An extended state observer based U-model control of the COVID-19

Area of Science:

• Control Theory
• Epidemiology
• Public Health Interventions

Background:

• The COVID-19 pandemic poses significant global health and economic challenges.
• Effective control strategies are crucial to mitigate the pandemic's impact.

Purpose of the Study:

• To develop and evaluate a novel control strategy for managing COVID-19 transmission.
• To propose a non-pharmaceutical intervention for pandemic control.

Main Methods:

• The study utilizes control theory, combining U-model control and extended state observer (ESO).
• An extended state observer-based U-model control (ESOUC) was developed to generate population restriction policies.
• Closed-loop stability of the regulation system was mathematically proven.

Main Results:

• Numerical simulations demonstrated that ESOUC suppresses COVID-19 faster than linear active disturbance rejection control.
• The proposed ESOUC strategy shows promise in controlling infectious disease spread.
• The method supports economic recovery by enabling faster pandemic containment.

Conclusions:

• ESOUC offers a feasible non-pharmaceutical intervention for COVID-19 control.
• The control strategy contributes to managing infectious diseases and facilitating economic recovery.
• This approach provides a valuable tool for pandemic management.