Publications

Pipelined image-based control uses parallel instances of its image-processing algorithm in a pipelined fashion to improve the quality of control. A performance-oriented control design improves the controller settling time with each additional processing resource, which creates a resources-performance trade-off.

We provide a model-based testing approach for systems comprising both state-transition based control flow, and data elements such as variables and data-dependent transitions. We propose test generation and execution, based on model-coverage: we generate test cases that aim to reach all transitions of the model.

Design decisions are made in an early-design phase of system development. These decisions have a big impact on the resulting system design and realization. Making design decisions in this stage is a complex and risky task, because there are a lot of uncertainties regarding their impact on the system qualities.

Image Processing (IP) applications have become popular with the advent of efficient algorithms and low-cost CMOS cameras with high resolution. However, IP applications are compute-intensive, consume a lot of energy and have long processing times. Image approximation has been proposed by recent works for an energy-efficient design of these applications.

In mixed-criticality systems, tasks of different criticality share system resources, mainly to reduce cost. Cost is further reduced by using adaptive mode-based scheduling arrangements, such as Vestal's model, to improve resource efficiency, while guaranteeing schedulability of critical functionality.

We consider supervisor synthesis of Extended Finite Automata that are represented using Binary Decision Diagrams (BDDs). Peak used BDD nodes and BDD operation count are introduced as platform independent and deterministic metrics that quantitatively indicate the computational effort needed to synthesize a supervisor.

At the pre-concept stage, an architect explores the problem space together with various stakeholders, including engineers, marketing, and future users of the system. This requires competencies and tactics to communicate efficiently while maintaining a system-level scope. We present a practical Structured Problem Exploration approach to assist architects in exploring the problem space.

Cyber physical systems of systems operate on and with machine-generated data that form the foundation of many of their information-centric functions and processes. Especially within infrastructure systems of systems and the applications of the internet of things, data became an asset for additional tasks regarding their efficient and effective operations, e.

To architect and design a system, the stakeholder needs have to be satisfied by technical solutions, for which decisions on trade-offs have to be made. A trend is that the number of functions, components, and interfaces in systems increase, often by an order of magnitude or more, such that reasoning about the impact of a decision becomes increasingly hard and tracing its impact throughout the system is crucial.

Predictive maintenance strategies which estimate remaining useful life of system components ensure reliable availability of assets and low total costs of ownership by preventing breakdowns and down-times with timely and well-scheduled maintenance. The focus on the components’ life times falls short, however, to infer the system-level capability to achieve upcoming tasks, especially if these tasks vary either in the strain they cause for the system or in the environmental conditions in which the system needs to perform.