Skip to Main Content Discrete LPV Modeling of Diabetes Mellitus for Control Purposes Abstract: The utilization of modern and advanced control engineering related methods for the control, estimation and assessment of physiological applications is widespread.
It is also well-known that this engineering apparatus is executed on digital computers. The current insufficiency of available and accurate discretized models, especially in case of Diabetes Mellitus DMprovides incentive for this research.
The researchers typically approximate the continuous solutions which may not be the best alternative in many cases, in particular considering numerical stability and cost-effectiveness. In this paper we performed an analysis of the available discretization options in order to develop discrete models with a special focus on diabetes analysis Linear Parameter Varying LPV systems.
It found that type 2 diabetes is associated with a higher risk of mortality in hospitalised COVID patients than type 1 diabetes. The combination of an older age and high C-reactive protein CRP was also linked to a higher risk of death. Younger people under 70 years old with chronic kidney disease, a common long-term complication of diabetes, also had a higher likelihood of dying.
LPV techniques are very useful frameworks which allow the application of linear controller, observer and estimator design. In this study, three LPV discretization and two Jacobian based discretization methods are introduced and analyzed to provide a basis for our further investigations in the topic.