Genetic Programming Based Model Structure Identification using on-line System Data
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Genetic Programming, an heuristic optimization technique based on the theory of Genetic Algorithms, is a method successfully used to identify nonlinear model structures by analyzing a system's measured signals. Mostly, it is used as an offline tool which means that structural analysis is done after collecting all available identification data. In this paper, we propose an enhanced on-line GP approach that is able to adapt its behaviour to new observations while the GP process is executed. As an example we document how a model for a BMW diesel engine’s NOx exhausts was identified using on-line measurement data provided by an real-time data simulator environment.
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Conceptual Modeling and Simulation Conference - CMS 2005, October 20-22, 2005; Marseilles, France