Abstract
This paper presents applications of control system theory in biomedical engineering. These methodologies are used in engineering sciences to obtain a mathematical model of systems, but system identification as scientific methodology is rarely used in biomedical engineering. The paper presents exemplarily control theory and system identification as methods for obtaining a mathematical model of the spread SARS-CoV-2 virus. The models obtained in the course of this are data-driven and strongly data-dependent. The available dataset allowed us to consider a model of a pandemic spread in the context of both the number of tested individuals and the number of infected individuals and with a resultant model that is nonlinear. We also considered a mathematical model for the dependence between the number of confirmed infected individuals and the number of deaths caused by the disease. The resulting model is linear given with the transfer function corresponding to the second-order differential equation. The mathematical models developed were additionally analyzed in accordance with controllability and observability.
| Original language | English |
|---|---|
| Pages (from-to) | 19-24 |
| Number of pages | 6 |
| Journal | IFAC-PapersOnLine |
| Volume | 55 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - 20 Jul 2022 |
Keywords
- biomedical engineering
- system identification
- mathematical model
- control theory
- covid-19
ASJC Scopus subject areas
- Control and Systems Engineering
Fields of Expertise
- Human- & Biotechnology