Evidence map›Paper›PMID 42122447›Full record

ArticleSensors (Basel, Switzerland)2026

Attitude Controller for UAV First-Order Acceleration Coefficients Tracking.

Ding Xu, Hailong Pei

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Ding XuKey Laboratory of Autonomous Systems and Network Control, Ministry of Education, South China University of Technology, Guangzhou 510641, China.ORCID 0009-0004-4878-2168
Hailong PeiKey Laboratory of Autonomous Systems and Network Control, Ministry of Education, South China University of Technology, Guangzhou 510641, China.ORCID 0000-0001-9955-3200

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper proposes a novel attitude control methodology for unmanned aerial vehicles (UAVs). The core of the approach is a decomposition of the vehicle's orientation into a distinct horizontal tilt component and a yaw rotation. This reformulation provides a principled theoretical framework by redefining attitude error within an acceleration-coefficient space, which linearizes and decouples the horizontal acceleration dynamics-a significant simplification over conventional Euler-angle or quaternion-based models. From an engineering perspective, this framework enables the direct generation of angular velocity commands that guarantee first-order tracking of desired acceleration coefficients. This leads to a substantial reduction in the computational complexity of the outer-loop controller, enhances trajectory tracking accuracy, and ensures predictable performance under given attitude constraints and angular velocity limits. Simulation results demonstrate the method's superior performance compared to standard techniques, validating its dual value as both a theoretically-grounded control design tool and an effective solution for high-precision UAV navigation in real-world applications.

Indexed as

attitude controllerquaternion decompositionUAV

Identifiers

PMID42122447
PMCPMC13165700

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.