Measurement of process variables relevant for control purposes and implementation of model-based control algorithms in basic automation systems
Testing and test bench automation for targeted test runs
Modelling of dynamic characteristics
Development and parametrization of mathematical models describing dynamic characteristics as a basis for model-based control strategies
Simulation of dynamic behaviour
Numerical simulation of the dynamic behaviour of the investigated processes and systems (primarily used as a tool for control development)
Signal processing and signal analysis
Processing and analysis of signals with the aim to extract valuable information using methods of digital signal processing, statistics, informatics etc.
Control development
Development of (model-based) controllers for thermochemical, thermal and biotechnological processes and systems
Online estimation of non-measurable quantities
Design of estimators (also referred to as observers or soft sensors) for process variables not measurable during operation (also suitable for monitoring and fault diagnostics)
Numerical optimization – optimization-based energy and resource management systems
Development of modular optimization-based energy and resource management systems ensuring optimal interaction between different facilities and technologies
Self-learning forecasting methods
Self-learning methods for forecasting future yields of volatile energy sources (e.g. photovoltaic or solar thermal) and future energy demands (e.g. electricity, heat)
Implementation and validation
Practical implementation of the methods developed (i.e. controllers, soft sensors, energy management systems etc.) in collaboration with our company partners
Evaluation of the process control and operating behaviour achieved
Know-how transfer
Support and training for company partners throughout the development phase up to market maturity