Nonlinear adaptive control of COVID-19 with media campaigns and treatment

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by the infection of severe acute respiratory syndrome coronavirus 2, which is spreading all over the world and causing huge human and economic losses. For these reasons, we study the adaptive control problem of COVID-19 in consideration of media campaigns and treatment in this paper. Firstly, a novel compartment model is constructed by analysing the spread mechanism of COVID-19 and a nonlinear adaptive control problem is established. Then, using the estimation of parameters updated by adaptive laws, the controllers are designed to achieve the control goals. Finally, numerical examples are presented to illustrate the control capability to the outbreak of COVID-19.

[1]  Weiping Li,et al.  Applied Nonlinear Control , 1991 .

[2]  Haifa Ben Fredj,et al.  Novel Corona virus disease infection in Tunisia: Mathematical model and the impact of the quarantine strategy , 2020, Chaos, Solitons & Fractals.

[3]  E. Labriji,et al.  Mathematical modeling of the spread of COVID-19 among different age groups in Morocco: Optimal control approach for intervention strategies , 2020, Chaos, Solitons & Fractals.

[4]  Mostafa Rachik,et al.  Optimal control approach of a mathematical modeling with multiple delays of the negative impact of delays in applying preventive precautions against the spread of the COVID-19 pandemic with a case study of Brazil and cost-effectiveness , 2020, Chaos, Solitons & Fractals.

[5]  S. Chariyalertsak,et al.  Application technology to fight the COVID-19 pandemic: Lessons learned in Thailand , 2020, Biochemical and Biophysical Research Communications.

[6]  Thomas E. Yankeelov,et al.  Simulating the spread of COVID-19 via a spatially-resolved susceptible–exposed–infected–recovered–deceased (SEIRD) model with heterogeneous diffusion , 2020, Applied Mathematics Letters.

[7]  P. Mallon,et al.  COVID19- clinical presentation and therapeutic considerations , 2020, Biochemical and Biophysical Research Communications.

[8]  Qimin Zhang,et al.  A delayed avian influenza model with avian slaughter: Stability analysis and optimal control , 2019, Physica A: Statistical Mechanics and its Applications.

[9]  Jianjun Jiao,et al.  Dynamics of an SEIR model with infectivity in incubation period and homestead-isolation on the susceptible☆ , 2020, Applied Mathematics Letters.

[10]  Áine Byrne,et al.  Piecewise-constant optimal control strategies for controlling the outbreak of COVID-19 in the Irish population , 2020, Mathematical Biosciences.

[11]  Hadi Jahanshahi,et al.  Optimal policies for control of the novel coronavirus disease (COVID-19) outbreak , 2020, Chaos, Solitons & Fractals.

[12]  Musadaq A. Hadi,et al.  Control of COVID-19 system using a novel nonlinear robust control algorithm , 2020, Biomedical Signal Processing and Control.

[13]  Jing Zhao,et al.  Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus–Infected Pneumonia , 2020, The New England journal of medicine.

[14]  Christopher A. Gilligan,et al.  A modelling framework to assess the likely effectiveness of facemasks in combination with ‘lock-down’ in managing the COVID-19 pandemic , 2020, Proceedings of the Royal Society A.

[15]  E. Carafoli,et al.  History of the COVID-19 pandemic: Origin, explosion, worldwide spreading , 2020, Biochemical and Biophysical Research Communications.

[16]  Tsuyoshi Murata,et al.  {m , 1934, ACML.