Modern mechatronic and cyber-physical systems are capable of autonomously adapting their behavior due to their inherent intelligence. Such systems are increasingly complex and therefore pose a great challenge to its development.
Thus, we design intelligent technical systems and optimize their dynamic system behavior. To this end, modeling methods are being developed to optimize complex multi-body models with flexible bodies regarding their oscillation behavior.
Furthermore, we research the dependability of such systems with the focus on aspects of reliability, safety and availability.
Through self-optimization, intelligent technical systems are capable of significantly increasing their dependability. In this context, it is necessary to investigate the failure behavior, in addition to the desired system behavior, and to appropriately incorporate it into the modeling of the entire system.
To incorporate dependability of these systems into the design phase, we develop integrated modeling tools for dependability and behavior. This allows us to identify strong interactions between the system's behavior and the degradation of individual components or the entire system at an early stage, and to identify critical components as well as system states.
With these modeling methods, we use multi-target optimization techniques not only to regulate the dependability of an intelligent system in operation based on its current state but also to provide an autonomous system response to future failures. We develop condition monitoring methods for detection of the current system state and for prediction of the time to failure.
With the active influence on the dependability of an intelligent technical system by means of a control system and the associated prognosis of the remaining useful life (RUL), new intelligent maintenance strategies are possible, which could lead to a significant increase in the availability of these Systems.