SIIR流行病模型中的MPC控制器

IF 1.9 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Computation Pub Date : 2023-09-04 DOI:10.3390/computation11090173
Nikita Kosyanov, E. Gubar, Vladislav Taynitskiy
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引用次数: 0

摘要

传染病是现代世界最重要的问题之一,例如,由COVID-19、流感和许多其他呼吸道疾病引起的冠状病毒感染的周期性爆发严重影响了许多国家的经济。因此,必须尽量减少经济损失,其中包括工作损失和治疗费用、隔离费用等。最近的研究提出了许多描述病毒传播动力学的不同模型,这些模型有助于分析流行病的爆发。在目前的工作中,我们专注于寻找对噪声具有鲁棒性的解决方案,并考虑到过程中未来变化的动态。我们通过使用非线性模型预测控制(MPC)控制器来扩展先前的结果,以找到有效的控制。MPC是一种用于具有观测值的动态控制系统的计算数学方法,用于寻找有效的控制。
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MPC Controllers in SIIR Epidemic Models
Infectious diseases are one of the most important problems of the modern world, for example, the periodic outbreaks of coronavirus infections caused by COVID-19, influenza, and many other respiratory diseases have significantly affected the economics of many countries. Hence, it is therefore important to minimize the economic damage, which includes both loss of work and treatment costs, quarantine costs, etc. Recent studies have presented many different models describing the dynamics of virus spread, which help to analyze the epidemic outbreaks. In the current work we focus on finding solutions that are robust to noise and take into account the dynamics of future changes in the process. We extend previous results by using a nonlinear model-predictive-control (MPC) controller to find effective controls. MPC is a computational mathematical method used in dynamically controlled systems with observations to find effective controls.
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来源期刊
Computation
Computation Mathematics-Applied Mathematics
CiteScore
3.50
自引率
4.50%
发文量
201
审稿时长
8 weeks
期刊介绍: Computation a journal of computational science and engineering. Topics: computational biology, including, but not limited to: bioinformatics mathematical modeling, simulation and prediction of nucleic acid (DNA/RNA) and protein sequences, structure and functions mathematical modeling of pathways and genetic interactions neuroscience computation including neural modeling, brain theory and neural networks computational chemistry, including, but not limited to: new theories and methodology including their applications in molecular dynamics computation of electronic structure density functional theory designing and characterization of materials with computation method computation in engineering, including, but not limited to: new theories, methodology and the application of computational fluid dynamics (CFD) optimisation techniques and/or application of optimisation to multidisciplinary systems system identification and reduced order modelling of engineering systems parallel algorithms and high performance computing in engineering.
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