Design, modeling, and control of precision motion system for the wafer scanner systems
Bibliographic record
Abstract
Over the last few decades, academia and industry have focused on designing and developing high-precision motion systems for various applications. These systems play a crucial role in modern and future micro- and nanotechnologies, including scanning probe microscopy and lithography machines in the semiconductor industry. The next generation of high-precision motion systems, particularly in semiconductor manufacturing, demands increased throughput (measured in wafers per hour) and improved accuracy (in micrometers). To meet these requirements, enhancing force stability and accuracy is essential for achieving faster acceleration in semiconductor lithography machines. Recent research and assessments indicate that the reluctance actuator holds promise as a driving mechanism for the next-generation precision motion system in semiconductor lithography machines. The primary challenge with reluctance actuators lies in managing the non-linear relationship between magnetic force and current, as well as between magnetic force and the air gap. These nonlinearities pose significant issues in design, control, and operation. Furthermore, there is a contemporary trend toward adopting piezoelectric actuators to drive exure-guided piezo stages in the short-stroke (SS) domain. This rising preference highlights the industry's focus on achieving speed and precision in the evolving landscape of wafer scanner systems. Piezoelectric-based micopositioning stages are favoured in many applications due to their advantageous features. However, piezoelectric actuators exhibit challenging nonlinear behavior, complicating the modeling, control, and synchronization processes. The dissertation introduces two significant contributions to enhancing the tracking performance of reluctance-actuated motion stages and piezoelectric micropositioning. First, it presents a design for a reluctance-actuated motion stage characterized by various operational conditions. Next, three distinct control approaches are proposed to linearize the dynamic behavior of the reluctance actuator and improve tracking performance toward a desired reference signal. Notably, these novel control approaches rely solely on position measurements, eliminating the need for ux and force measurements compared to existing literature-based control methods. The second contribution involves integrating a uni-axial fine positioning piezo-actuated stage with an existing precision motion system. This multi-stage design aims to enhance overall system precision. Additionally, a feedforward compensator-based rate-dependent Prandtl-Ishlinskii model has been developed to address hysteresis nonlinearities in piezoelectric actuators. Finally, this dissertation contributes to the design of a tracking control system for a specific class of non-minimum phase nonlinear systems with unknown uncertainties and external disturbances. The proposed control strategy combines two key elements: an output feedback control to Utilize stabilizing full-state feedback control and an extended high-gain observer to Enhance robustness and disturbance rejection. As a case study, we demonstrate that the state feedback controller simpli�es to a PID-like controller for a relative degree-two system.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".