Research Focus Control and Process Automation
Our Research Unit specialises in model-based control and optimisation of complex industrial systems. They offer unique expertise in the following Research Units.
Our Research Focus
Complex Systems under Control
We want cars to run smoothly and safely, we want buildings to maintain a comfortable living atmosphere, and we want to understand and optimise the flow of urban traffic. At first glance, these topics have nothing in common – but they are all about complex interconnected systems, which have to be controlled and optimised using advanced mathematical methods in order to make them behave the way we want. The availability of powerful computers enables the realisation of sophisticated model-based control concepts in many different application areas. This trend has evoked a continuous demand for new and effective methodologies in model design and process optimisation.
Many mechanical systems, such as a planet orbiting the sun, can be fully analysed from first principles of physics. But most complex real-world-systems have to be characterised by carefully studying the intricate connections between input parameters and system behaviour, casting them into mathematical equations.
The behaviour of many complex systems is usually described by a set of differential equations, most often nonlinear in their nature. Once the necessary parameters are available, such a description becomes a mathematical model, which can be used for the optimal operation of the system as well as for forecasting and diagnosis.
The list of possible application areas is endless – it ranges from controlling industrial machines in order to minimise vibrations over acoustic optimisation of loudspeakers to regulating eco-friendly combustion processes in chemical engineering. Sometimes it is not even enough to have a precise mathematical description of a system available. The model also has to be sufficiently simple – especially if it is supposed to be used for real-time process control. This gives rise to the discipline of model reduction.