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Reem Ashour

dblp:205/3813 · also Reem K. Ashour · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2015
0000-0002-0928-7904ORCID · verified

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

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots
aerial robots
0.212015
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
0.212015
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
0.212015
Robust adaptive control of quadrotor unmanned aerial vehicle with uncertainty · ICRA 2015
Robotics › Motion planning and robot control
robot control
0.112015
Robust adaptive control of quadrotor unmanned aerial vehicle with uncertainty · ICRA 2015
Robotics › Motion planning and robot control › robot control
trajectory tracking
0.112015
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
YearPublicationVenuePosition
2015 Robust adaptive control of quadrotor unmanned aerial vehicle with uncertainty
abstract
In 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
ICRA3