Optimal and Memristor-Based Control of A Nonlinear Fractional Tumor-Immune Model
作者机构:Department of MathematicsCollege of ScienceTaif UniversityTaif21944Saudi Arabia Department of MathematicsFaculty of ScienceZagazig UniversityZagazig44519Egypt Department of Physics and Engineering MathematicsFaculty of Electronic engineeringMenoufia UniversityMenouf32952Egypt Department of MathematicsFaculty of ScienceAl-Azher UniversityNasr City11884Egypt
出 版 物:《Computers, Materials & Continua》 (计算机、材料和连续体(英文))
年 卷 期:2021年第67卷第6期
页 面:3463-3486页
核心收录:
学科分类:07[理学] 0701[理学-数学] 070101[理学-基础数学]
基 金:funded by“Taif University Researchers Supporting Project number(TURSP-2020/160) Taif University Taif Saudi Arabia”
主 题:RDTM tumor-immune optimal control caputo derivative signal flow simulink disease-free equilibrium stability memristive lyapunov exponents poincare map
摘 要:In this article,the reduced differential transform method is introduced to solve the nonlinear fractional model of *** fractional derivatives are described in the Caputo *** solutions derived using this method are easy and very *** model is given by its signal flow ***,a simulation of the system by the Simulink of MATLAB is *** disease-free equilibrium and stability of the equilibrium point are *** of a fractional optimal control for the cancer model is *** addition,to control the system,we propose a novel modification of its *** modification is based on converting the model to a memristive one,which is a first time in the literature that such idea is used to control this type of ***,we study the system’s stability via the Lyapunov exponents and Poincare maps before and after *** order differential equations(FDEs)are commonly utilized to model systems that have memory,and exist in several physical phenomena,models in thermoelasticity field,and biological *** have been utilized to model the realistic biphasic decline manner of elastic systems and infection of diseases with a slower rate of *** are more useful than integer-order in modeling sophisticated models that contain physical phenomena.