The paper addresses a flatness-based controller design for hyperbolic multiple-input systems based on the hyperbolic controller form (HCF). The state representation consists of homogeneous, boundary-coupled transport equations, which enables a straightforward design of stabilizing tracking controllers. The concept is discussed for the classical Timoshenko beam, where the HCF results as a generalized state representation. As this renders purely static state feedback insufficient for designing tracking controllers, two alternative approaches based on dynamic and quasi-static feedback are presented. The results are validated and illustrated by means of simulations.
Zusammenfassung Globale, lean-optimierte Lieferketten sind gegenüber Störungen wie Cyberangriffen oder Lieferengpässen hochgradig anfällig. Die vorliegende Arbeit entwickelt eine AAS-basierte Modellierung resilienzrelevanter Informationen für ein systemdynamisches Simulations- und Optimierungsframework. Erforderliche Eingabedaten umfassen Produktstrukturen, Bedarfe/Warenausgänge, Lieferantenparameter (Verzögerungszeiten, Kapazitätsgrenzen, Sicherheitsbestände) sowie die zu simulierenden Resilienzszenarien. Bestehende IDTA-Teilmodelle (Hierarchical Structures, CompanyData, PurchaseOrder) werden durch ResilienceData und ResilienceScenarios erweitert. Die AAS dient als abstrakte Schnittstelle, die heterogene Enterprise-Systeme standardisiert und on-demand der Simulation zugänglich macht.
Abstract Extracorporeal membrane oxygenation (ECMO) provides temporary cardiopulmonary support via an oxygenator. However, reliable oxygenator monitoring remains limited. This study examined whether multimodal condition parameters can be combined into an exploratory strategy for assessing oxygenator degradation. In vitro degradation was analyzed using blood flow- and gas exchange-related parameters. Temporal trends were evaluated with linear mixed-effects models, and principal component analysis with change-point analysis of the first principal component (PC1) was used to identify common patterns and structural transitions. All parameters showed significant temporal trends. PC1 explained 68.52 %–83.67 % of the total variance, with structural transitions detected between 186 and 253 min. The proposed approach may support exploratory, data-driven assessment of oxygenator degradation during ECMO.
Abstract The collaboration between biomedical technology and medicine has transformed modern healthcare, particularly in the field of reconstructive medicine and surgery. Innovations such as minimally invasive techniques including robotic-assisted systems, medical imaging, artificial intelligence, and many others have markedly improved diagnostic accuracy, therapeutic planning, treatment precision, disease outcomes, patient safety, and posttreatment recovery. These advancements have paved the way for more effective surgical procedures than ever before. This paper examines the relationship between technological development and reconstructive techniques, highlighting the benefits, challenges, and future implications of integrating advanced technologies into medicine.
