Fall 2026

Dynamics of Controlled Systems

ME 746 covers the dynamics of controlled systems, focusing on deriving equations for mechanical, fluid, and thermal systems using analytical and computational methods.

no offering record for this termCredits unavailable
Recorded instructors · Fall 2026 No instructors listed

Summary

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Recent recorded grades — Fall 2019: 3.65 GPA, 84.6% A/AB (n=13 letter grades); Fall 2020: 3.81 GPA, 100.0% A/AB (n=16 letter grades); Fall 2022: 3.77 GPA, 100.0% A/AB (n=15 letter grades).

Grade history

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average GPA
letter grades
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AB
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Prerequisites

Course map

Graduate/professional standing

  • Graduate/professional standing
ME 746

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree
  • Graduate/professional standing

Professors

Fall 2026

No instructors recorded for this selection.

Historical instructors & teaching patterns

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Calendar & sections

Fall 2026

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Meeting source records

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Student experience

the class

Recent recorded grades — Fall 2019: 3.65 GPA, 84.6% A/AB (n=13 letter grades); Fall 2020: 3.81 GPA, 100.0% A/AB (n=16 letter grades); Fall 2022: 3.77 GPA, 100.0% A/AB (n=15 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Mechanical processing, fluid power, and thermal systems.
  • Analytical, experimental, and computer techniques for control system analysis.

Skills

  • Deriving governing equations for physical systems under control.
  • Applying analytical, experimental, and computer-based techniques to control problems.

Grades

Latest available · Fall 2022— not enough history to project Fall 2026.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Fall 2022

More grade details Grade mix, volume & source data

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Sources & history

UW–Madison

Catalog & offerings

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Student reviews

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Grade history

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Dataset & model

Recorded 2026-09-07

View the dataset on Hugging Face
Model outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
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Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
  "model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
  "task_version": "14",
  "output_id": "213c4d2b1c3a1761582b96ca6a96990dbdaafb5e047c4706c79eaeb26321d32c",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}