A Novel Approach to Nonlinear Control in Tuberculosis Transmission Dynamics

Tuberculosis (TB) remains a pressing global health concern, as it poses a significant threat to societies worldwide. Researchers have developed various mathematical models to better comprehend TB transmission dynamics, with the susceptible, exposed, infected, recovered, and resistant (SEIRs) model being widely employed. This paper proposes various nonlinear controllers, including sliding mode control (SMC), integral sliding mode control (ISMC), and supertwisting sliding mode control (STSMC), to reduce the number of infected individuals through effective treatment strategies while preventing susceptible and exposed individuals from contracting the disease via vaccination. The gains of the proposed controller have been optimized using improved grey wolf optimization with integral time absolute error as an objective function. The Lyapunov stability criteria has been used in mathematical analysis to demonstrate the asymptotic stability of proposed controllers. MATLAB/Simulink is used for all simulations to compare the performance of proposed controllers. For a real-time scenario, hardware validation is performed using a hardware-in-loop experimental setup with the C2000 Delfino and the MCU F28379D Launchpad.