Kalman filtering for black-box identification of nonlinear ODE models
2006 (Swedish)In: Reglermöte 2006, 2006Conference paper (Refereed)
Two techniques for recursive identification of systems described by nonlinear ordinary differential equation models are discussed. The model is of black–box state space type, where the right–hand side function is estimated as a multi–variate polynomial in the states and input, with the parameters selected to be the polynomial coefficients. An algorithm based on Kalman filtering techniques is evaluated and compared to an RPEM. The Kalman filter based algorithm is e.g. suitable for initiation of the RPEM method as they are both based on the same model. In the paper the algorithm performance of the Kalman filter based method
is compared to that of the RPEM using a numerical example and live data from a cascaded tanks process.
Place, publisher, year, edition, pages
IdentifiersURN: urn:nbn:se:uu:diva-12993OAI: oai:DiVA.org:uu-12993DiVA: diva2:40763