Robustness of First- and Second-Order Consensus Algorithms for a Noisy Scale-Free Small-World Koch Network
In this brief, we study first- and second-order consensus algorithms for the scale-free small-world Koch network, where vertices are subject to white noise. We focus on three cases of consensus schemes: (1) first-order leaderless algorithm; (2) first-order algorithm with a single leader; and (3) sec...
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| Published in: | IEEE transactions on control systems technology Vol. 25; no. 1; pp. 342 - 350 |
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| Main Authors: | , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York
IEEE
01.01.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects: | |
| ISSN: | 1063-6536, 1558-0865 |
| Online Access: | Get full text |
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| Summary: | In this brief, we study first- and second-order consensus algorithms for the scale-free small-world Koch network, where vertices are subject to white noise. We focus on three cases of consensus schemes: (1) first-order leaderless algorithm; (2) first-order algorithm with a single leader; and (3) second-order leaderless algorithm. We are concerned with the coherence of the Koch network in the H 2 norm, which captures the level of agreement of vertices in face of stochastic disturbances. Based on the particular network construction, we derive explicit expressions of the coherence for all the three consensus algorithms, as well as their dependence on the network size. Particularly, for the first-order leader-follower model, we show that coherence relies on the shortest-path distance between the leader and the largest-degree vertices, as well as the degree of the leader. The asymptotic behaviors for coherence of the three consensus algorithms in Koch network behave differently from those associated with other networks lacking scale-free small-world features, indicating significant influences of the scale-free small-world topology on the performance of the consensus algorithms in noisy environments. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 1063-6536 1558-0865 |
| DOI: | 10.1109/TCST.2016.2550582 |