Demo Data from SIGIR 2026 / reviewers in the wild / expert
Issam Zeinoun
dblp:31/3361
· DBLP profile ↗
1ranked-venue papers
1as first author
0since 2021 · last 1994
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Artificial intelligence
1 paper |
Motion planning and robot control · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › robot control
adaptive control |
0.0 | 1 | 1994 | Fuzzy Based Adaptive Control for Flexible-Link Manipulators Actuated by Piezoceramics · ICRA 1994 |
Robotics › Motion planning and robot control › manipulator control
flexible-link manipulator control |
0.0 | 1 | 1994 | Fuzzy Based Adaptive Control for Flexible-Link Manipulators Actuated by Piezoceramics · ICRA 1994 |
Robotics › Motion planning and robot control
robot control |
0.0 | 1 | 1994 | Fuzzy Based Adaptive Control for Flexible-Link Manipulators Actuated by Piezoceramics · ICRA 1994 |
Methods — techniques the papers use, named apart from their topics
fuzzy logic · 0.0adaptive control · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 1994 | Fuzzy Based Adaptive Control for Flexible-Link Manipulators Actuated by PiezoceramicsabstractThis paper presents an adaptive control scheme based on a fuzzy logic algorithm and its application to end-effector positioning of flexible-link manipulators. Here, a fuzzy based adaptive controller is considered due to its simplicity and the fact that it does not require expressing the controller in terms of the system parameters, as it is necessary in the case of self-tuning regulators. This controller is based on a functional fuzzy model where the consequents are crisp functions represent controllers designed for different operating regimes. The premise is constituted by the fuzzy subsets corresponding to the process parameters estimated in real time. The effectiveness of this new scheme is verified on a clamped free beam and a single-line flexible arm instrumented with piezoceramic sensors and actuators. It is shown that robust performance may be achieved in face of large parameter variations.> Issam Zeinoun, Farshad Khorrami |
ICRA | 1 |