Discernibility of Topological Variations for Networked LTI Systems
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
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Detail(s)
Original language | English |
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Journal / Publication | IEEE Transactions on Automatic Control |
Online published | 23 Dec 2021 |
Publication status | Online published - 23 Dec 2021 |
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Abstract
In this paper, the discernibility of topological variations for networked linear time-invariant (LTI) systems is investigated, where the network topology is general, and the nodes have identical higher-dimensional dynamics. A necessary and sufficient condition on the discernibility is derived, revealing how the topological variations, node-system dynamics and inner interactions altogether affect the discernibility of the network. Compared with the existing conditions in [28] and [31], which require the network topology to be undirected, this condition is more general. Furthermore, the discernibility of topological variations for multi-agent systems is revisited. A new necessary and sufficient condition is established, and the indiscernible space is completely characterized. Differing from the condition provided in [31], this condition removes the requirements on the multi-agent system and has broader applicability. The effectiveness of the results is demonstrated by several examples.
Research Area(s)
- Artificial neural networks, Brain modeling, discernibility, Eigenvalues and eigenfunctions, indiscernible state, Linear systems, Multi-agent systems, Network topology, Networked systems, topological variation, Topology
Citation Format(s)
Discernibility of Topological Variations for Networked LTI Systems. / Hao, Yuqing; Wang, Qingyun; Duan, Zhisheng; Chen, Guanrong.
In: IEEE Transactions on Automatic Control, 23.12.2021.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review