Iterative Learning Control Systems
Iterative Learning Control Systems is a research topic within Control and Systems Engineering. Science Explorer counts 33k research works in it since 1950. 15.1% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on Iterative Learning Control (ILC) and its applications in engineering practice. It covers topics such as repetitive control, model-free adaptive control, data-driven control, motion control, robotic systems, feed drive systems, batch processes, nonlinear systems, and convergence analysis.
- Iterative Learning Control
- Repetitive Control
- Model-Free Adaptive Control
- Data-Driven Control
- Motion Control
- Robotic Systems
- Feed Drive Systems
- Batch Processes
- Nonlinear Systems
- Convergence Analysis
- Research works
- 33k fractional, since 1950
- In the world top 10%
- 4.9k per year above
- Top-10% rate
- 15.1% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- -4% the tick is no change
Which countries lead Iterative Learning Control Systems research?
By volume, China and the United States publish the most (2.8k and 231 works in 2022–2025).
By volume, 2022–2025
- 1 China 2.8k works
- 2 United States 231 works
- 3 India 197 works
- 4 Japan 193 works
- 5 Germany 120 works
- 6 South Korea 111 works
- 7 United Kingdom 104 works
- 8 Italy 81 works
- 9 France 78 works
- 10 Vietnam 69 works
How concentrated that is
The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.
Shares of the rows listed above, not of the whole node.
Which institutions lead Iterative Learning Control Systems research?
By volume in 2022–2025, Harbin Institute of Technology publishes the most Iterative Learning Control Systems research, followed by Nanjing University of Science and Technology and Beihang University.
By volume, 2022–2025
- 1 Harbin Institute of TechnologyChina 121 works
- 2 Nanjing University of Science and TechnologyChina 60 works
- 3 Beihang UniversityChina 49 works
- 4 Huazhong University of Science and TechnologyChina 48 works
- 5 Nanjing University of Aeronautics and AstronauticsChina 47 works
- 6 Southeast UniversityChina 44 works
- 7 Northwestern Polytechnical UniversityChina 41 works
- 8 Beijing Institute of TechnologyChina 41 works
- 9 Zhejiang UniversityChina 40 works
- 10 Tsinghua UniversityChina 40 works
Who are the leading researchers in Iterative Learning Control Systems?
The most-cited researchers publishing on Iterative Learning Control Systems include Frede Blaabjerg, José Rodríguez and Peng Shi.
- 1 Frede Blaabjerg Denmark 12k citations
- 2 José Rodríguez Chile 6.8k citations
- 3 Peng Shi Australia 5k citations
- 4 Jinde Cao China 4.2k citations
- 5 Frank L. Lewis United States 3.8k citations
- 6 C. L. Philip Chen Macau 3.6k citations
- 7 Manfred Morari Switzerland 3.4k citations
- 8 Lihua Xie Singapore 3.2k citations
- 9 Miroslav Krstić United States 3.1k citations
- 10 A. Stephen Morse United States 2.9k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Iterative Learning Control Systems research done?
The largest centres of Iterative Learning Control Systems research in 2022–2025 are Beijing (China), Nanjing (China), Shanghai (China) and Harbin (China). Among places with at least 20 works in it, it is an unusually large share of all research in Qinhuangdao and Eindhoven.
Largest cities, 2022–2025
Where it is the local speciality
- QinhuangdaoCN · 35.6 works18×
- EindhovenNL · 21.9 works9.9×
Location quotient: how much more of its research is in Iterative Learning Control Systems than the world average.
Where is the best place to study Iterative Learning Control Systems?
Among universities, judged by research, Qingdao University, Bohai University and Harbin Institute of Technology score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Qingdao UniversityChina | 75.6 | 33.7% | 11.3× | 30 | +187.5% |
| 2 | Bohai UniversityChina | 65.8 | 39.9% | 21.4× | 11 | +90.4% |
| 3 | Harbin Institute of TechnologyChina | 64.5 | 20.2% | 15.3× | 121 | -3.8% |
| 4 | Northeastern UniversityChina | 55.3 | 22.9% | 9.2× | 39 | -12.5% |
| 5 | Nanjing University of Science and TechnologyChina | 54.1 | 14.3% | 15.2× | 60 | -10.6% |
| 6 | Beihang UniversityChina | 51.0 | 15.0% | 9.1× | 48 | -4.1% |
| 7 | Nanjing University of Aeronautics and AstronauticsChina | 49.3 | 11.5% | 10.9× | 47 | -27.6% |
| 8 | Hong Kong Polytechnic UniversityHong Kong | 48.8 | 27.8% | 2.1× | 9 | +241.9% |
| 9 | Hanoi University of Science and TechnologyVietnam | 47.4 | 14.3% | 13.2× | 12 | — |
| 10 | Qingdao University of Science and TechnologyChina | 46.8 | 11.6% | 17.1× | 30 | -11.3% |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Iterative Learning Control Systems research growing?
Output in 2018–2022 was 4% lower than in 2013–2017, peaking in 2024.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Which topics inside it are moving
Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.