Design and experimental study of a dynamical adaptive backstepping–sliding mode control scheme for position tracking and regulating of a low‐cost pneumatic cylinder
Bibliographic record
Abstract
Summary A dynamical adaptive backstepping–sliding mode control scheme is designed and implemented for the first time, to track and regulate the position of a low‐cost pneumatically driven single‐rod, double‐acting cylinder. The mass flow rate of compressed air into and out of the cylinder is regulated by a 5/3‐way proportional directional control valve. The derivation of the controller, utilizing a design procedure that guarantees stability of the control system, is presented first. Next, experimental evaluation of the controller is conducted with respect to performance and robustness to parametric uncertainties. Experiments employ a sinusoidal reference trajectory with tracking frequencies of 0.05, 0.1, and 0.2 Hz; a multiple‐step polynomial reference trajectory having step sizes of 0.0125, 0.025, 0.05, and 0.1 m; and three external loads of 4.4, 9, and 16 kg operating in two modes (motion assisting and resisting). From over 70 experiments involving various operating conditions, average root mean square of tracking error of 1.73 mm and steady‐state error of 0.71 mm are achieved for the position tracking and regulating, respectively. As compared with the classical sliding mode control scheme alone, the new controller outperforms by more than twofold. The adaptive LuGre‐based friction observer applied in this control scheme significantly assists in compensating the adverse effect of friction with the average of 55% less tracking error. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".