062a368457d731a8ee4afb310620ddaf App_a2020v10n20p7183.pdf 10c9a8f0ccccdf6cf8de5b7d4cdcbde21417ec51 App_a2020v10n20p7183.pdf f5a4ffd545614bb86fbb230a47cf8a23db21532cae1526d5d4905ce15f5f98ce App_a2020v10n20p7183.pdf Title: Supervision of the Infection in an SI (SI-RC) Epidemic Model by Using a Test Loss Function to Update the Vaccination and Treatment Controls Subject: This paper studies and proposes some supervisory techniques to update the vaccination and control gains through time in a modified SI (susceptible-infectious) epidemic model involving the susceptible and subpopulations. Since the presence of linear feedback controls are admitted, a compensatory recovered (or immune) extra subpopulation is added to the model under zero initial conditions to deal with the recovered subpopulations transferred from the vaccination and antiviral/antibiotic treatment on the susceptible and the infectious, respectively. Therefore, the modified model is referred to as an SI(RC) epidemic model since it integrates the susceptible, infectious and compensatory recovered subpopulations. The defined time-integral supervisory loss function can evaluate weighted losses involving, in general, both the susceptible and the infectious subpopulations. It is admitted, as a valid supervisory loss function, that which involves only either the infectious or the susceptible subpopulations. Its concrete definition involving only the infectious is related to the Shannon information entropy. The supervision problem is basically based on the implementation of a parallel control structure with different potential control gains to be judiciously selected and updated through time. A higher decision level structure of the supervisory scheme updates the appropriate active controller (i.e., that with the control gain values to be used along the next time window), as well as the switching time instants. In this way, the active controller is that which provides the best associated supervisory loss function along the next inter-switching time interval. Basically, a switching action from one active controller to another one is decided as a better value of the supervisory loss function is detected for distinct controller gain values to the current ones. Keywords: epidemic model; transient behavior; control gains: feedback; supervised control design; vaccination and treatment controls Author: Manuel De la Sen, Asier Ibeas, Raul Nistal, Santiago Alonso-Quesada and Aitor Garrido Creator: LaTeX with hyperref package Producer: pdfTeX-1.40.18 CreationDate: Thu Oct 22 13:29:13 2020 CEST ModDate: Thu Oct 22 13:32:56 2020 CEST Tagged: no UserProperties: no Suspects: no Form: none JavaScript: no Pages: 22 Encrypted: no Page size: 595.276 x 841.89 pts (A4) Page rot: 0 File size: 2681057 bytes Optimized: no PDF version: 1.7 name type encoding emb sub uni object ID ------------------------------------ ----------------- ---------------- --- --- --- --------- YXNNUJ+URWPalladioL-Ital Type 1 Custom yes yes no 10 0 ZMXAIR+URWPalladioL-Bold Type 1 Custom yes yes no 15 0 MDIROB+URWPalladioL-Roma Type 1 Custom yes yes no 19 0 YIJSCU+Rpxr Type 1 Builtin yes yes no 23 0 CRVMKC+TimesNewRomanPS-BoldItalicMT Type 1C WinAnsi yes yes no 31 0 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Title: About the Positivity and Equilibrium Points Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@46daef40 Item: Title: Supervised Selection of the Control Gains Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@12f41634 Children: Item: Title: Supervisory Objective to Update the Control Gains Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@13c27452 Item: Title: Updating Algorithms Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@262b2c86 Item: Title: Simulation Results Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@371a67ec Item: Title: References Destination: edu.harvard.hul.ois.jhove.module.pdf.PdfSimpleObject@5ed828d Info: Title: Supervision of the Infection in an SI (SI-RC) Epidemic Model by Using a Test Loss Function to Update the Vaccination and Treatment Controls Author: Manuel De la Sen, Asier Ibeas, Raul Nistal, Santiago Alonso-Quesada and Aitor Garrido Subject: This paper studies and proposes some supervisory techniques to update the vaccination and control gains through time in a modified SI (susceptible-infectious) epidemic model involving the susceptible and subpopulations. Since the presence of linear feedback controls are admitted, a compensatory recovered (or immune) extra subpopulation is added to the model under zero initial conditions to deal with the recovered subpopulations transferred from the vaccination and antiviral/antibiotic treatment on the susceptible and the infectious, respectively. Therefore, the modified model is referred to as an SI(RC) epidemic model since it integrates the susceptible, infectious and compensatory recovered subpopulations. The defined time-integral supervisory loss function can evaluate weighted losses involving, in general, both the susceptible and the infectious subpopulations. It is admitted, as a valid supervisory loss function, that which involves only either the infectious or the susceptible subpopulations. Its concrete definition involving only the infectious is related to the Shannon information entropy. The supervision problem is basically based on the implementation of a parallel control structure with different potential control gains to be judiciously selected and updated through time. A higher decision level structure of the supervisory scheme updates the appropriate active controller (i.e., that with the control gain values to be used along the next time window), as well as the switching time instants. In this way, the active controller is that which provides the best associated supervisory loss function along the next inter-switching time interval. Basically, a switching action from one active controller to another one is decided as a better value of the supervisory loss function is detected for distinct controller gain values to the current ones. 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