PD output feedback control design for industrial robotic manipulators
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents an output feedback PD-type controller for the trajectory tracking control of robotic manipulators. A linear observer is used to estimate the unknown velocity signals of the nonlinear manipulator. In the first part of this paper, we propose a PD-like output-feedback control law. The Lyapunov method is used to characterize the asymptotic property of all the signals in the closed-loop error model dynamics. This property sets the bound on the tracking error trajectory of the closed-loop system. In the second part, we remove the nominal model dynamics from the control design to formulate a model-independent PD-type output feedback approach. Using an asymptotic analysis for the singularly perturbed closed-loop model, we guarantee that all the signals under the proposed PD output feedback design are bounded and their bounds can be made arbitrarily small by using observer-controller gains. Implementation results demonstrate the potential application of the proposed method on real systems.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it