Parameter estimation of an hiv model with mutants using sporadically sampled data

Seok Kyoon Kim, Jung Su Kim, Tae Woong Yoon

Research output: Contribution to journalArticlepeer-review


The HIV (Human Immunodeficiency Virus) causes AIDS (Acquired Immune Deficiency Syndrome). The process of infection and mutation by HIV can be described by a 3rd order state equation. For this HIV model that includes the dynamics of the mutant virus, we present a parameter estimation scheme using two state variables sporadically measured, out of the three, by employing a genetic algorithm. It is assumed that these non-uniformly sampled measurements are subject to random noises. The effectiveness of the proposed parameter estimation is demonstrated by simulations. In addition, the estimated parameters are used to analyze the equilibrium points of the HIV model, and the results are shown to be consistent with those previously obtained.

Original languageEnglish
Pages (from-to)753-759
Number of pages7
JournalJournal of Institute of Control, Robotics and Systems
Issue number8
Publication statusPublished - 2011 Aug


  • Genetic algorithm
  • HIV model
  • Mutant virus
  • Non-uniformly sampled output data
  • Parameter estimation

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Applied Mathematics


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