Dynamics of Controlled Systems
Focuses on deriving equations for physical systems under control, covering mechanical, fluid, and thermal domains using analytical, experimental, and computer methods.
Summary
Past student reviews · Robert Nowak
The course was rated maximum difficulty.
What you’ll be able to do
Describe how physical state feedback affects dynamic stiffness of a control system
Analyze the sensitivity of the system with eigenvalue migration analysis
Develop improved control systems by implementing active state feedback which mimics the physical system and augments the system performance
Differentiate command tracking from disturbance rejection. The student will characterize the necessary command feedforward structure in order to achieve optimal command tracking.
Manipulate observer inputs and state feedback inputs to achieve zero-lag properties
Draw the block diagram of physical systems identifying the appropriate inputs required for a properly formed observer
Implement observers for state estimation in multi-variable control systems
Source: UW Guide 1· UW Guide 2
Grade history
↗All recorded terms · compare terms & instructors
Prerequisites
Course mapGraduate/professional standing or declared in Capstone Certificate in Power Conversion and Control. Not open to students with credit forM E 746.
- Graduate/professional standing
- declared in Capstone Certificate in Power Conversion and Control
- not eligible with
This is a best-effort interpretation; check the catalog requirements above.
Prerequisite text tree
- All of
- Any of
- Graduate/professional standing
- declared in Capstone Certificate in Power Conversion and Control
- Not eligible with
- Any of
Professors
Spring 2027No instructors recorded for this selection.
Historical instructors & teaching patterns
Recorded history may be incomplete and does not establish a future schedule.
Calendar & sections
Spring 2027Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections.
Meeting source records
Student experience
the class
Past student reviews · Robert Nowak
A 2003 student rated the course highly difficult and low quality, stating they never cared about the class.
Recent recorded grades — Fall 2006: 3.20 GPA, 60.0% A/AB (n=15 letter grades); Fall 2007: 3.25 GPA, 50.0% A/AB (n=10 letter grades); Fall 2024: 3.78 GPA, 100.0% A/AB (n=18 letter grades).
difficulty & workload
Past student reviews · Robert Nowak
The course was rated maximum difficulty.
Past student reviews · Robert Nowak
A past student expressed complete disinterest in the subject matter.
Topics
- Mechanical processing, fluid power, and thermal systems
- Analytical, experimental, and computer techniques
- Dynamic stiffness and physical state feedback
- Command tracking, disturbance rejection, and feedforward structures
- State estimation and observers in multi-variable control
Skills
- System sensitivity analysis using eigenvalue migration
- Implementing active state feedback to augment system performance
- Manipulating observer and state feedback inputs for zero-lag properties
- Drawing block diagrams for observer formation in physical systems
- Implementing observers for state estimation in multi-variable systems
Grades
Latest available · Fall 2024— not enough history to project Spring 2027.
Grade distribution · % of letter grades
Grades over time
Through Fall 2024
More grade details Grade mix, volume & source data
Not enough comparable courses for Spring 2027 in UW–Madison.
Sources & history
Catalog & offerings
Descriptions, prerequisites, and recorded course offerings.
Catalog observation history
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Student reviews
Original comments behind the course and instructor summaries.
Read original reviews
Grade history
Recorded grade distributions by term, section, and instructor.
Explore recorded gradesRecorded 2026-10-29
Model outputs & technical records
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
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