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Specialized Interior-Point Algorithm for Stable Nonlinear System Identification
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Automatic control. Univ Sydney, Australian Ctr Field Robot, Sch Aerosp Mech & Mechatron Engn, Sydney, NSW 2006, Australia.ORCID iD: 0000-0001-6946-1508
Univ Sydney, Australian Ctr Field Robot, Sch Aerosp Mech & Mechatron Engn, Sydney, NSW 2006, Australia.
2019 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 64, no 6, p. 2442-2456Article in journal (Refereed) Published
Abstract [en]

Estimation of nonlinear dynamic models from data poses many challenges, including model instability and nonconvexity of long-term simulation fidelity. Recently Lagrangian relaxation has been proposed as a method to approximate simulation fidelity and guarantee stability via semidefinite programming (SDP); however, the resulting SDPs have large dimension, limiting their utility in practical problems. In this paper, we develop a path-following interior-point algorithm that takes advantage of special structure in the problem and reduces computational complexity from cubic to linear growth with the length of the dataset. The new algorithm enables empirical comparisons to established methods including nonlinear autoregressive models with exogenous inputs, and we demonstrate superior generalization to new data. We also explore the "regularizing" effect of stability constraints as an alternative to regressor subset selection.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC , 2019. Vol. 64, no 6, p. 2442-2456
Keywords [en]
Nonlinear system identification, optimization algorithms, stability of nonlinear systems
National Category
Control Engineering
Identifiers
URN: urn:nbn:se:uu:diva-387931DOI: 10.1109/TAC.2018.2867358ISI: 000469913800017OAI: oai:DiVA.org:uu-387931DiVA, id: diva2:1331756
Funder
Australian Research Council, DP130100551; DP150100577Available from: 2019-06-27 Created: 2019-06-27 Last updated: 2019-06-27Bibliographically approved

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Umenberger, Jack

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