Bipartite Tracking Consensus of Linear Multi-Agent Systems With a Dynamic Leader

258 indexed citations

Abstract

loading...

About

This paper, published in 2017, received 258 indexed citations. Written by Guanghui Wen, He Wang, Xinghuo Yu and Wenwu Yu covering the research area of Control and Systems Engineering and Computer Networks and Communications. It is primarily cited by scholars working on Computer Networks and Communications (247 citations), Control and Systems Engineering (122 citations) and Public Health, Environmental and Occupational Health (36 citations). Published in IEEE Transactions on Circuits & Systems II Express Briefs.

Countries where authors are citing Bipartite Tracking Consensus of Linear Multi-Agent Systems With a Dynamic Leader

Specialization
Citations

This map shows the geographic impact of Bipartite Tracking Consensus of Linear Multi-Agent Systems With a Dynamic Leader. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Bipartite Tracking Consensus of Linear Multi-Agent Systems With a Dynamic Leader with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bipartite Tracking Consensus of Linear Multi-Agent Systems With a Dynamic Leader more than expected).

Fields of papers citing Bipartite Tracking Consensus of Linear Multi-Agent Systems With a Dynamic Leader

Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of Bipartite Tracking Consensus of Linear Multi-Agent Systems With a Dynamic Leader. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Bipartite Tracking Consensus of Linear Multi-Agent Systems With a Dynamic Leader.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

This paper is also available at doi.org/10.1109/tcsii.2017.2777458.

Explore hit-papers with similar magnitude of impact

Rankless by CCL
2026