Robust Sliding Control of SEIR Epidemic Models

Abstract

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 ofa prioriknowledge on the system.

Reinforcement learning-based decision support system for COVID-19

“…Sliding mode control, tracking control, optimal control, and adaptive control methods have been applied to control the spread of malaria, influenza, zika virus,... etc. [7] [10] , [11] , [12] . Optimal control methods are used to identify ideal intervention strategies for mitigating epidemics that accounts for the cost involved in implementing pharmaceutical or nonpharmaceutical interventions (PI or NPI).…”

Dynamics of SEIR epidemic model by optimal auxiliary functions method

“…Ibeas et al. [6] proposed a robust vaccination strategy capable of eradicating infectious diseases from a population group. For this aim, a control theoretical approach based on a sliding-mode control law is used.…”

On Confinement and Quarantine Concerns on an SEIAR Epidemic Model with Simulated Parameterizations for the COVID-19 Pandemic

“…Epidemic mathematical models in different formal frameworks are of crucial interest in recent decades [1,2]. Such mentioned formal frameworks include, for instance, differential, difference and differential/difference hybrid equations, dynamic systems, control theory [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20], computation [7], and information theory [21][22][23][24][25][26][27][28] as well as combined mathematical analysis of epidemic spreading and control design tools [21,22,[27][28][29][30][31][32][33][34][35][36]. One of the objectives of such models is to investigate and predict the evolution of epidemic infectious diseases in humans, animals, or plants as well as to elucidate how the interventions, like quarantine actions or regular and impulsive vaccination and treatment controls, can avoid or mitigate their contagious propagation (See References [1,2,11,…”