Robust sliding control of SEIR epidemic models

This paper is aimed at designing a robust vaccination strategy capable of eradicating an infectious disease from a population regardless of the potential uncertainty in the parameters defining the disease. For this purpose, a control theoretic approach based on a sliding-mode control law is used. In...

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Detalles Bibliográficos
Autores: Ibeas, Asier|||0000-0001-5094-3152, De la Sen, Manuel|||0000-0001-9320-9433, Alonso-Quesada, Santiago|||0000-0002-4724-7583
Tipo de recurso: artículo
Fecha de publicación:2014
País:España
Institución:Universitat Autònoma de Barcelona
Repositorio:Dipòsit Digital de Documents de la UAB
Idioma:inglés
OAI Identifier:oai:ddd.uab.cat:215260
Acceso en línea:https://ddd.uab.cat/record/215260
https://dx.doi.org/urn:doi:10.1155/2014/104764
Access Level:acceso abierto
Palabra clave:Adaptive sliding control
Closed loop properties
Control-theoretic approach
Infectious disease
Parametric uncertainties
Saturation function
SEIR epidemic models
Vaccination strategy
Descripción
Sumario:This paper is aimed at designing a robust vaccination strategy capable of eradicating an infectious disease from a population regardless of the potential uncertainty in the parameters defining the disease. For this purpose, a control theoretic approach based on a sliding-mode control law is used. Initially, the controller is designed assuming certain knowledge of an upper-bound of the uncertainty signal. Afterwards, this condition is removed while an adaptive sliding control system is designed. The closed-loop properties are proved mathematically in the nonadaptive and adaptive cases. Furthermore, the usual sign function appearing in the sliding-mode control is substituted by the saturation function in order to prevent chattering. In addition, the properties achieved by the closed-loop system under this variation are also stated and proved analytically. The closed-loop system is able to attain the control objective regardless of the parametric uncertainties of the model and the lack of a priori knowledge on the system.