This work proposes a Compact Model Synthesis (CMS) for Partially Observed Operational Systems (POOS) without using the complete knowledge of models. Series of “grey boxes” fed with partial observations are built in order to synthesize target variables with compact models. The recursive process for real time computation is based on Kalman Filters (KF). This stochastic approach allows to converge in line toward deterministic models with estimated uncertainties and without intrusion on the complete model process. Mathematical context is described first and illustrated secondly with two examples.
- Design Engineering Division
- Computers and Information in Engineering Division
Compact Model Synthesis for Partially Observed Operational Systems
Dion, J, Abid, F, Chevallier, G, Festjens, H, Peyret, N, Renaud, F, Seifeddine, M, & Stephan, C. "Compact Model Synthesis for Partially Observed Operational Systems." Proceedings of the ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. Volume 7B: 9th International Conference on Multibody Systems, Nonlinear Dynamics, and Control. Portland, Oregon, USA. August 4–7, 2013. V07BT10A036. ASME. https://doi.org/10.1115/DETC2013-12111
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