Abstract
The evolution of antibiotic resistance in bacteria is a significant public health risk influenced by several factors. Switched systems can abstract the evolutionary aspects driven by antibiotic use in a given population. However, mathematical models are not perfect, and uncertain dynamics remain. Based on a set theory approach, our main result is the development of an algorithm to demonstrate the stabilizability of a robust invariant set for the uncertain switched system. The algorithm also provides a characterization of invariant regions for switched systems under perturbations. Our findings provide insights into how to incorporate uncertainties in switched systems. This paves the way for selecting antibiotics to tackle drug-resistant infections.