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Record W2151521682 · doi:10.1109/9.847743

Nonlinear control strategy development for asymmetric actuators

2000· article· en· W2151521682 on OpenAlexaff
Amir Khajepour

Bibliographic record

VenueIEEE Transactions on Automatic Control · 2000
Typearticle
Languageen
FieldEngineering
TopicTeleoperation and Haptic Systems
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsActuatorControl theory (sociology)Nonlinear systemController (irrigation)PlantConstant (computer programming)Quadratic equationControl systemComputer scienceControl (management)EngineeringMathematicsPhysics

Abstract

fetched live from OpenAlex

We develop a nonlinear control method for asymmetric actuators. Asymmetric actuators do not generate symmetric power during an application. Thrusters and shape memory alloy wires are examples of this class of actuators that produce only unidirectional forces. Hydraulic and pneumatic cylinders are generally asymmetric because, under constant pressure, the generated force in the forward direction is different than that in the reverse direction. Existing control methods assume a symmetric actuation, and therefore, application of asymmetric actuators calls for new control schemes. Current control techniques implement a bias in utilizing asymmetric actuators. However, the amount of the bias depends on the control effort and is not constant. Also, the use of a bias changes the system equilibrium point and introduces a steady-state error. We propose a control scheme capable of producing any biased input. The controller is a second-order system coupled to the system through quadratic terms. The application of quadratic terms for the control input enables us to generate any biased control input, which can be utilized by asymmetric actuators.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.224
Teacher spread0.213 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreMethods

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2000
Admission routes1
Has abstractyes

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