Synthesis of Optimal Finite Frequency Controllers for Flexible Robotic Manipulator Control
Bibliographic record
Abstract
In this paper, we explore the relationship between the hybrid passivity and finite gain systems framework and the generalized Kalman-Yakubovich-Popov (GKYP) Lemma. In particular, we investigate how to optimally design finite frequency (FF) controllers which possess strictly positive real (SPR) properties over a low frequency range, and bounded real (BR) properties over a high frequency range. Such FF SPR/BR controllers will be used to control systems which have experienced a passivity violation. We first review the hybrid systems framework and how linear time-invariant hybrid systems relate to FF positive real (PR), FF SPR, and FF BR systems and the GKYP Lemma. A convex optimization problem is posed where constraints are imposed via linear matrix inequalities yielding optimal FF SPR/BR controllers. The FF SPR/BR controllers are optimal in that they approximate the traditional H2 control solution. FF SPR/BR controllers are used to control both single- and two-link flexible manipulators. Experimental results successfully demonstrate closed-loop stability via the hybrid systems framework, and implementation of the proposed controller synthesis scheme.
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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) | 0.001 | 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".