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Chaojun Qin

dblp:383/4603 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 1 since 2021

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 · 56% Legged, aerial and field robots · 44%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots
aerial robot control
0.812024
Attitude Control for Morphing Quadrotor through Model Predictive Control with Constraints · ICRA 2024
Robotics › Motion planning and robot control › robot control › flight control
attitude control
0.812024
Attitude Control for Morphing Quadrotor through Model Predictive Control with Constraints · ICRA 2024
Robotics › Motion planning and robot control › robot control
model predictive control
0.212024
Attitude Control for Morphing Quadrotor through Model Predictive Control with Constraints · ICRA 2024

Methods — techniques the papers use, named apart from their topics

output feedback linearization · 0.8model predictive control · 0.8
YearPublicationVenuePosition
2024 Attitude Control for Morphing Quadrotor through Model Predictive Control with Constraints
abstract
Morphing quadrotors that can be potentially applied to confined spaces such as warehouses, tanks, and pipelines have flourished in recent years. Most work has focused on the mechanical feasibility of the morphing systems and high-level flight controller design, with limited discussions on low-level control. In this paper, a constrained model predictive control (MPC) is proposed and applied to solve the attitude control problem of a morphing quadrotor. Prior to controller design, a custom-built morphing quadrotor is introduced with the kinematic and dynamic models established and corresponding issues and challenges presented. In the controller, to eliminate the steady-state error, an embedded integrator is adopted by exploiting the differential variables; then, the constraints of the morphing quadrotor are incorporated into the MPC formulation to simulate real flight conditions, and an orthonormal function is employed to approximate the control input sequences in the controller to alleviate the computational burden. In the comparative studies, several scenarios are considered to demonstrate the effectiveness of the proposed control strategy in attitude control.
Na Zhao 0008, Yudong Luo, Chaojun Qin, Yantao Shen 0001
ICRA3