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Record W4412567214 · doi:10.1109/tcyb.2025.3586002

Trajectory Tracking Control Employing Nonlinear Compensator and State Observer for Photothermal-Driven Liquid Crystal Elastomer Actuator

2025· article· en· W4412567214 on OpenAlexaff
Jundong Wu, Yawu Wang, Chun‐Yi Su, Daiki Sato, Jinhua She

Bibliographic record

VenueIEEE Transactions on Cybernetics · 2025
Typearticle
Languageen
FieldMaterials Science
TopicPolymer composites and self-healing
Canadian institutionsConcordia University
FundersHigher Education Discipline Innovation ProjectNational Natural Science Foundation of China
KeywordsControl theory (sociology)ActuatorNonlinear systemTrajectoryLiquid crystalTracking (education)ElastomerObserver (physics)State observerMaterials sciencePhotothermal therapyControl engineeringComputer scienceControl (management)EngineeringPhysicsArtificial intelligenceOptoelectronicsNanotechnologyComposite materialPsychology

Abstract

fetched live from OpenAlex

The trajectory tracking control for the photothermal-driven liquid crystal elastomer (LCE) actuator presents a significant challenge due to its hysteresis nonlinear characteristic and its inherent complex deformation mechanism. To address this challenge, this article proposes a trajectory tracking control method for the LCE actuator utilizing a nonlinear compensator and a state observer. The proposed control is a multistep control, which includes temperature control from the input voltage to the LCE temperature and displacement control from the LCE temperature to the LCE displacement. In the proposed method, we design a non-Lipschitz continuous state-feedback controller to realize finite-time convergence control of the temperature. As for the displacement control, we design a state observer to estimate the change rate of the LCE displacement. Meanwhile, a nonlinear inverse compensator is designed to compensate for the hysteresis nonlinearity of the LCE dynamics, which simplifies the complex nonlinear control problem into a linear control problem. Hence, the pole placement method can be utilized to design a trajectory tracking controller to achieve the control objective. The proposed control method is validated by tracking control experiments with different target trajectories.

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 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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.015
GPT teacher head0.255
Teacher spread0.239 · 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 teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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