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Parameter estimation of an hiv model with mutants using sporadically sampled data
- Authors
- Kim, S.-K.; Kim, J.S.; Yoon, T.-W.
- Issue Date
- 2011
- Keywords
- Genetic algorithm; HIV model; Mutant virus; Non-uniformly sampled output data; Parameter estimation
- Citation
- Journal of Institute of Control, Robotics and Systems, v.17, no.8, pp.753 - 759
- Indexed
- SCOPUS
KCI
- Volume
- 17
- Number
- 8
- Start Page
- 753
- End Page
- 759
- ISSN
- 1976-5622
- Abstract
- 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. © ICROS 2011.
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Related Researcher
- YOON, TAE WOONG
- College of Engineering (School of Electrical Engineering)