Feedback control of an HBV model based on ensemble kalman filter and differential evolution

Junyoung Jang, Kihoon Jang, Hee Dae Kwon, Jeehyun Lee

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

In this paper, we derive efficient drug treatment strategies for hepatitis B virus (HBV) infection by formulating a feedback control problem. We introduce and analyze a dynamic mathematical model that describes the HBV infection during antiviral therapy. We determine the reproduction number and then conduct a qualitative analysis of the model using the number. A control problem is considered to minimize the viral load with consideration for the treatment costs. In order to reflect the status of patients at both the initial time and the follow-up visits, we consider the feedback control problem based on the ensemble Kalman filter (EnKF) and differential evolution (DE). EnKF is employed to estimate full information of the state from incomplete observation data. We derive a piecewise constant drug schedule by applying DE algorithm. Numerical simulations are performed using various weights in the objective functional to suggest optimal treatment strategies in different situations.

Original languageEnglish
Pages (from-to)667-691
Number of pages25
JournalMathematical Biosciences and Engineering
Volume15
Issue number3
DOIs
Publication statusPublished - 2018 Jun

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Agricultural and Biological Sciences(all)
  • Computational Mathematics
  • Applied Mathematics

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