Gray box identification using difference of convex programming

Gray box identification using difference of convex programming

Yu, C. (TU Delft Team Raf Van de Plas)
Ljung, Lennart (Linköping University)
Verhaegen, M.H.G. (TU Delft Team Raf Van de Plas)

Dochain, Denis (editor)
Henrion, Didier (editor)
Peaucelle, Dimitri (editor)

2017

Gray-box identification is prevalent in modeling physical and networked systems. However, due to the non-convex nature of the gray-box identification problem, good initial parameter estimates are crucial for a successful application. In this paper, a new identification method is proposed by exploiting the low-rank and structured Hankel matrix of impulse response. This identification problem is recasted into a difference-of-convex programming problem, which is then solved by the sequential convex programming approach with the associated initialization obtained by nuclear-norm optimization. The presented method aims to achieve the maximum impulse-response fitting while not requiring additional (non-convex) conditions to secure non-singularity of the similarity transformation relating the given state-space matrices to the gray-box parameterized ones. This overcomes a persistent shortcoming in a number of recent contributions on this topic, and the new method can be applied for the structured state-space realization even if the involved system parameters are unidentifiable. The method can be used both for directly estimating the gray-box parameters and for providing initial parameter estimates for further iterative search in a conventional gray-box identification setup.

convex-concave procedure
Structured state-space model

http://resolver.tudelft.nl/uuid:0f32cbc6-455d-4368-89fb-4e34303b7c16

https://doi.org/10.1016/j.ifacol.2017.08.1469

Elsevier, Laxenburg, Austria

IFAC-PapersOnLine: Proceedings 20th IFAC World Congress, 50-1

20th World Congress of the International Federation of Automatic Control (IFAC), 2017, 2017-07-09 → 2017-07-14, Toulouse, France

IFAC-PapersOnLine, 50 (1)

Institutional Repository

conference paper

© 2017 C. Yu, Lennart Ljung, M.H.G. Verhaegen