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Enregistrement W2319859550 · doi:10.2514/6.2009-6162

Active Vibration Control Using Adaptive Positive Position Feedback

2009· article· en· W2319859550 sur OpenAlex

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Notice bibliographique

RevueAIAA Guidance, Navigation, and Control Conference · 2009
Typearticle
Langueen
DomaineEngineering
ThématiqueDynamics and Control of Mechanical Systems
Établissements canadiensYork University
Organismes subventionnairesnon disponible
Mots-clésControl theory (sociology)Feedback controlVibrationComputer sciencePosition (finance)Adaptive controlPosition paperVibration controlControl (management)Active vibration controlControl engineeringArtificial intelligenceEngineeringAcousticsPhysics

Résumé

récupéré en direct d'OpenAlex

An active vibration control strategy is developed for a flexible manipulator with a collocated piezoelectric sensor/actuator pair. Dynamic modeling of the flexible manipulator is first shown and then a control law is developed. The positive position feedback (PPF) control law is augmented with an adaptive parameter estimator based on the recursive least squares method which updates the natural frequencies of the structure online. Accurate targeting of the vibrational modes is critical for damping of the vibrations using PPF and simulations are conducted to demonstrate its eectiveness. I. Introduction Active vibration control of a single-link flexible manipulator is a relatively complex problem and has had numerous papers published on it. From a robotics standpoint, a flexible manipulator is desirable due to the fact that existing manipulators are large and heavy due to the need for the manipulator to be sti in order for the precise location of the tip to be known. The flexible manipulator on the other hand, would have the advantages of lighter weight, lower power consumption, and better maneuverability due to smaller size. The drawback to the flexible manipulator is that it faces large vibrations, leading to positional inaccuracy of the tip during and after movement. The same problems occur in large flexible structures for use in space, such as solar panel arrays. Since the size and mass of an object that can be put into space is severely limited, most structures are flexible due to their smaller mass. This can lead to a variety of problems in areas such as high precision attitude control and stability of motions. A significant number of papers have been written on PPF 1‐3 demonstrating its eectiveness in active vibration control. However, the eectiveness of PPF deteriorates when the natural frequencies of the structure are poorly known or changing due to, for example, the presence of a tip mass. There has been significantly less work done on adaptive PPF than there has been on just PPF. Kwak et al. 4 present a method for adaptively tuning the controller frequency of the PPF controller for a single mode of a cantilever beam, and also illustrate their implementation of a real-time controller. Rew et al. 5 propose an adaptive PPF controller for a plate in a fixed-free configuration in which estimated natural frequencies are adjusted at every time step. Baz and Hong 6 present an adaptive modal PPF controller where the AMPPF controller parameters are adjusted in an adaptive manner in order to follow the performance of an optimal reference model (for a cantilever beam). In the first section, development of a finite element model for an Euler-Bernoulli beam to take into account the eect of the sensor and actuator dynamics is presented. This model is created for use in the simulations and is based upon the work of Bandyopadhyay et al. 7 with some modifications. In the second section, a positive position feedback controller is designed for damping of the beam’s vibrations, and then an adaptive online parameter estimator based upon the recursive least squares method with forgetting factor is designed for the first two modes of vibration. Next, the results of using the adaptive estimator to update the estimates of the beam’s first two natural frequencies are presented and their eectiveness demonstrated. Finally, conclusions and possible further areas of investigation are discussed.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,922
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,001
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,008
Tête enseignante GPT0,209
Écart entre enseignants0,201 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle