School of Computer and Information Engineering, Beijing Technology and Business University, Beijing, 100048, China; School of Automation, Beijing University of Posts and Telecommunications, Beijing, 100876, China.
School of Computer and Information Engineering, Beijing Technology and Business University, Beijing, 100048, China.
ISA Trans. 2022 May;124:115-123. doi: 10.1016/j.isatra.2021.02.039. Epub 2021 Feb 25.
The coronavirus disease 2019 (COVID-19) is a new, rapidly spreading and evolving pandemic around the world. The COVID-19 has seriously affected people's health or even threaten people's life. In order to contain the spread of the pandemic and minimize its impact on economy, the tried-and-true control theory is utilized. Firstly, the control problem is clarified. Then, by combining advantages of the U-model control and the extended state observer (ESO), an extended state observer-based U-model control (ESOUC) is proposed to generate a population restriction policy. Closed-loop stability of the regulation system is also proved Two examples are considered, and numerical simulation results show that the ESOUC can suppress the COVID-19 faster than the linear active disturbance rejection control, which benefits controlling the infectious disease and the economic recovery. The ESOUC may provide a feasible non-pharmaceutical intervention in the control of the COVID-19.
新型冠状病毒肺炎(COVID-19)是一种在全球迅速传播和演变的新的大流行疾病。COVID-19 严重影响了人们的健康,甚至威胁到人们的生命。为了控制大流行的传播并将其对经济的影响降到最低,利用了经过验证的控制理论。首先,阐明了控制问题。然后,通过结合 U 型控制和扩张状态观测器(ESO)的优点,提出了一种基于扩张状态观测器的 U 型控制(ESOUC)来制定人口限制政策。还证明了调节系统的闭环稳定性。考虑了两个示例,数值模拟结果表明,ESOUC 可以比线性主动干扰抑制控制更快地抑制 COVID-19,这有利于控制传染病和经济复苏。ESOUC 可能为 COVID-19 的控制提供一种可行的非药物干预措施。