Sliding Mode Controller and Filter Applied to a Model oft an Electrohydraulic Actuator System
Bibliographic record
Abstract
A new robust state and parameter estimation strategy called the Variable Structure Filter (VSF) has recently been proposed and used for state and parameter estimation. A very common problem of linear stochastic systems is to design a combined robust control and estimation strategy, given system and noise uncertainties. Variable Structure Control (VSC) and its special form of Sliding Mode Control (SMC) show superb robustness. This paper proposes a new strategy involving the Sliding Mode Control and the Variable Structure Filter. Both the estimator and controller are based on the concepts of Variable Structure Systems (VSS). In the presence of bounded parametric uncertainties and noise, a robust stability is guaranteed. Further more, the combined strategy can be used to achieve high regulation rates or short settling times. The object of this paper is to introduce this combined VSF and SMC strategy and to demonstrate its application to a third order model of a high precision hydrostatic system, referred to as the Electrohydraulic Actuator System (EHA).
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".