Nonlinear control of Covid-19 pandemic based on the SIRD model

In the last month of 2019, a new version of Corona disease was observed in Wuhan (China) which is known as Covid-19. Several models have been proposed to predict disease treatment. The SIR model is considered one of the simplest models for the prediction of pandemic disease. This means susceptible (S), infected (I), and recovered (R) populations. The SIRD model is yet another method that includes one more equation, i.e., the number of deaths (D). This paper proposed a control law for the first time to prevent the progression of the disease. The proposed control law is based on the SIRD model and uses the feedback linearization method for the Covid-19 nonlinear model. The goal of control in this model is to reduce the number of people infected with the Covid-19 and the number of deaths due to the disease. Delay in treatment of infected people and percentage of people who should be treated are investigated as two important parameters. The results show that with the treatment of infected people in the first weeks, the number of people infected decreases by 96.3% and the number of deaths by 93.6%