Demo Data from EDBT 2026 / reviewers in the wild / expert
Muhammad Faraz Faraz
dblp:262/4419
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1
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 |
Legged, aerial and field robots · 56% Motion planning and robot control · 44% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Legged, aerial and field robots
aerial robots |
0.2 | 1 | 2015 | Robust adaptive control of quadrotor unmanned aerial vehicle with uncertainty · ICRA 2015 |
Robotics › Legged, aerial and field robots › aerial robot control › UAV control
quadrotor control |
0.2 | 1 | 2015 | Robust adaptive control of quadrotor unmanned aerial vehicle with uncertainty · ICRA 2015 |
Robotics › Motion planning and robot control › robot control › adaptive control
robust adaptive control |
0.2 | 1 | 2015 | Robust adaptive control of quadrotor unmanned aerial vehicle with uncertainty · ICRA 2015 |
Robotics › Motion planning and robot control
robot control |
0.1 | 1 | 2015 | Robust adaptive control of quadrotor unmanned aerial vehicle with uncertainty · ICRA 2015 |
Robotics › Motion planning and robot control › robot control
trajectory tracking |
0.1 | 1 | 2015 | Robust adaptive control of quadrotor unmanned aerial vehicle with uncertainty · ICRA 2015 |
Methods — techniques the papers use, named apart from their topics
proportional-derivative control · 0.2lyapunov stability analysis · 0.2backstepping · 0.2adaptive control · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | Robust adaptive control of quadrotor unmanned aerial vehicle with uncertaintyabstractIn this paper, we deal with the stability and tracking control problem of quadrotor unmanned aerial vehicle (UAV) in the presence of the modeling error and disturbance uncertainty. The flight tracking control system combines classical proportional-derivative (PD) like term with robust and adaptive control term. Lyapunov method is used to design and show the asymptotic behavior of the linear and angular states of the vehicle. In contrast with other existing adaptive backstepping design, the proposed design is very simple and easy to implement as it does not require multiple design steps without using augmented signals and known bound of the uncertainty. Various experimental results on quadrotor UAV system are presented to demonstrate the effectiveness of the proposed design for real-time application. Muhammad Faraz Faraz, Reem Ashour, Jorge Dias 0001, Lakmal D. Seneviratne |
ICRA | 2 |