[11] Synchronization preserving model reduction of multi-agent network systems by eigenvalue assignments.
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发表刊物：in Proceedings of 58th IEEE Control and Decision Conference, Nice, France Dec. 2019.
摘要：In this paper, the structure-preserving model reduction problem for multi-agent network systems consisting of diffusively coupled agents is investigated. A new model reduction method based on eigenvalue assignment is derived. Particularly, the spectrum of the reduced Laplacian matrix is selected as a subset of the spectrum of the original Laplacian matrix. The resulting reduced-order model retains the network protocol of diffusive couplings, and thus the synchronization property is preserved. Moreover, a concise expression for the upper-bound of the H2 approximation error is presented in the setting of a leader-follower network, and it provides a guideline to select the eigenvalues of the reduced Laplacian matrix. The effectiveness of the proposed method is finally illustrated via the application to a spacecraft network, with a comparison of performances with the graph clustering method in [1] and balanced truncation approach in [2].
合写作者：成晓东,Jacquelien M.A. Scherpen,熊军林
第一作者：余兰林
论文类型：论文集
是否译文：否
发表时间：2019-12-11
收录刊物：EI
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