On variable structure robotic control with integral sliding surfaces
Bibliographic record
Abstract
Dynamic behavior of a system in the sliding mode is entirely defined by the sliding surface. Customarily, the surface is selected as a hyperplane in the system state-space resulting in a PD type sliding surface. This is not the only possible structure, and other designs with more complex or time-varying surfaces may provide definite advantages. Slotine and Spong (1985) included an integral term in the sliding surface expression that resulted in a type of PID sliding surface. In this paper we present a new design procedure and stability analysis for robotic variable structure controllers with PID like sliding surface. Two versions of the controllers are presented: regular and adaptive. The former is very simple and can operate with an unknown robot dynamic model; the only information required is a bound on one parameter. The latter provides an online estimation for this bound. Both controllers are robust with respect to bounded external disturbances and some unmodeled dynamic effects. The simulation results have demonstrated stable, with minimum chattering transient responses that may be significantly faster than responses of traditional PD-manifold controllers under the same conditions.>
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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 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".