Projective Synchronization and H∞ Control of a T-S Fuzzy-Based COVID-19 SEIR Model
Abstract
This paper addresses the projective synchronization and H ∞ control of the Susceptible-Exposed-Infectious-Recovered (SEIR) COVID-19 model using Takagi-Sugeno (T-S) fuzzy control techniques. A fuzzy controller design is proposed to synchronize the SEIR nonlinear model by using the Linear Matrix Inequality (LMI) technique and the Lyapunov function. Based on the LMI technique, Lyapunov function, and H ∞ control theory, the system's stability and H ∞ performance is ensured by a set of necessary criteria. The advantage of this research lies in its ability to enhance system stability, defined via Lyapunov-based LMI conditions, and robustness, measured through the H ∞ disturbance attenuation level, both of which are crucial for effective pandemic management. This paper presents simulations and numerical data to highlight the benefits of the proposed method, demonstrating its effectiveness in mitigating the negative consequences of the COVID-19 pandemic by comparing controlled and uncontrolled scenarios.
Fields of Study & Subjects
Neural Networks Stability and Synchronization
Mathematical and Theoretical Epidemiology and Ecology Models
Stability and Control of Uncertain Systems
Publication details
- Journal / source
- Journal of Intelligent & Fuzzy Systems
- Volume
- 50
- Issue
- 7
- Pages
- 2277–2305
- Publication date
- 7 January 2026
- Language
- EN