Geometry Control of the Deposited Layer in a Nonplanar Laser Cladding Process Using a Variable Structure Controller
Bibliographic record
Abstract
This paper presents a closed-loop laser cladding process used in nonplanar deposition of desired metallic materials. In the proposed system, the deposited layer geometry is continuously controlled via a sliding mode controller (SMC). The controller, which uses the scanning speed as the control input, is designed based on a parametric Hammerstein model. The model is a parametric dynamic model with several unknown parameters, which are identified experimentally using the recursive least squares method. The designed SMC is robust to all model parameters’ uncertainties and disturbances. The results showed that the tracking accuracy improves and the chattering effect reduces if an integrator on the scanning speed is added to the controller. It was observed that this addition decreases the response speed. The performance of the proposed controllers was verified through the fabrication of several parts made of SS303-L. This verification indicates that the developed closed-loop laser cladding process can reduce stair-step effects as well as production time in rapid prototyping of functional parts created with the adaptive slicing technique.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".