Jun Fu

6.5k citations
239 papers · 4.9k indexed · 2 hit papers · h-index 39

Jun Fu

220 papers receiving 4.8k citations

Hit Papers

Event-Triggered Approximate Optimal Pa...1692015202620182022100200300

Peers

Jun Fu
Comparison fields: 5 of 124
  • Control and Systems Engineering 3.6k
  • Computer Networks and Communications 1.6k
  • Computational Theory and Mathematics 657
  • Aerospace Engineering 447
  • Energy Engineering and Power Technology 52
Replace Shuping He with:
Shuping He China
Kun Liu China
Xing‐Gang Yan United Kingdom
Jian Liu China
Feng Xiao China
Xiaona Song China
Zhang Ren China
Teodoro Álamo Spain
Vijay Gupta United States
Zhiyun Lin China
Jun Fu relative to Shuping He China Shuping He's profile →
Citations per field
00.5×
Shuping He · 1×
Citations per year

Countries citing papers authored by Jun Fu

Since Specialization
Citations

This map shows the geographic impact of Jun Fu's research. 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 Jun Fu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Fu more than expected).

Fields of papers citing papers by Jun Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun Fu. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jun Fu. The network helps show where Jun Fu may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Jun Fu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jun Fu Line = papers co-authored together Jun Fu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202510
2 20247
3 20249
4 20240
5 20243
6 202335
7 20233
8 202252
9 202174
10 202126
11 202053
12 202028
13 201931
14 201983
15 201851
16 201843
17 201830
18 2017137
19
Robust control of SVC: A new adaptive backstepping method
20069
20
Novel Adaptive Backstepping Method for TCSC Control
20063

About Jun Fu

Jun Fu is a scholar working on Control and Systems Engineering, Computer Networks and Communications, Energy Engineering and Power Technology, Computational Theory and Mathematics and Statistical and Nonlinear Physics, having authored 239 papers that have together received 4.9k indexed citations. Recurring topics across this work include Adaptive Control of Nonlinear Systems (71 papers), Stability and Control of Uncertain Systems (66 papers), Advanced Control Systems Optimization (34 papers), Control and Stability of Dynamical Systems (26 papers), Fault Detection and Control Systems (26 papers), Distributed Control Multi-Agent Systems (24 papers), Neural Networks Stability and Synchronization (23 papers) and Adaptive Dynamic Programming Control (17 papers). The work is most often cited by research in Control and Systems Engineering (3.6k citations), Computer Networks and Communications (1.6k citations), Computational Theory and Mathematics (657 citations), Aerospace Engineering (447 citations) and Energy Engineering and Power Technology (52 citations). Jun Fu has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Tianyou Chai, Ruicheng Ma, Tai‐Fang Li, Chun‐Yi Su, Ying Jin, Youmin Zhang, Ziquan Yu, Ruicheng Ma, Yue Fu and Jun Zhao. Their work appears in journals such as IEEE Transactions on Systems Man and Cybernetics Systems, Automatica, IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Cybernetics and IEEE Transactions on Automatic Control.

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.

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