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Optimal Control and Spectral Collocation Method for Solving Smoking Models

Amr M. S. Mahdy1,*, Mohamed S. Mohamed1, Ahoud Y. Al Amiri2, Khaled A. Gepreel1
1 Department of Mathematics, College of Science, Taif University, Taif, 21944, Saudi Arabia
2 Department of Mathematics, College of Science, Bisha University, Bisha, P.O. Box 61922, Saudi Arabia
* Corresponding Author: Amr M. S. Mahdy. Email:
(This article belongs to this Special Issue: Recent Trends in Computational Methods for Differential Equations)

Intelligent Automation & Soft Computing 2022, 31(2), 899-915.

Received 11 February 2021; Accepted 10 June 2021; Issue published 22 September 2021


In this manuscript, we solve the ordinary model of nonlinear smoking mathematically by using the second kind of shifted Chebyshev polynomials. The stability of the equilibrium point is calculated. The schematic of the model illustrates our proposition. We discuss the optimal control of this model, and formularize the optimal control smoking work through the necessary optimality cases. A numerical technique for the simulation of the control problem is adopted. Moreover, a numerical method is presented, and its stability analysis discussed. Numerical simulation then demonstrates our idea. Optimal control for the model is further discussed by clarifying the optimal control through drawing before and after control. Fractional request differential equations (FDEs) are usually used to display frameworks that have memory and exist in a few thermoelasticity models and organic standards. FDEs show the realistic biphasic decline of infection of diseases but at a slower rate. FDEs are more suitable than integer order ones in modeling complex systems, such as biological systems.


Shifted second kind chebyshev; smoking model; stability; hamiltonian; lagrange multipliers; optimal control

Cite This Article

A. M. S. Mahdy, M. S. Mohamed, A. Y. Al Amiri and K. A. Gepreel, "Optimal control and spectral collocation method for solving smoking models," Intelligent Automation & Soft Computing, vol. 31, no.2, pp. 899–915, 2022.


This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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