Ping Gong

985 total citations
30 papers, 784 citations indexed

About

Ping Gong is a scholar working on Computer Networks and Communications, Control and Systems Engineering and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Ping Gong has authored 30 papers receiving a total of 784 indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Computer Networks and Communications, 13 papers in Control and Systems Engineering and 7 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Ping Gong's work include Distributed Control Multi-Agent Systems (23 papers), Neural Networks Stability and Synchronization (21 papers) and Adaptive Control of Nonlinear Systems (12 papers). Ping Gong is often cited by papers focused on Distributed Control Multi-Agent Systems (23 papers), Neural Networks Stability and Synchronization (21 papers) and Adaptive Control of Nonlinear Systems (12 papers). Ping Gong collaborates with scholars based in China, Australia and South Korea. Ping Gong's co-authors include Weiyao Lan, Qing‐Long Han, Kaihong Zhao, Kun Wang, Choon Ki Ahn, Fei Chen, Zhiyao Ma, Qing‐Guo Wang and Guowei Dong and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Automatic Control and Automatica.

In The Last Decade

Ping Gong

26 papers receiving 771 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ping Gong China 15 525 375 133 119 106 30 784
Jiang Wei China 12 199 0.4× 273 0.7× 65 0.5× 292 2.5× 191 1.8× 47 616
Xian‐Feng Zhou China 10 204 0.4× 300 0.8× 64 0.5× 337 2.8× 162 1.5× 31 605
Haydar Akça United Arab Emirates 12 343 0.7× 273 0.7× 56 0.4× 211 1.8× 383 3.6× 35 796
Mingxin Wang China 13 203 0.4× 225 0.6× 99 0.7× 31 0.3× 145 1.4× 42 469
Baowei Wu China 19 440 0.8× 669 1.8× 28 0.2× 74 0.6× 44 0.4× 79 871
Fangcui Jiang China 14 670 1.3× 264 0.7× 131 1.0× 47 0.4× 90 0.8× 24 786
Daniel Melchor‐Aguilar Mexico 14 293 0.6× 455 1.2× 44 0.3× 22 0.2× 96 0.9× 41 597
Jiang Wei China 15 122 0.2× 262 0.7× 35 0.3× 338 2.8× 249 2.3× 43 590
Fanwei Meng China 13 157 0.3× 260 0.7× 23 0.2× 123 1.0× 252 2.4× 45 573
Ferenc Hartung Hungary 16 100 0.2× 331 0.9× 138 1.0× 96 0.8× 282 2.7× 44 622

Countries citing papers authored by Ping Gong

Since Specialization
Citations

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

Fields of papers citing papers by Ping Gong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ping Gong. 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 Ping Gong. The network helps show where Ping Gong may publish in the future.

Co-authorship network of co-authors of Ping Gong

This figure shows the co-authorship network connecting the top 25 collaborators of Ping Gong. A scholar is included among the top collaborators of Ping Gong 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 Ping Gong. Ping Gong 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
1.
Gong, Ping & Qing‐Guo Wang. (2025). Robust adaptive distributed optimization for heterogeneous unknown second-order nonlinear multiagent systems. Science China Information Sciences. 68(4).
2.
Gong, Ping & Choon Ki Ahn. (2025). Robust Adaptive Fuzzy Fixed-Time Distributed Time-Varying Optimization in Unbalanced Nonlinear Second-Order Multiagent Networks. IEEE Transactions on Fuzzy Systems. 33(8). 2730–2742.
3.
Gong, Ping, Qing‐Guo Wang, & Choon Ki Ahn. (2024). Finite-Time Distributed Optimization in Unbalanced Multiagent Networks: Fractional-Order Dynamics, Disturbance Rejection, and Chatter Avoidance. IEEE Transactions on Automation Science and Engineering. 22. 6691–6701. 6 indexed citations
4.
Ma, Zhiyao, et al.. (2023). Adaptive Fuzzy Fault-Tolerant Control of Uncertain Fractional-Order Nonlinear Systems with Sensor and Actuator Faults. Fractal and Fractional. 7(12). 862–862. 4 indexed citations
5.
Gong, Ping, et al.. (2023). Fixed-Time Distributed Time-Varying Optimization for Nonlinear Fractional-Order Multiagent Systems with Unbalanced Digraphs. Fractal and Fractional. 7(11). 813–813. 6 indexed citations
6.
Gong, Ping. (2023). Distributed output-based bipartite consensus for nonlinear fractional-order multi-agent systems with continuous and intermittent communications. SHILAP Revista de lepidopterología. 4. 100028–100028. 1 indexed citations
7.
Gong, Ping, et al.. (2023). A Continuous Algorithm for Finite-Time Consensus of Disturbed Fractional-Order Multiagent Systems Over Digraphs. IEEE Transactions on Circuits & Systems II Express Briefs. 70(11). 4148–4152. 8 indexed citations
8.
Gong, Ping & Qing‐Long Han. (2020). Practical Fixed-Time Bipartite Consensus of Nonlinear Incommensurate Fractional-Order Multiagent Systems in Directed Signed Networks. SIAM Journal on Control and Optimization. 58(6). 3322–3341. 20 indexed citations
9.
Gong, Ping, Qing‐Long Han, & Weiyao Lan. (2020). Finite-Time Consensus Tracking for Incommensurate Fractional-Order Nonlinear Multiagent Systems With Directed Switching Topologies. IEEE Transactions on Cybernetics. 52(1). 65–76. 63 indexed citations
10.
11.
Wang, Kun & Ping Gong. (2019). Multiple positive solutions for a coupled system of nonlinear impulsive fractional differential equations with parameters. Advances in Difference Equations. 2019(1). 1 indexed citations
12.
Gong, Ping & Kun Wang. (2019). Output feedback consensus control for fractional-order nonlinear multi-agent systems with directed topologies. Journal of the Franklin Institute. 357(3). 1473–1493. 19 indexed citations
13.
14.
Gong, Ping, Kun Wang, & Weiyao Lan. (2019). Fully distributed robust consensus control of multi-agent systems with heterogeneous unknown fractional-order dynamics. International Journal of Systems Science. 50(10). 1902–1919. 15 indexed citations
15.
Gong, Ping & Weiyao Lan. (2018). Adaptive robust tracking control for uncertain nonlinear fractional-order multi-agent systems with directed topologies. Automatica. 92. 92–99. 118 indexed citations
16.
Gong, Ping & Weiyao Lan. (2018). Adaptive Robust Tracking Control for Multiple Unknown Fractional-Order Nonlinear Systems. IEEE Transactions on Cybernetics. 49(4). 1365–1376. 77 indexed citations
17.
Zhao, Kaihong & Ping Gong. (2017). Positive solutions of nonlocal integral BVPS for the nonlinear coupled system involving high-order fractional differential. Mathematica Slovaca. 67(2). 447–466. 7 indexed citations
18.
Gong, Ping. (2017). Distributed tracking of heterogeneous nonlinear fractional-order multi-agent systems with an unknown leader. Journal of the Franklin Institute. 354(5). 2226–2244. 66 indexed citations
19.
Gong, Ping. (2016). Distributed consensus of non‐linear fractional‐order multi‐agent systems with directed topologies. IET Control Theory and Applications. 10(18). 2515–2525. 54 indexed citations
20.
Zhao, Kaihong & Ping Gong. (2014). Existence of Positive Solutions for a Class of Higher-Order Caputo Fractional Differential Equation. Qualitative Theory of Dynamical Systems. 14(1). 157–171. 30 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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