One focus of the SR institute is the development and implementation of modern model-based control methods. These approaches use a mathematical model of the controlled system in order to explicitly predict and improve its behavior.
Using inverse dynamical models in control algorithms allows, for example, compensating undesired elastic effects. By using robust control techniques it is additionally possible to directly account for the unmodelled uncertainty of the systems. Optimization-based methods make it possible to further manage over actuated systems and to follow trajectories with highest accuracy. Adaptive and fault-tolerant control methods react flexibly to the system’s state and reconfigure the system in case of a failure.
By consistently applying modern control methods, more lightweight systems can be designed and their efficiency can be improved considerably. The tight integration of modelling, optimization, and control additionally allows the holistic design of the controlled system with regard to its system dynamics within the framework of a multidisciplinary design optimization.
Development of robust fault diagnosis methods is a prerequisite for the design of advanced fault-tolerant control laws with event-driven reconfiguration capabilities. Main applications are safety, reliability, and performance in automatization of ground and air vehicles.
The competences of the SR institute in the field of design of robust fault diagnosis systems as well as design of fault-tolerant control laws have been successfully applied in several EU projects and in close cooperation with industry (e.g. Airbus). Efficient methods and tools for design and implementation of model and signal-based fault diagnosis systems have been developed at the institute.