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Record W2756394884 · doi:10.23919/chicc.2017.8028107

Adaptive robust control of quadrotor helicopter towards payload transportation applications

2017· article· en· W2756394884 on OpenAlex

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

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdaptive Control of Nonlinear Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsControl theory (sociology)Payload (computing)Robustness (evolution)Robust controlParametric statisticsAdaptive controlLinear-quadratic regulatorSliding mode controlControl engineeringComputer scienceIntegral sliding modeEngineeringControl systemControl (management)Nonlinear systemMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

Sliding mode control is known as a robust control approach to maintain system performance and keep it insensitive to disturbances. This paper proposes an integral sliding mode based adaptive robust control for a quadrotor helicopter with parametric uncertainties and disturbances. With the help of the synthesized on-line adaptive scheme, the uncertain parameters can be accurately estimated without the knowledge of the uncertainty bounds. In this case, there is no need to increase the discontinuous control gain, which may stimulate control chattering effect, to maintain the robustness of the controller. The effectiveness of the proposed control strategy is validated through a simulation of the payload transportation application. Compared to the commonly used linear quadratic regulator (LQR) approach, the proposed adaptive robust control strategy can maintain the tracking performance during the whole flight phase.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.989
Threshold uncertainty score0.526

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.023
GPT teacher head0.237
Teacher spread0.214 · 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

Quick stats

Citations5
Published2017
Admission routes1
Has abstractyes

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