Thomas Dötschel

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The design of robust control techniques is the prerequisite to guarantee maximum efficiency and lifetime for high-temperature fuel cells with constant and varying electrical load. For the design of such control laws as well as for the development of model-based observer approaches, it is essential to derive low-dimensional mathematical models which can be(More)
The design of reliable and robust control strategies for the automatized operation of SOFC systems in a decentralized power grid demands for the use of nonlinear dynamic system models with a large number of physical parameters. These models have to cover the most dominant nonlinear effects and include knowledge about the uncertainty of specific parameters.(More)
Mathematical models for the dynamics of high-temperature Solid Oxide Fuel Cells (SOFCs) can be subdivided into thermal, fluidic, and electro-chemical system components. For the purpose of automatic control design of such systems, it is especially important to focus on the thermal subsystem. This results from the fact that high operating temperatures are(More)
Model-predictive control approaches are well-known means to stabilize dynamical systems and to compute input signals online which allow for the tracking of desired state trajectories. These control procedures, which are partially implemented by means of algorithmic differentiation, are inherently robust and can, therefore, be used to compensate unknown(More)
For nonlinear systems, feedback control strategies have to be parameterized in such a way that they guarantee asymptotic stability in a certain neighborhood of desired operating points or desired trajectories. Due to not exactly known initial conditions, parameter uncertainties, and measurement errors characterizing dynamic system models in real(More)
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