Yun-Chung Chu

1.1k total citations · 1 hit paper
28 papers, 856 citations indexed

About

Yun-Chung Chu is a scholar working on Control and Systems Engineering, Electrical and Electronic Engineering and Artificial Intelligence. According to data from OpenAlex, Yun-Chung Chu has authored 28 papers receiving a total of 856 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Control and Systems Engineering, 6 papers in Electrical and Electronic Engineering and 5 papers in Artificial Intelligence. Recurrent topics in Yun-Chung Chu's work include Advanced Control Systems Optimization (8 papers), Control Systems and Identification (8 papers) and Adaptive Control of Nonlinear Systems (7 papers). Yun-Chung Chu is often cited by papers focused on Advanced Control Systems Optimization (8 papers), Control Systems and Identification (8 papers) and Adaptive Control of Nonlinear Systems (7 papers). Yun-Chung Chu collaborates with scholars based in Singapore, Hong Kong and United Kingdom. Yun-Chung Chu's co-authors include Keck Voon Ling, Wencheng Luo, K. Glover, Yeng Chai Soh, Mark S. K. Lau, Jie Huang, Ann P. Dowling, A. P. Dowling, Michael Z. Q. Chen and Jie Huang and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Automatic Control and Automatica.

In The Last Decade

Yun-Chung Chu

27 papers receiving 836 citations

Hit Papers

Inverse optimal adaptive control for attitude tracking of... 2005 2026 2012 2019 2005 100 200 300
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Inverse optimal adaptive control for attitude tracking of spacecraft
    2005 330 citations Wencheng Luo, Yun-Chung Chu et al. IEEE Transactions on Automatic Control profile →

Peers

Yun-Chung Chu
Humin Lei China
Z.J. Palmor Israel
S. Jagannathan United States
Shunji Manabe Japan
Shubhi Purwar India
D. Normand‐Cyrot France
N. Léchevin Canada
Jean‐Marc Biannic France
Qinghe Wu China
Zongli Lin United States
Humin Lei China
Yun-Chung Chu
Citations per year, relative to Yun-Chung Chu Yun-Chung Chu (= 1×) peers Humin Lei

Countries citing papers authored by Yun-Chung Chu

Since Specialization
Citations

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

Fields of papers citing papers by Yun-Chung Chu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yun-Chung Chu. 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 Yun-Chung Chu. The network helps show where Yun-Chung Chu may publish in the future.

Co-authorship network of co-authors of Yun-Chung Chu

This figure shows the co-authorship network connecting the top 25 collaborators of Yun-Chung Chu. A scholar is included among the top collaborators of Yun-Chung Chu 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 Yun-Chung Chu. Yun-Chung Chu 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.
Hoshino, H., T. John Koo, Yun-Chung Chu, & Yoshihiko Susuki. (2024). Model predictive control of smart districts participating in frequency regulation market: a case study of using heating network storage. SHILAP Revista de lepidopterología. 17(1). 365–377. 1 indexed citations
2.
Chu, Yun-Chung, et al.. (2013). Robust $H_{\infty}$ Receding Horizon Control for a Class of Coordinated Control Problems Involving Dynamically Decoupled Subsystems. IEEE Transactions on Automatic Control. 59(1). 134–149. 9 indexed citations
3.
Chu, Yun-Chung & Michael Z. Q. Chen. (2012). Efficient Model Predictive Algorithms for Tracking of Periodic Signals. Journal of Control Science and Engineering. 2012. 1–13. 6 indexed citations
4.
Chu, Yun-Chung, et al.. (2011). Optimized Dynamic Policy for Receding Horizon Control of Linear Time-Varying Systems With Bounded Disturbances. IEEE Transactions on Automatic Control. 57(4). 973–988. 54 indexed citations
5.
Lau, Mark S. K., et al.. (2010). A general mathematical model of probabilistic ripple-carry adders. Design, Automation, and Test in Europe. 1100–1105. 6 indexed citations
6.
Chu, Yun-Chung, et al.. (2009). Robust MPC with optimized controller dynamics for linear polytopic systems with bounded additive disturbances. Asian Control Conference. 1322–1327. 4 indexed citations
7.
Lau, Mark S. K., Keck Voon Ling, & Yun-Chung Chu. (2009). Energy-aware probabilistic multiplier. 281–290. 68 indexed citations
8.
Luo, Wencheng, Yun-Chung Chu, & Keck Voon Ling. (2005). Inverse optimal adaptive control for attitude tracking of spacecraft. IEEE Transactions on Automatic Control. 50(11). 1639–1654. 330 indexed citations breakdown →
9.
Luo, Wencheng, Yun-Chung Chu, & Keck Voon Ling. (2004). H∞ tracking control of a rigid spacecraft. American Control Conference. 2681–2686. 8 indexed citations
10.
Luo, Wencheng & Yun-Chung Chu. (2004). Attitude control using the SDRE technique. 3. 1281–1286. 16 indexed citations
11.
Luo, Wencheng, Yun-Chung Chu, & Keck Voon Ling. (2004). H/sub /spl infin// tracking control of a rigid spacecraft. 2681–2686 vol.3. 5 indexed citations
12.
Chu, Yun-Chung. (2002). Bounds of the incremental gain for discrete-time recurrent neural networks. IEEE Transactions on Neural Networks. 13(5). 1087–1098. 1 indexed citations
13.
Chu, Yun-Chung. (2002). Further results for systems with repeated scalar nonlinearities. 1. 280–285. 8 indexed citations
14.
Chu, Yun-Chung & K. Glover. (2002). Gain-scheduling for systems with repeated scalar nonlinearities. 1. 406–411.
15.
Chu, Yun-Chung & K. Glover. (2002). Bounds of the induced norm and model reduction errors for a class of nonlinear systems. 4. 4288–4293. 2 indexed citations
16.
Chu, Yun-Chung & K. Glover. (1999). Stabilization and performance synthesis for systems with repeated scalar nonlinearities. IEEE Transactions on Automatic Control. 44(3). 484–496. 51 indexed citations
17.
Chu, Yun-Chung & Jie Huang. (1999). A neural-network method for the nonlinear servomechanism problem. IEEE Transactions on Neural Networks. 10(6). 1412–1423. 26 indexed citations
18.
Chu, Yun-Chung & K. Glover. (1999). Bounds of the induced norm and model reduction errors for systems with repeated scalar nonlinearities. IEEE Transactions on Automatic Control. 44(3). 471–483. 88 indexed citations
19.
Chu, Yun-Chung & Jie Huang. (1998). A neural network method for the nonlinear servomechanism problem. 26. 527–531 vol.1. 3 indexed citations
20.
Chu, Yun-Chung & Jie Huang. (1998). Solving the nonlinear regulator equations by a single layer feedforward neural network. Computers & Industrial Engineering. 35(1-2). 359–362. 1 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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