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Experimental study of PID for attitude control of a quadcopter using an ESP32

2024· article· en· W4400604813 on OpenAlex
Ahmed Khalil Moussaoui, Mohamed Habbab, A. Hazzab, Hireche Slimane, Ambrish Chandra, Hicham Gouabi, Alhachemi Moulay Abdellah

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueInternational Journal of Power Electronics and Drive Systems/International Journal of Electrical and Computer Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsQuadcopterPID controllerMicrocontrollerComputer scienceMATLABController (irrigation)Rotor (electric)Control engineeringControl theory (sociology)Control (management)Artificial intelligenceEngineeringEmbedded systemTemperature control

Abstract

fetched live from OpenAlex

Aerial robotics encompasses intricate kinematics and dynamics that govern the flight of quad-rotor systems. Among the various methods employed for flight control using microcontrollers like the ESP32 developed by ESPRESSIF; the proportional integral derivative (PID) controller stands out as a widely adopted approach. The ESP32 microcontroller offers a superior interface, delivering enhanced performance and response time, particularly in dynamic environments. This article delves into the implementation and viability of the ESP32 platform for communication with MATLAB/Simulink, as well as real-time data acquisition to control the attitude of quadcopter withe chassis F450. The PID controller was designed to specifically work with the ESP32 platform and rigorously tested on an actual quadcopter during flight operations. lastly, a comprehensive analysis of the data gained and empirical results from the physical model demonstrates that the proposed framework is effective.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.477
Threshold uncertainty score0.788

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.267
Teacher spread0.257 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it