Keng Peng Tee

9.8k citations
96 papers · 7.8k indexed · 5 hit papers · h-index 29
Topics
Robot Manipulation and Learning (31 papers)Adaptive Control of Nonlinear Systems (23 papers)Adaptive Dynamic Programming Control (13 papers)

In The Last Decade

Keng Peng Tee

94 papers receiving 7.7k citations

Hit Papers

Barrier Lyapunov Functions for the control of output-cons...20062026201220192009201020112011200650010001.5k2.0k

Peers

Keng Peng Tee
Comparison fields: 5 of 106
  • Control and Systems Engineering 6.4k
  • Computational Theory and Mathematics 2.0k
  • Computer Networks and Communications 1.3k
  • Biomedical Engineering 910
  • Aerospace Engineering 809
Replace Warren E. Dixon with:
Warren E. Dixon United States
J.-J.E. Slotine United States
Chun‐Yi Su Canada
Sandra Hirche Germany
P.J. Gawthrop United Kingdom
Yongping Pan China
Jörg Raisch Germany
Haoyong Yu Singapore
Russ Tedrake United States
D.M. Dawson United States
Keng Peng Tee relative to Warren E. Dixon United States Warren E. Dixon's profile →
Citations per field
00.5×1.5×2.3×
Warren E. Dixon · 1×
Citations per year

Countries citing papers authored by Keng Peng Tee

Since Specialization
Citations

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

Fields of papers citing papers by Keng Peng Tee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Keng Peng Tee. 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 Keng Peng Tee. The network helps show where Keng Peng Tee may publish in the future.

Co-authorship network of co-authors of Keng Peng Tee

This figure shows the co-authorship network connecting the top 25 collaborators of Keng Peng Tee. A scholar is included among the top collaborators of Keng Peng Tee 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 Keng Peng Tee. Keng Peng Tee 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
#WorkIndexed citations
1 4
2 7
3 81
4 113
5 1
6 3
7 6
8 89
9 58
10 3
11
Adaptive Neural Control for Output Feedback Nonlinear Systems Using a Barrier Lyapunov Functionbreakdown →
871
12 6
13 80
14 62
15 243
16 15
17 107
18 17
19 125
20 1

About Keng Peng Tee

Keng Peng Tee is a scholar working on Control and Systems Engineering, Human-Computer Interaction and Computer Vision and Pattern Recognition, having authored 96 papers that have together received 7.8k indexed citations. Recurring topics across this work include Robot Manipulation and Learning (31 papers), Adaptive Control of Nonlinear Systems (23 papers) and Adaptive Dynamic Programming Control (13 papers). The work is most often cited by research in Control and Systems Engineering (6.4k citations), Computational Theory and Mathematics (2.0k citations) and Computer Networks and Communications (1.3k citations). Keng Peng Tee has collaborated with scholars based in Singapore, China and United Kingdom. Frequent co-authors include Shuzhi Sam Ge, Eng Hock Tay, Beibei Ren, T. H. Lee, Zhong-Liang Tang, Wei He, Theodore E. Milner, Etienne Burdet, Rui Yan and Francis E. H. Tay. Their work appears in journals such as Journal of Neuroscience, Automatica and IEEE Transactions on Biomedical Engineering.

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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