Xing‐Gang Yan

6.2k total citations · 1 hit paper
207 papers, 4.8k citations indexed

About

Xing‐Gang Yan is a scholar working on Control and Systems Engineering, Computer Networks and Communications and Electrical and Electronic Engineering. According to data from OpenAlex, Xing‐Gang Yan has authored 207 papers receiving a total of 4.8k indexed citations (citations by other indexed papers that have themselves been cited), including 165 papers in Control and Systems Engineering, 40 papers in Computer Networks and Communications and 26 papers in Electrical and Electronic Engineering. Recurrent topics in Xing‐Gang Yan's work include Adaptive Control of Nonlinear Systems (103 papers), Stability and Control of Uncertain Systems (83 papers) and Fault Detection and Control Systems (42 papers). Xing‐Gang Yan is often cited by papers focused on Adaptive Control of Nonlinear Systems (103 papers), Stability and Control of Uncertain Systems (83 papers) and Fault Detection and Control Systems (42 papers). Xing‐Gang Yan collaborates with scholars based in United Kingdom, China and United States. Xing‐Gang Yan's co-authors include Christopher Edwards, Sarah K. Spurgeon, Zehui Mao, Qingling Zhang, Bin Jiang, Dezhi Xu, Kangkang Zhang, Leonid Fridman, Yuri Shtessel and Jinghao Li and has published in prestigious journals such as IEEE Transactions on Automatic Control, IEEE Transactions on Industrial Electronics and Automatica.

In The Last Decade

Xing‐Gang Yan

197 papers receiving 4.7k citations

Hit Papers

Nonlinear robust fault re... 2007 2026 2013 2019 2007 100 200 300 400

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Xing‐Gang Yan United Kingdom 40 4.0k 861 704 475 293 207 4.8k
Alessandro Pisano Italy 38 4.1k 1.0× 803 0.9× 890 1.3× 902 1.9× 133 0.5× 212 5.1k
Michaël Defoort France 32 3.2k 0.8× 1.6k 1.9× 577 0.8× 568 1.2× 135 0.5× 137 4.4k
María M. Serón Australia 30 4.5k 1.1× 336 0.4× 728 1.0× 256 0.5× 225 0.8× 219 5.2k
Bo Bernhardsson Sweden 24 3.4k 0.9× 1.7k 2.0× 661 0.9× 306 0.6× 357 1.2× 87 5.0k
Weisheng Yan China 30 1.9k 0.5× 1.4k 1.6× 392 0.6× 205 0.4× 362 1.2× 222 3.4k
Farshad Khorrami United States 32 3.1k 0.8× 706 0.8× 810 1.2× 275 0.6× 413 1.4× 297 4.1k
Emmanuel G. Collins United States 26 2.4k 0.6× 528 0.6× 641 0.9× 340 0.7× 494 1.7× 197 3.7k
Quanmin Zhu United Kingdom 41 3.6k 0.9× 560 0.7× 596 0.8× 476 1.0× 1.0k 3.5× 304 4.8k
H.N. Koivo Finland 29 3.4k 0.8× 524 0.6× 1.7k 2.4× 927 2.0× 477 1.6× 223 5.1k
Jun Fu China 39 3.6k 0.9× 1.6k 1.9× 466 0.7× 228 0.5× 397 1.4× 239 4.9k

Countries citing papers authored by Xing‐Gang Yan

Since Specialization
Citations

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

Fields of papers citing papers by Xing‐Gang Yan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xing‐Gang Yan. 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 Xing‐Gang Yan. The network helps show where Xing‐Gang Yan may publish in the future.

Co-authorship network of co-authors of Xing‐Gang Yan

This figure shows the co-authorship network connecting the top 25 collaborators of Xing‐Gang Yan. A scholar is included among the top collaborators of Xing‐Gang Yan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Xing‐Gang Yan. Xing‐Gang Yan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Zhao, Dongya, et al.. (2024). Model-free adaptive tensor product control for a class of nonlinear systems. Control Engineering Practice. 147. 105912–105912. 2 indexed citations
4.
Zhou, Chao, et al.. (2024). Adaptive cooperating fault-tolerant formation control for multi-agent systems with double Markovian switching topologies and actuator faults. Systems & Control Letters. 191. 105865–105865. 1 indexed citations
5.
Yang, Weilin, et al.. (2023). An improved neural networks-based vector control approach for permanent magnet linear synchronous motor. Journal of the Franklin Institute. 361(4). 106565–106565. 4 indexed citations
6.
Zhang, Qian, et al.. (2023). Design and Control of an Innovative Overactuated Thrust Vectoring Six-DoF Quadrotor for Extreme and Challenging Environments. Unmanned Systems. 13(2). 345–361. 1 indexed citations
7.
Yang, Weilin, Jiayu Chen, Dezhi Xu, & Xing‐Gang Yan. (2021). Hierarchical global fast terminal sliding‐mode control for a bridge travelling crane system. IET Control Theory and Applications. 15(6). 814–828. 14 indexed citations
8.
Zhao, Dongya, et al.. (2019). Output Feedback Sliding Mode Control for Continuous Stirred Tank Reactors. Kent Academic Repository (University of Kent). 1443–1448. 3 indexed citations
9.
Liu, Wanquan, Xing‐Gang Yan, Shoudong Huang, Chunyu Yang, & Guoliang Wang. (2018). Advanced Control for Singular Systems with Applications. Mathematical Problems in Engineering. 2018. 1–2. 1 indexed citations
10.
Khan, Mohammad Farhan, Sarah K. Spurgeon, & Xing‐Gang Yan. (2018). Modeling and Dynamic Behavior of eIF2 Dependent Regulatory System With Disturbances. IEEE Transactions on NanoBioscience. 17(4). 518–524. 2 indexed citations
11.
Vesia, Michael, S.S. Prime, Xing‐Gang Yan, Lauren E. Sergio, & J. Douglas Crawford. (2010). Parietal regions specialized for saccades and reach in the human: a rTMS study. Journal of Vision. 10(7). 1093–1093. 1 indexed citations
12.
Spurgeon, Sarah K., et al.. (2010). A sliding mode observer for estimating substrate consumption rate in a fermentation process. 17. 172–177. 3 indexed citations
13.
Yan, Xing‐Gang, et al.. (2010). Sliding Mode Observer based Control for a Continuous Fermentation Process. Kent Academic Repository (University of Kent). 854–859. 3 indexed citations
14.
Yan, Xing‐Gang, et al.. (2009). Static output feedback sliding mode control for time‐varying delay systems with time‐delayed nonlinear disturbances. International Journal of Robust and Nonlinear Control. 20(7). 777–788. 51 indexed citations
15.
Yan, Xing‐Gang, Christopher Edwards, & Sarah K. Spurgeon. (2004). Output feedback sliding mode control for nonminimum phase systems with nonlinear disturbances. UCL Discovery (University College London). 3. 1951–1957. 2 indexed citations
16.
Yan, Xing‐Gang. (2003). Control scheme for redundant parallel UPS with instantaneous current sharing. Journal of Tsinghua University(Science and Technology). 1 indexed citations
17.
Yan, Xing‐Gang, I‐Ming Chen, & James Lam. (2001). D-Type learning control for nonlinear time-varying systems with unknown initial states and inputs. Transactions of the Institute of Measurement and Control. 23(2). 69–82. 23 indexed citations
18.
Yan, Xing‐Gang. (2000). Learning Control for Nonlinear System and Its Application in Robot. Kent Academic Repository (University of Kent). 2 indexed citations
19.
Yan, Xing‐Gang, et al.. (2000). Decentralized Control of Nonlinear Large-Scale Systems Using Dynamic Output Feedback. Journal of Optimization Theory and Applications. 104(2). 459–475. 25 indexed citations
20.
Yan, Xing‐Gang & Siying Zhang. (1997). Design of Robust Controllers with Similar Structure for Nonlinear Uncertain Composite Large-Scale Systems Possessing Similarity. Kent Academic Repository (University of Kent). 6 indexed citations

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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