tetano
Editor, Senior Moderator
J Theor Biol. 2019 Aug 23. pii: S0022-5193(19)30327-3. doi: 10.1016/j.jtbi.2019.08.015. [Epub ahead of print]
[h=1]Observer-Based Adaptive PI Sliding Mode Control of Developed Uncertain SEIAR Influenza Epidemic Model Considering Dynamic Population.[/h] Mehra AHA[SUP]1[/SUP], Zamani I[SUP]2[/SUP], Abbasi Z[SUP]3[/SUP], Ibeas A[SUP]4[/SUP].
[h=3]Author information[/h] 1 Electrical and Electronic Engineering Department, Shahed University, Tehran, Iran. Electronic address: a.amirimehra@shahed.ac.ir. 2 Electrical and Electronic Engineering Department, Shahed University, Tehran, Iran. Electronic address: zamaniiman@shahed.ac.ir. 3 Electrical and Computer Engineering Department, Qom University of Technology, Qom, Iran. Electronic address: abbasi.z@qut.ac.ir. 4 Departament de Telecomunicaci? i Enginyeria de Sistemes, Escolad'Enginyeria. UniversitatAut?noma de Barcelona, Barcelona, Spain. Electronic address: asier.ibeas@uab.cat.
[h=3]Abstract[/h] This paper presents a new Susceptible, Exposed, Infected, Asymptomatic, and Recovered individuals (SEIAR) model for influenza considering a dynamic population. In the given model, the possibility of transmission of asymptomatic individuals (infectious with no visible symptoms) to infected individuals (infectious exhibiting symptoms) is considered. The basic reproduction number and the equilibrium points of the new model are given while the stability of the equilibrium points is analyzed by using the Jacobian matrix. Then a multi-controller scheme consisting of a parallel controller defined by two control inputs (vaccination and antiviral treatment) is given where both of them are based on Proportional-Integral (PI) and sliding mode controllers, which are parameterized adaptively to guarantee the convergence of trajectories to the sliding surface with minimum amount of chattering. The proposed control scheme is able to asymptotically stabilize the SEIAR model in the sense of eradication of the infected and susceptible individuals. Moreover, a (reduced-order) observer is designed to estimate the actual state variables that are used in the implementation of the control signals. By using MATLAB? software, a comprehensive simulation and evaluation of treatment and performance are carried out to support the presented theoretical results.
Copyright ? 2019. Published by Elsevier Ltd.
[h=4]KEYWORDS:[/h] Adaptive PI sliding mode; Dynamic population; Lyapunov stability; Observer-based control; SEIAR model
PMID: 31449819 DOI: 10.1016/j.jtbi.2019.08.015
[h=1]Observer-Based Adaptive PI Sliding Mode Control of Developed Uncertain SEIAR Influenza Epidemic Model Considering Dynamic Population.[/h] Mehra AHA[SUP]1[/SUP], Zamani I[SUP]2[/SUP], Abbasi Z[SUP]3[/SUP], Ibeas A[SUP]4[/SUP].
[h=3]Author information[/h] 1 Electrical and Electronic Engineering Department, Shahed University, Tehran, Iran. Electronic address: a.amirimehra@shahed.ac.ir. 2 Electrical and Electronic Engineering Department, Shahed University, Tehran, Iran. Electronic address: zamaniiman@shahed.ac.ir. 3 Electrical and Computer Engineering Department, Qom University of Technology, Qom, Iran. Electronic address: abbasi.z@qut.ac.ir. 4 Departament de Telecomunicaci? i Enginyeria de Sistemes, Escolad'Enginyeria. UniversitatAut?noma de Barcelona, Barcelona, Spain. Electronic address: asier.ibeas@uab.cat.
[h=3]Abstract[/h] This paper presents a new Susceptible, Exposed, Infected, Asymptomatic, and Recovered individuals (SEIAR) model for influenza considering a dynamic population. In the given model, the possibility of transmission of asymptomatic individuals (infectious with no visible symptoms) to infected individuals (infectious exhibiting symptoms) is considered. The basic reproduction number and the equilibrium points of the new model are given while the stability of the equilibrium points is analyzed by using the Jacobian matrix. Then a multi-controller scheme consisting of a parallel controller defined by two control inputs (vaccination and antiviral treatment) is given where both of them are based on Proportional-Integral (PI) and sliding mode controllers, which are parameterized adaptively to guarantee the convergence of trajectories to the sliding surface with minimum amount of chattering. The proposed control scheme is able to asymptotically stabilize the SEIAR model in the sense of eradication of the infected and susceptible individuals. Moreover, a (reduced-order) observer is designed to estimate the actual state variables that are used in the implementation of the control signals. By using MATLAB? software, a comprehensive simulation and evaluation of treatment and performance are carried out to support the presented theoretical results.
Copyright ? 2019. Published by Elsevier Ltd.
[h=4]KEYWORDS:[/h] Adaptive PI sliding mode; Dynamic population; Lyapunov stability; Observer-based control; SEIAR model
PMID: 31449819 DOI: 10.1016/j.jtbi.2019.08.015