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Design of Dynamic Nonlinear Control Techniques for Flexible-Link Manipulators

2008· article· en· W2020428123 on OpenAlexaff
V. Gavriloiu, Valery D. Yurkevich, K. Khorasani

Bibliographic record

VenueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomena · 2008
Typearticle
Languageen
FieldEngineering
TopicDynamics and Control of Mechanical Systems
Canadian institutionsConcordia University
Fundersnot available
KeywordsControl theory (sociology)Nonlinear systemLink (geometry)Stability (learning theory)Computer scienceControl engineeringPosition (finance)Tracking (education)Control (management)EngineeringPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

In this paper, we develop robust dynamical controllers for addressing the problems of tracking and regulation of flexible-link manipulators. The design of dynamical controllers is based on construction of a two-time scale dynamical motion of the closed-loop system. The main control objective is to achieve stability of the closed-loop system while ensuring boundedness of all the control signals as well as sufficiently small tip-position tracking requirement. In order to achieve a minimum phase behaviour for utilizing output feedback control strategy, a new redefined output is proposed. Instead of using the joint angles as outputs in the rigid-link case, a new output is chosen for the flexible-link case which will provide and guarantee stability of the closed-loop flexible system. Simulations results are provided for flexible-link manipulators using the proposed control strategies. A comparative analysis is also included to demonstrate and illustrate the advantages and disadvantages of the considered control methodologies.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.036
GPT teacher head0.278
Teacher spread0.242 · 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 designSimulation or modeling
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".

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Citations0
Published2008
Admission routes1
Has abstractyes

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Same venueDiffusion and defect data, solid state data. Part B, Solid state phenomena/Solid state phenomenaSame topicDynamics and Control of Mechanical SystemsFrench-language works237,207