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Fuzzy logic and Lyapunov-based non-linear controllers for HCV infection.
IET Systems Biology ( IF 2.3 ) Pub Date : 2021-04-01 , DOI: 10.1049/syb2.12014
Ali Hamza 1 , Iftikhar Ahmad 1 , Muhammad Uneeb 1
Affiliation  

Hepatitis C is the liver disease caused by the Hepatitis C virus (HCV) which can lead to serious health problems such as liver cancer. In this research work, the non-linear model of HCV having three state variables (uninfected hepatocytes, infected hepatocytes and virions) and two control inputs has been taken into account, and four non-linear controllers namely non-linear PID controller, Lyapunov Redesign controller, Synergetic controller and Fuzzy Logic-Based controller have been proposed to control HCV infection inside the human body. The controllers have been designed for the anti-viral therapy in order to control the amount of uninfected hepatocytes to the desired safe limit and to track the amount of infected hepatocytes and virions to their reference value which is zero. One control input is the Pegylated interferon (peg-IFN-α) which acts in reducing the infected hepatocytes and the other input is ribavirin which blocks the production of virions. By doing so, the uninfected hepatocytes increase and achieve the required safe limit. Lyapunov stability analysis has been used to prove the stability of the whole system. The comparative analysis of the proposed nonlinear controllers using MATLAB/Simulink have been done with each other and with linear PID. These results depict that the infected hepatocytes and virions are reduced to the desired level, enhancing the rate of sustained virologic response (SVR) and reducing the treatment period as compared with previous strategies introduced in the literature.

中文翻译:

用于HCV感染的模糊逻辑和基于Lyapunov的非线性控制器。

丙型肝炎是由丙型肝炎病毒(HCV)引起的肝脏疾病,可导致严重的健康问题,例如肝癌。在这项研究工作中,考虑了具有三个状态变量(未感染的肝细胞,感染的肝细胞和病毒体)和两个控制输入的HCV非线性模型,并且使用了四个非线性控制器,即非线性PID控制器,Lyapunov Redesign为了控制HCV在人体内的感染,已经提出了一种控制控制器,协同控制器和基于模糊逻辑的控制器。已经设计了用于抗病毒治疗的控制器,以便将未感染的肝细胞的数量控制到所需的安全极限,并将感染的肝细胞和病毒体的数量跟踪到其参考值零。一个对照输入是聚乙二醇化干扰素(peg-IFN-α),其可减少感染的肝细胞,而另一个输入是利巴韦林,其阻断病毒体的产生。这样,未感染的肝细胞增加并达到所需的安全极限。Lyapunov稳定性分析已被用来证明整个系统的稳定性。使用MATLAB / Simulink对提出的非线性控制器进行了相互比较,并与线性PID进行了比较分析。这些结果表明,与先前文献中介绍的策略相比,被感染的肝细胞和病毒粒子减少到所需水平,从而提高了持续病毒学应答(SVR)的速度并缩短了治疗时间。这样,未感染的肝细胞增加并达到所需的安全极限。Lyapunov稳定性分析已被用来证明整个系统的稳定性。使用MATLAB / Simulink对提出的非线性控制器进行了相互比较,并与线性PID进行了比较分析。这些结果表明,与先前文献中介绍的策略相比,被感染的肝细胞和病毒粒子减少到所需水平,从而提高了持续病毒学应答(SVR)的速度并缩短了治疗时间。这样,未感染的肝细胞增加并达到所需的安全极限。Lyapunov稳定性分析已被用来证明整个系统的稳定性。使用MATLAB / Simulink对提出的非线性控制器进行了相互比较,并与线性PID进行了比较分析。这些结果表明,与先前文献中介绍的策略相比,被感染的肝细胞和病毒粒子减少到所需水平,从而提高了持续病毒学应答(SVR)的速度并缩短了治疗时间。使用MATLAB / Simulink对提出的非线性控制器进行了相互比较,并与线性PID进行了比较分析。这些结果表明,与先前文献中介绍的策略相比,被感染的肝细胞和病毒粒子减少到所需水平,从而提高了持续病毒学应答(SVR)的速度并缩短了治疗时间。使用MATLAB / Simulink对提出的非线性控制器进行了相互比较,并与线性PID进行了比较分析。这些结果表明,与先前文献中介绍的策略相比,被感染的肝细胞和病毒粒子减少到所需水平,从而提高了持续病毒学应答(SVR)的速度并缩短了治疗时间。
更新日期:2021-04-01
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