Feedback Control of Autonomous Systems

Covers feedback control theory, numerical optimal control, and quadcopter dynamics with hands-on labs on a nano quadcopter platform.

offering recorded3 credits
Recorded instructors · Spring 2027 Xiangru Xu3.4/5

Summary

1 / 2

Recent recorded grades — Spring 2026: 3.43 GPA, 85.7% A/AB (n=7 letter grades).

What you’ll be able to do

  • Express a dynamic system into its state space form and determine its linearized model around a given operating point

  • Use Lyapunov direct and indirect methods to determine the stability of nonlinear systems

  • Explain and assess controllability, observability, and stability of linear systems

  • Solve general optimal control problems using off-the-shelf numerical software

  • Solve linear quadratic problems using linear quadratic regulator

  • Apply differential flatness for quadcopter trajectory generation, and design linear tracking controllers for quadcopters

  • Apply the maximum principle to find the optimal solution of an unconstrained optimal control problem

Source: UW Guide 1 UW Guide 2

Grade history

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average GPA
letter grades
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All recorded terms · compare terms & instructors

Prerequisites

Course map

M E 340,E C E 332, 334, graduate/professional standing, or member of Engineering Guest Students

EMA/ME 458 used by

“Used by” includes alternatives; linked courses may have other requirements. This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree

Professors

Spring 2027
Adjusted rating
RMP difficulty
captured reviews
About this rating

Raw average: 3.07/5 from 14 quality ratings. The adjusted rating blends this with the UW review average (3.66/5), weighted as 20 additional ratings. Smaller samples stay closer to that average. Each captured review is counted once in the prior; this does not correct who chooses to leave a review.

RMP profile ↗ · All captured review dates; profile matched by name.

Recent recorded grades — Spring 2026: 3.43 GPA, 85.7% A/AB (n=7 letter grades).

Historical instructors & teaching patterns

XIANGRU XU is recorded teaching in Spring 2026. Recorded history may be incomplete and does not establish a future schedule.

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 360
LEC 001Classroom Instruction0 / 360

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records

Student experience

the class

Recent recorded grades — Spring 2026: 3.43 GPA, 85.7% A/AB (n=7 letter grades).

difficulty & workload

No workload feedback recorded.

Topics

  • Feedback control theory
  • Numerical optimal control for autonomous systems
  • Quadcopter kinematics, dynamics, control, and trajectory planning
  • Nonlinear system stability via Lyapunov methods

Skills

  • State-space modeling and linearization of dynamic systems
  • Stability analysis of nonlinear systems using Lyapunov methods
  • Optimal control using the maximum principle
  • Quadcopter trajectory generation and controller design

Grades

Latest available · Spring 2026— not enough history to project Spring 2027.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F
More grade details Grade mix, volume & source data

Not enough comparable courses for Spring 2027 in UW–Madison.

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

Selected offering source records
EMA/ME 458 · Spring 2027

Feedback Control of Autonomous Systems

Recorded 2026-10-14
EMA/ME 458 · Spring 2027

Feedback Control of Autonomous Systems

Recorded 2026-10-14
Raw records
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Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Full model traces

Recorded model configuration, reasoning, and tool conversations.

Model & dataset provenance
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