World Health Organization (WHO) has declared COVID-19 a pandemic on March 11, 2020. As of May 23, 2020, according to WHO, there are 213 countries, areas or territories with COVID-19 positive cases. To effectively address this situation, it is imperative to have a clear understanding of the COVID-19 transmission dynamics and to concoct efficient control measures to mitigate/contain the spread. In this work, the COVID-19 dynamics is modelled using susceptible–exposed–infectious–removed model with a nonlinear incidence rate. In order to control the transmission, the coefficient of nonlinear incidence function is adopted as the Governmental control input. To adequately understand the COVID-19 dynamics, bifurcation analysis is performed and the effect of varying reproduction number on the COVID-19 transmission is studied. The inadequacy of an open-loop approach in controlling the disease spread is validated via numerical simulations and a robust closed-loop control methodology using sliding mode control is also presented. The proposed SMC strategy could bring the basic reproduction number closer to 1 from an initial value of 2.5, thus limiting the exposed and infected individuals to a controllable threshold value. The model and the proposed control strategy are then compared with real-time data in order to verify its efficacy.

世界卫生组织 (WHO) 已于 2020 年 3 月 11 日宣布 COVID-19 为大流行病。据世界卫生组织称，截至 2020 年 5 月 23 日，有 213 个国家、地区或领地出现 COVID-19 阳性病例。为了有效解决这种情况，必须清楚地了解 COVID-19 的传播动态，并制定有效的控制措施来减轻/遏制传播。在这项工作中，使用具有非线性发病率的易感-暴露-感染-去除模型对 COVID-19 动力学进行建模。为了控制传输，采用非线性入射函数的系数作为政府控制输入。为了充分了解 COVID-19 的动态，进行了分岔分析，并研究了不同的再生数对 COVID-19 传输的影响。通过数值模拟验证了开环方法在控制疾病传播方面的不足之处，并提出了一种使用滑模控制的稳健闭环控制方法。提出的 SMC 策略可以使基本再生数从初始值 2.5 接近 1，从而将暴露和感染个体限制在可控阈值。然后将模型和建议的控制策略与实时数据进行比较，以验证其有效性。从而将暴露和感染的个体限制在一个可控的阈值内。然后将模型和建议的控制策略与实时数据进行比较，以验证其有效性。从而将暴露和感染的个体限制在一个可控的阈值内。然后将模型和建议的控制策略与实时数据进行比较，以验证其有效性。