A Novel Approach to Automated Mechanism Recognition based on Model Discrimination


In this work, a model-based optimization framework is proposed which includes parameter identifiability and estimation, as well as an enhanced model discrimination step. For this purpose, a so-called Automated Mechanism Recognition (AMR) approach has been developed. It allows different models to perform in a collected set of measured data points. Each model stands for a diverse physical mechanism. Based on the developed framework, it is now possible to identify time points, i.e., time intervals where a certain model is valid or more appropriate. Thus, suitable control actions can be carried out in order to increase the process performance. By this means, a better process understanding can be obtained and undesired or even critical process states can be recognized. The application of AMR is demonstrated by means of case studies including a catalytic fixed bed reactor, a two-phase flow system and a biotechnical system.

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@inproceedings{Schneberger2007ANA, title={A Novel Approach to Automated Mechanism Recognition based on Model Discrimination}, author={Jan Sch{\"{o}neberger and Harvey Arellano-Garcia and G{\"{u}nter Wozny}, year={2007} }