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Record W1998811959 · doi:10.1155/2011/572424

Controller Design for Rotary Inverted Pendulum System Using Evolutionary Algorithms

2011· article· en· W1998811959 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

VenueMathematical Problems in Engineering · 2011
Typearticle
Languageen
FieldEngineering
TopicAdvanced Control Systems Design
Canadian institutionsUniversity of Alberta
FundersUniversity of Tabriz
KeywordsInverted pendulumControl theory (sociology)Particle swarm optimizationRobustness (evolution)Nonlinear systemAnt colony optimization algorithmsGenetic algorithmEngineeringPosition (finance)Computer scienceControl engineeringAlgorithmMathematical optimizationMathematicsControl (management)Artificial intelligencePhysics

Abstract

fetched live from OpenAlex

This paper presents evolutionary approaches for designing rotational inverted pendulum (RIP) controller including genetic algorithms (GA), particle swarm optimization (PSO), and ant colony optimization (ACO) methods. The goal is to balance the pendulum in the inverted position. Simulation and experimental results demonstrate the robustness and effectiveness of the proposed controllers with regard to parameter variations, noise effects, and load disturbances. The proposed methods can be considered as promising ways for control of various similar nonlinear systems.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.731
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.052
GPT teacher head0.215
Teacher spread0.163 · 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