Established in 2005 under support of MŠMT ÈR (project 1M0572)

Publications

Adaptive continuous hierarchical model-based decision making

Typ:
Conference paper
Proceedings name:
Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics
Publisher:
SciTePress – Science and Technology Publications
Serie:
Portugalsko
Year:
2011
ISBN:
978-989-8425-74-4
Keywords:
Bayesian modelling, Hierarchical model, Parameter estimation
Anotation:
Industrial model-based control often relies on parametric models. However, for certain operational conditions either the precise underlying physical model is not available or the lack of relevant or reliable data prevents its use. A popular approach is to employ the black box or grey box models, releasing the theoretical rigor. This leads to several candidate models being at disposal, from which the (often subjectively) prominent one is selected. However, in the presence of model uncertainty, we propose to benefit from a subset of credible models. The idea behind the multimodelling approach is closely related to hierarchical modelling methodology. By using several modelling levels, it is possible to achieve relatively high quality and robust solution, providing a way around typical constraints in industrial applications.
 
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