journal of Low Frequency Noise, Vibration and Active Control, 41(4), 1523-1531.
  • [9] Jajarmi, A., Baleanu, D., Sajjadi, S.S., & Nieto, J.J. (2022). Analysis and some applications of a regularized ψ-Hilfer fractional derivative. Journal of Computational and Applied Mathematics,415, 114476.
  • [10] Baleanu, D., Jajarmi, A., Mohammadi, H., & Rezapour, S. (2020). A new study on the mathematical modelling of human liver with Caputo-Fabrizio fractional derivative. Chaos, Solitons & Fractals, 134, 109705.
  • [11] Qureshi, S., Argyros, I.K., Soomro, A., Gdawiec, K., Shaikh, A.A., & Hincal, E. (2023). A new optimal root-finding iterative algorithm: local and semilocal analysis with polynomiography. Numerical Algorithms, 1-31.
  • [12] Baleanu, D., Ghassabzade, F.A., Nieto, J.J., & Jajarmi, A. (2022). On a new and generalized fractional model for a real cholera outbreak. Alexandria Engineering Journal, 61(11), 9175-9186.
  • [13] Defterli, O., Baleanu, D., Jajarmi, A., Sajjadi, S.S., Alshaikh, N., & Asad, J.H. (2022). Fractional treatment: An accelerated mass-spring system. Romanian Reports in Physics, 74, 122.
  • [14] Li, X., Wang, D., & Saeed, T. (2022). Multi-scale numerical approach to the polymer filling process in the weld line region. Facta Universitatis, Series: Mechanical Engineering, 20(2), 363-380.
  • [15] Boutayeb, A., & Chetouani, A. (2007). A population model of diabetes and pre-diabetes. International Journal of Computer Mathematics, 84(1), 57-66.
  • [16] Jajarmi, A., Ghanbari, B., & Baleanu, D. (2019). A new and efficient numerical method for the fractional modeling and optimal control of diabetes and tuberculosis co-existence. Chaos: An Interdisciplinary Journal of Nonlinear Science, 29(9), 093111.
  • [17] Almeida, R., Pooseh, S., & Torres, D.F. (2015). Computational Methods in the Fractional Calculus of Variations. London: Imperial College Press.
  • [18] Shaikh, F., Shaikh, A.A., Hincal, E., & Qureshi, S. (2023). Comparative analysis of numerical simulations of blood flow through the segment of an artery in the presence of stenosis. Journal of Applied Mathematics and Computational Mechanics, 22(2).
  • [19] He, J.H. (2020). Lagrange crisis and generalized variational principle for 3D unsteady flow. International Journal of Numerical Methods for Heat & Fluid Flow, 30(3), 1189-1196.
  • [20] Agrawal, O.P. (2004). A general formulation and solution scheme for fractional optimal control problems. Nonlinear Dynamics, 38(1), 323-337.
  • [21] Agrawal, O.P. (2008). A formulation and numerical scheme for fractional optimal control problems.Journal of Vibration and Control, 14(9-10), 1291-1299.
  • [22] Frederico, G.S., & Torres, D.F. (2008). Fractional conservation laws in optimal control theory. Nonlinear Dynamics, 53(3), 215-222.
  • [23] Tricaud, C., & Chen, Y. (2010). Time-optimal control of systems with fractional dynamics. International Journal of Differential Equations, ID 461048, DOI: 10.1155/2010/461048.
  • [24] Agrawal, O.P., Defterli, O., & Baleanu, D. (2010). Fractional optimal control problems with several state and control variables. Journal of Vibration and Control, 16(13), 1967-1976.
  • [25] Agrawal, P., & Baleanu, D. (2007). A hamiltonian formulation and a direct numerical scheme for fractional optimal control problems. Journal of Vibration and Control, 13(9-10), 1269-1281.
  • [26] Atangana, A., & Baleanu, D. (2016). New fractional derivatives with nonlocal and non-singular kernel: theory and application to heat transfer model. Thermal Science, 20, 763-769.
  • [27] Pooseh, S., Almeida, R., & Torres, D.F. (2014). Fractional order optimal control problems with free terminal time. Journal of Industrial and Management Optimization, 10(2), 363-381.
  • [28] Agrawal, O.P. (2004). A general formulation and solution scheme for fractional optimal control problems. Nonlinear Dynamics, 38(1), 323-337.
  • [29] He, C.H., & Liu, C. (2023). Fractal dimensions of a porous concrete and its effect on the concrete’s strength. Facta Universitatis, Series: Mechanical Engineering, 21(1), 137-150.
  • [30] Ding, Y., Wang, Z., & Ye, H. (2011). Optimal control of a fractional-order HIV-immune system with memory. IEEE Transactions on Control Systems Technology, 20(3), 763-769.
  • [31] Agrawal, P. (2008). A formulation and numerical scheme for fractional optimal control problems. Journal of Vibration and Control, 14(9-10), 1291-1299.
  • [32] Ding, Y., Wang, Z., & Ye, H. (2011). Optimal control of a fractional-order HIV-immune system with memory. IEEE Transactions on Control Systems Technology, 20(3), 763-769
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2024).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-686f79f0-99f1-427b-8eeb-a8ca9de6c36f
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