[Zurück]

C. Hametner, S. Jakubek:
"Combustion Engine Modelling using an Evolving Local Model Network";
Vortrag: 2011 IEEE International Conference On Fuzzy Systems, Taipei, Taiwan; 27.06.2011 - 30.06.2011; in: "Proceedings of the 2011 IEEE International Conference On Fuzzy Systems", (2011), ISBN: 978-1-4244-7316-8; S. 2802 - 2807.

In this paper a new evolving parameter estimation
algorithm for a local model network under special consideration
of combustion engine modelling is presented. For practical applications
computational speed, incorporation of prior knowledge
and the interpretability of the local models is of great interest.
Accordingly, a robust and efficient online training algorithm with
a particular focus on computational requirements involved in
dynamic system identification of complex nonlinear processes
is presented. The incremental construction of the model tree
allows to gradually increase the model complexity while a proper
initialisation of new model parameters is easily possible. The
proposed evolving local model network is validated using real
measurement data from a state-of-the-art 4-cylinder EURO5
diesel engine.

System identification, local model network, online learning, engine modelling