Related papers: Meta model application for consistency management …
Robust control design is mainly devoted to guarantee closed-loop stability of a model-based control law in presence of parametric and structural uncertainties. The control law is usually a complex feedback law which is derived from a…
Evaluating the security of cyber-physical systems throughout their life cycle is necessary to assure that they can be deployed and operated in safety-critical applications, such as infrastructure, military, and transportation. Most safety…
The machine learning lifecycle extends beyond the deployment stage. Monitoring deployed models is crucial for continued provision of high quality machine learning enabled services. Key areas include model performance and data monitoring,…
Scalability of the control plane in a software-defined network (SDN) is enabled by means of decentralization of the decision-making logic, i.e., by replication of controller functions to physically or virtually dislocated controller…
Ensuring the trustworthiness and long-term verifiability of scientific data is a foundational challenge in the era of data-intensive, collaborative research. Provenance metadata plays a key role in this context, capturing the origin,…
Complex engineering problems can be modelled as optimisation problems. For instance, optimising engines, materials, components, structure, aerodynamics, navigation, control, logistics, and planning is essential in aerospace. Metaheuristics…
Safety-critical system's failure or malfunction can cause loss of human lives or damage to the physical environment; therefore, continuous safety assessment is crucial for such systems. In many domains this includes the use of Safety…
[Context & Motivation] Adaptive systems are an important research area. The dominant reason for adaptivity in systems are changes in the environment. Thus, it is an important question how to model the environment and how to determine the…
Reference models in form of best practices are an essential element to ensured knowledge as design for reuse. Popular modeling approaches do not offer mechanisms to embed reference models in a supporting way, let alone a repository of it.…
Due to changes in model dynamics or unexpected disturbances, an autonomous robotic system may experience unforeseen challenges during real-world operations which may affect its safety and intended behavior: in particular actuator and system…
This study presents a synchronisation-oriented perspective towards adaptive control which views model-referenced adaptation as synchronisation between actual and virtual dynamic systems. In the context of adaptation, model reference…
To cope with the increasing complexity of developing and maintaining modern (software) systems, multiple abstractions (models) of the same system can be established and used to allow different domain experts to collaborate and contribute…
Using models for requirements engineering (RE) is uncommon in systems engineering, despite the widespread use of model-based engineering in general. One reason for this lack of use is that formal models do not match well the trend to move…
Systems engineering approaches use high-level models to capture the architecture and behavior of the system. However, when safety engineers conduct safety and reliability analysis, they have to create formal models, such as fault-trees,…
Nowadays, there are several complex systems in different sectors such as aviation, air traffic control ...etc. These systems do not have a precise perimeter, they are open and made of various specific components built with different…
We present a bottleneck analysis tool for designing compute systems for autonomous Unmanned Aerial Vehicles (UAV). The tool provides insights by exploiting the fundamental relationships between various components in the autonomous UAV such…
This White Paper sets out to explain the value that metamodelling can bring to air traffic management (ATM) research. It will define metamodelling and explore what it can, and cannot, do. The reader is assumed to have basic knowledge of…
Background: Distributed data-intensive systems are increasingly designed to be only eventually consistent. Persistent data is no longer processed with serialized and transactional access, exposing applications to a range of potential…
The zeitgeist of the digital era has been dominated by an expanding integration of Artificial Intelligence~(AI) in a plethora of applications across various domains. With this expansion, however, questions of the safety and reliability of…
Ensuring constraint satisfaction is a key requirement for safety-critical systems, which include most robotic platforms. For example, constraints can be used for modeling joint position/velocity/torque limits and collision avoidance.…