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Record W2901314429 · doi:10.25071/10315/35242

Direct Switching Position Control Algorithms For Pneumatic Actuators Using On/Off Solenoid Valves

2018· article· en· W2901314429 on OpenAlex
Yile Zhang, Gary M. Bone

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

VenueProgress in Canadian Mechanical Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicHydraulic and Pneumatic Systems
Canadian institutionsMcMaster University
Fundersnot available
KeywordsActuatorPneumatic actuatorSolenoidPosition (finance)Solenoid valveComputer scienceControl theory (sociology)Control valvesControl (management)Control engineeringAlgorithmEngineeringMechanical engineeringArtificial intelligence

Abstract

fetched live from OpenAlex

Pneumatic actuators are advantageous in terms of cost, power to weight ratio and inherent safety. However, their dynamics makes precise closed-loop position control very difficult in practice. Two sliding-mode control algorithms for controlling the position of a pneumatic cylinder by directly switching four on/off solenoid valves are proposed in this paper. The solenoid valves are much less expensive than the commonly used servo or proportional valves. The proposed algorithms are compared to two state of the art position control algorithms. Based on experiments on a high friction cylinder with various payloads, the proposed controllers provide superior performance in terms of valve switches per second, steady state error, settling time and overshoot. The achieved number of valve switches per second is also about one tenth of the number required by the pulse-width modulation method that is commonly used with on/off valves. This should result in prolonged valve lifetimes and reduced maintenance costs.

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: Empirical · Consensus signal: none
Teacher disagreement score0.735
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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