PID-Like Controllers for a Class of Uncertain Underactuated Nonlinear Systems with Application to Wafer-handling Robot
Bibliographic record
Abstract
We develop an output feedback tracking controller for a class of underactuated nonlinear systems, specifically applied to a wafer handling robot in semiconductor manufacturing. The proposed controller exhibits performance similar to a PID controller, incorporating proportional, derivative, and integral components to shape both transient and steady-state behavior. Unlike traditional approaches, the controller does not require any stability assumptions on the system’s zero dynamics, making it well-suited for non-minimum phase systems. The design process begins with a full-state feedback controller to achieve the tracking objective. This is then extended into an output feedback control framework by integrating an Extended High-Gain Observer (EHGO). The EHGO employs a cascade observer structure, estimating the unmeasured output from available system measurements to ensure accurate feedback. As a case study, we demonstrate that for a relative degree-two system, the state feedback controller simplifies into a PID-like structure, enhancing ease of implementation. The proposed control strategy is validated by applying it to a wafer-handling robot described as a flexible joint system. The results showcase the robot’s ability to achieve precise trajectory tracking while compensating for uncertainties and external disturbances. They also highlight the controller’s robustness and adaptability, making it a viable solution for high-precision wafer transfer operations in semiconductor fabrication.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".