Prof. Dr. Radu Grosu - Smart Attributes for CPPS
Production systems are extensively equipped with sensors, actuators and controllers, and the automation pyramid is linked through a communication network into an either strictly centralized or to a strictly decentralized IT structure. A fixed set of products and services is typically offered, and their realization is carefully planned in advance: Unfortunately, too sequential, too comprehensive, and hardware/product specific.
The technological advancements of the past decade nurtures the emergence of a new and fascinating cyber‐physical (CP) society, in which the physical, continuous world of things is getting merged with the virtual, discrete world of knowledge. Akin to a biological system, a CPPS will adapt itself in real time to its environment, reshape on the fly its products and production lines, and lower its costs and pollution footprint. While many advances are already under way, there are still many research and technological challenges that have to be mastered. One of the greatest challenges is to efficiently predict the emergent behaviors of these systems. However, the complexity of their models often hinders any attempt to exhaustively verify their safe behavior.
An alternative method is to equip them with monitors and to predict emergent behaviors at runtime. This approach makes Cyber-Physical Systems self‐aware opening up new perspectives to design smart systems able to dynamically self‐organize or reconfigure themselves in order to adapt to the different circumstances. For example, in the automotive scenario, the increasing failure rates of microchips, due to continuously shrinking of devices, and the usage of unreliable sources of information (e.g., information sent by other vehicles) require fast error detection, fault tolerant system designs and new planning strategies. Some of these problems can be solved by knowledge-based techniques like autonomous reconfiguration and substitution of faulty.
Monitoring introduces a runtime overhead that may alter the timing‐related behavior of the system under scrutiny. In applications with real‐time constraints, overhead control strategies may be necessary to reduce the overhead to acceptable levels by, for example, turning on and off the monitoring. Gaps in monitoring, however, introduce uncertainty in the monitoring results. Hence, another research direction will also focus on efficient techniques to quantify this uncertainty and computing an estimate of the current state of the system.
Hence, PhD research within the topic "Smart Attributes for CPPS" focusses on:
- Ontologies (OG): Develop standardized ontologies, comprising structural and behavioral models (services), and proper communication models, such that OG can be discovered, accessed and executed in real‐time.
- Beyond execution (BE): Develop multi‐scale, spatial‐temporal, specification languages, ontologies and abstractions, which facilitate offline (detection) and online (control) of emergent, undesired OG‐behavior.
- Adaptability (AD): Develop ontologies (possibly for a set of devices) which facilitate a proper reaction (e.g., a new execution strategy, on a possibly new configuration) to uncertain and unforeseen situations.
The position will be located at the Cyber Physical System Group at TU Wien under the supervision of Prof. Radu Grosu and Dr. Ezio Bartocci. The position is well suited for applicants with a background in computer science, informatics and electrical engineering. Experience in embedded systems and signal processing is required, knowledge in Internet of Things technologies, ontologies, runtime verification and control theory is considered a plus.