Ontwikkeling van online gekoppelde toestands-/krachts -/parameterschatting voor flexibele meerlichamensystemen.

The future of smart, connected mechanical systems will strongly rely on a digital representation of these systems and their functional performance. This holds for design analysis but also for motion and condition tracking through state/input/parameter estimation during the life-cycle of the system. Especially this last application typically requires multiple high-fidelity numerical simulation runs, which is too computationally expensive using current modeling approaches. This project proposes a novel adaptively reduced approach for the simulation of these mechanical systems. Model reduction allows to drastically lower the computational load of a model by generating a consistent approximation of this model. However, it is often difficult to properly define this reduction before the model is actually used. By using adaptive techniques with an online adjustable reduced model, the model can start from a typical reference model and can then be automatically tailored to the specific application in which it is used, as the model learns its own behavior. A holistic methodology is pursued in this research where all stages from original model description, to model reduction, time integration and actual state-estimation are investigated. This allows for a fully integrated approach specifically tailored to the modeling problems encountered in many mechanical systems, like large motions with small deformations and large local deformations.