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10.1016/j.chaos.2021.111051 http://scihub22266oqcxt.onion/10.1016/j.chaos.2021.111051 34108820!8179022!34108820     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Chaos+Solitons+Fractals 2021 ; 149 (ä): 111051 Nephropedia Template TP {{tp|p=34108820|t=2021. Nonlinear control of infection spread based on a deterministic SEIR model |pdf=|usr=}}{{34108820}} gab.com Text Nonlinear control of infection spread based on a deterministic SEIR model JO: Chaos Solitons Fractals http://www.kidney.de/pget.php?&tw=1&pmid=34108820 #FOAvip In this study, a mathematical model (SEIR model) with a restriction parameter is used to explore the dynamic of the COVID-19 pandemic. This work presents a nonlinear and robust control algorithm based on variable structure control (VSC) to control the transmission of coronavirus disease (COVID-19). The VSC algorithm is a control gain switching technique in which is necessary to define a switching surface. Three switching surfaces are proposed based on rules that depend on: (i) exposed and infected population, (ii) susceptible and infected population, and (iii) susceptible and total population. In case (iii) a model-based state estimator is presented based on the extended Kalman filter (EKF) and the estimator is used in combination with the VSC. Numerical results demonstrate that the proposed control strategies have the ability to flatten the infection curve. In addition, the simulations show that the success of lowering and flattening the epidemic peak is strongly dependent on the chosen switching surfaces. A comparison between the VSC and sliding mode control (SMC) is presented showing that the VSC control can provide better performance taking into account two aspects: time duration of pandemic and the flattened curve peak with respect to SMC. Twit Text FOAVip Nonlinear control of infection spread based on a deterministic SEIR model ????Chaos Solitons Fractals http://www.kidney.de/pget.php?&tw=1&pmid=34108820 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34108820 #FOAvip English Wikipedia <ref>{{Cite pmid|34108820}}</ref> Nonlinear control of infection spread based on a deterministic SEIR model #MMPMID34108820 Piccirillo V Chaos Solitons Fractals 2021[Aug]; 149 (ä): 111051 PMID34108820show ga In this study, a mathematical model (SEIR model) with a restriction parameter is used to explore the dynamic of the COVID-19 pandemic. This work presents a nonlinear and robust control algorithm based on variable structure control (VSC) to control the transmission of coronavirus disease (COVID-19). The VSC algorithm is a control gain switching technique in which is necessary to define a switching surface. Three switching surfaces are proposed based on rules that depend on: (i) exposed and infected population, (ii) susceptible and infected population, and (iii) susceptible and total population. In case (iii) a model-based state estimator is presented based on the extended Kalman filter (EKF) and the estimator is used in combination with the VSC. Numerical results demonstrate that the proposed control strategies have the ability to flatten the infection curve. In addition, the simulations show that the success of lowering and flattening the epidemic peak is strongly dependent on the chosen switching surfaces. A comparison between the VSC and sliding mode control (SMC) is presented showing that the VSC control can provide better performance taking into account two aspects: time duration of pandemic and the flattened curve peak with respect to SMC. äNonlinear control of infection spread based on a deterministic SEIR mo(epmc).pdf DeepDyve Pubget Overpricing