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Recursive prediction error identification and scaling of non-linear systems with midpoint numerical integration
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Systems and Control. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control.
2010 (English)In: 2010  American Control Conference: ACC 2010, 2010, 4510-4515 p.Conference paper, Published paper (Refereed)
Abstract [en]

A new recursive prediction error algorithm (RPEM) based on a non-linear ordinary differential equation (ODE) model of black-box state space form is presented. The selected model is discretised by a midpoint integration algorithm and compared to an Euler forward algorithm. When the algorithm is applied, scaling of the sampling time is used to improve performance further. This affects the state vector, the parameter vector and the Hessian. This impact is analysed and described in three Theorems. Numerical examples are provided to verify the theoretical results obtained.

Place, publisher, year, edition, pages
2010. 4510-4515 p.
Series
Proceedings of the American Control Conference, ISSN 0743-1619
National Category
Computational Mathematics
Identifiers
URN: urn:nbn:se:uu:diva-138748ISI: 000287187904150ISBN: 978-1-4244-7427-1 (print)OAI: oai:DiVA.org:uu-138748DiVA: diva2:379731
Conference
American Control Conference Baltimore, MD, JUN 30-JUL 02, 2010
Available from: 2010-07-29 Created: 2010-12-19 Last updated: 2011-04-18Bibliographically approved

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Tayamon, SomaWigren, Torbjörn

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