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arXiv · 2106.01813

Identification of diffusively coupled linear networks through structured polynomial models

E. M. M.·Kivits·Paul M. J. Van den Hof
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Abstract

Physical dynamic networks most commonly consist of interconnections of physical components that can be described by diffusive couplings. These diffusive couplings imply that the cause-effect relationships in the interconnections are symmetric and therefore physical dynamic networks can be represented by undirected graphs. This paper shows how prediction error identification methods developed for linear time-invariant systems in polynomial form can be configured to consistently identify the parameters and the interconnection structure of diffusively coupled networks. Further, a multi-step least squares convex optimization algorithm is developed to solve the nonconvex optimization problem that results from the identification method.

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E. M. M., Kivits, Paul M. J. Van den Hof. 2021-06-03. Identification of diffusively coupled linear networks through structured polynomial models. https://doi.org/10.1109/tac.2022.3191406

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