ArticleNonlinear dynamics2020
Nonlinear model predictive control with logic constraints for COVID-19 management.
Article in Nonlinear dynamics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
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Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Data-driven strategies for model-informed decision-making during the COVID-19 pandemic: a systematic review.BMJ open · 2026Pooled it
- Optimizing infectious disease mitigation under dynamic conditions.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Smart epidemic control: A hybrid model blending ODEs and agent-based simulations for optimal, real-world intervention planning.PLoS computational biology · 2025Article
- Optimal control prevents itself from eradicating stochastic disease epidemics.PLoS computational biology · 2025Article
- Wastewater-based modeling, reconstruction, and prediction for COVID-19 outbreaks in Hungary caused by highly immune evasive variants.Water research · 2023Article
- Stochastic SIR model predicts the evolution of COVID-19 epidemics from public health and wastewater data in small and medium-sized municipalities: A one year study.Chaos, solitons, and fractals · 2022Article
- Recursive state and parameter estimation of COVID-19 circulating variants dynamics.Scientific reports · 2022Article
- State-controlled epidemic in a game against a novel pathogen.Scientific reports · 2022Article
- Controlling epidemic diseases based only on social distancing level: General case.ISA transactions · 2022Article
- Reconstructing social mixing patterns via weighted contact matrices from online and representative surveys.Scientific reports · 2022Article
- Microsimulation based quantitative analysis of COVID-19 management strategies.PLoS computational biology · 2022Article
- Feedback control of social distancing for COVID-19 via elementary formulae.IFAC-PapersOnLine · 2022Article
- Stochastic forecasting of COVID-19 daily new cases across countries with a novel hybrid time series model.Nonlinear dynamics · 2022Article
- Estimating the state of epidemics spreading with graph neural networks.Nonlinear dynamics · 2022Article
- Mathematical modeling and optimal control of the COVID-19 dynamics.Results in physics · 2021Article
- Prediction and Analysis of Tourist Management Strategy Based on the SEIR Model during the COVID-19 Period.International journal of environmental research and public health · 2021Article
- An algorithm for the robust estimation of the COVID-19 pandemic's population by considering undetected individuals.Applied mathematics and computation · 2021Article
- New strategy to control covid-19 pandemic using lead/lag compensator.Biomedical signal processing and control · 2021Article
- Nonlinear Dynamics of the Introduction of a New SARS-CoV-2 Variant with Different Infectiousness.Mathematics (Basel, Switzerland) · 2021Article
- Model predictive control for optimal social distancing in a type SIR-switched model.IFAC-PapersOnLine · 2021Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The management of COVID-19 appears to be a long-term challenge, even in countries that have managed to suppress the epidemic after their initial outbreak. In this paper, we propose a model predictive approach for the constrained control of a nonlinear compartmental model that captures the key dynamical properties of COVID-19. The control design uses the discrete-time version of the epidemic model, and it is able to handle complex, possibly time-dependent constraints, logical relations between model variables and multiple predefined discrete levels of interventions. A state observer is also constructed for the computation of non-measured variables from the number of hospitalized patients. Five control scenarios with different cost functions and constraints are studied through numerical simulations, including an output feedback configuration with uncertain parameters. It is visible from the results that, depending on the cost function associated with different policy aims, the obtained controls correspond to mitigation and suppression strategies, and the constructed control inputs are similar to real-life government responses. The results also clearly show the key importance of early intervention, the continuous tracking of the susceptible population and that of future work in determining the true costs of restrictive control measures and their quantitative effects.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.