Modeling and Control of Contouring Errors for Five-Axis Machine Tools—Part II: Precision Contour Controller Design
Bibliographic record
Abstract
Abstract The accurate tracking of tool-paths on five-axis CNC machine tools is essential in achieving high speed machining of dies, molds, and aerospace parts with sculptured surfaces. Because traditional CNCs control the tracking errors of individual drives of the machine, this may not lead to desired contouring accuracy along tool-paths, which require coordinated action of all the five drives. This paper proposes a new control approach where the tool tip and tool orientation errors, i.e., the contouring errors, are minimized along the five-axis tool-paths. The contouring error and kinematic model of the machine, which are presented in Part I of the paper, are used in defining the plant. A multi-input–multi-output sliding mode controller, which tries to minimize path tracking and path following velocity errors, is introduced. The stability of the system is ensured, and the proposed model is experimentally demonstrated on a five-axis machine tool. The path errors originating from the dynamics of five simultaneously active drives are significantly reduced.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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".