Modelling and robust position and orientation control of a non-affine nonlinear dielectrophoresis-based micromanipulation system
Bibliographic record
Abstract
Conventional dielectrophoresis and electrorotation have attracted widespread attention in the field of individual micro-object manipulation in recent years. The improvement of current dielectrophoresis-based micromanipulation systems’ flexibility, accuracy and level of automation are essential requirements of dielectrophoresis-based micromanipulation techniques. For the purpose of high-precision automatic positioning and orientation control of a micro-object, we have developed approximate analytical expressions to describe the conventional dielectrophoretic force and electrorotation torque generated by quadrupole polynomial electrodes on a spherical micro-particle. Numerical simulations based on the finite element method are used to demonstrate the effectiveness of the proposed modelling method. In addition, the non-affine nonlinear dynamic models of the dielectrophoresis-based micromanipulation subsystems are established. Furthermore, an uncertainty and disturbance estimator based dynamic sliding mode controller is proposed and applied to achieve a robust sequential position and orientation control system. The stability of the closed-loop system is established. The performance of the proposed control is demonstrated through simulation studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".