| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Electronics and Electrical Engineering | 70 | 342 | 1040 | 39 |
| Mechanical and Aerospace Engineering | 153 | 50 | 116 | 17 |
| Engineering and Technology | 240 | 100 | 288 | 28 |
The aim of the journal is to expand the discussion of research in Control theory, Nonlinear system, Control theory, Mathematical optimization and Control engineering. International Journal of Robust and Nonlinear Control features Control theory research that overlaps with concepts in Control (management). Research on Control (management) addressed in it frequently intersections with the field of Tracking (particle physics).
The concepts on Nonlinear system presented in the journal can also apply to other research fields, including Bounded function and Applied mathematics. Discussions in it are anchored in the subject of Control theory and the similar topic of Observer (quantum physics). Some problems in Mathematical optimization that were presented in it overlapped with concepts under Stability (learning theory) and Model predictive control.
It focuses on Control engineering but the discussions also offer insight into other areas such as Control system and Actuator.
The published papers mostly deal with topics like Control theory, Nonlinear system, Mathematical optimization, Control theory and Control engineering. The journal papers investigate Control theory research which frequently intersects with Bounded function. The Control engineering research presented in the journal articles focuses mostly on Control (management) and, on occasion, topics in Multi-agent system.
International Journal of Robust and Nonlinear Control focuses largely on the fields of Control theory, Nonlinear system, Control (management), Event triggered and Control (linguistics). The work on Control theory tackled in International Journal of Robust and Nonlinear Control brings together disciplines like Tracking (particle physics) and Stability (probability). International Journal of Robust and Nonlinear Control explores topics in Nonlinear system which can be helpful for research in disciplines like Artificial neural network, Class (set theory), Multi-agent system and Applied mathematics.
The study on Multi-agent system presented in International Journal of Robust and Nonlinear Control intersects with subjects under the field of Distributed computing.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in International Journal of Robust and Nonlinear Control (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in International Journal of Robust and Nonlinear Control (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 1.24% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 23.92% were posted by at least one author from the top 10 institutions publishing in the journal. Another 9.35% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 20.68% of all publications and 46.04% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Kunyu Wang;Kunyu Wang;Engang Tian;Engang Tian;Jinliang Liu;Linnan Wei
(2020)Unknown
(2022)Yong Xu;Mei Fang;Ya-Jun Pan;Kaibo Shi
(2021)Unknown
(2021)Xueli Wang;Derui Ding;Derui Ding;Xiaohua Ge;Qing-Long Han
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French Institute for Research in Computer Science and Automation - INRIA
Publications: 12
