Course plan
15 weeks — slides & labs
Each teaching week is half lecture, half lab. Open the deck to learn the method,
then the lab sheet to build it in quadsim. Links light up as each week is released.
The software
quadsim — the course simulator
What it is
A fully readable, pure-NumPy 12-state nonlinear quadrotor model with an RK4
integrator and a closed-loop runner. No black boxes — you can re-derive every line by hand.
You extend one StudentController class all term; by the final project it flies a full mission.
60-second start
# from the simulator/ directory python -m venv .venv && source .venv/bin/activate pip install -r requirements.txt export PYTHONPATH=. python examples/02_hover_pid.py # reference autopilot python examples/02_hover_pid.py --controller student # your turn python -m pytest -q # smoke tests
One hard dependency (numpy). Runs on any laptop in seconds — no GPU, no MATLAB.
Graded work
Assignments
Every graded item has a full brief with its assessment rubric. Weekly lab sheets teach the how; these pages define the what and how it's graded.
Six lab reports — 30%
Individual. One per graded week (Weeks 4–9), 5% each, due at the start of the next class.
Lab 1 · Linearization (Wk 4) Lab 2 · Attitude (Wk 5) Lab 3 · Position (Wk 6) Lab 4 · LQR (Wk 7) Lab 5 · Estimation (Wk 8) Lab 6 · Trajectory (Wk 9)
Team case study — 20%
Teams of ~4. Integrate the six labs into one autopilot, fly a full mission from estimated state, diagnose the limitation. Presented in Week 10.
Final project — 40%
Same teams. Fly the mission, then fly it better with MPC or RL — proposal Week 10, live demo Week 15.
Remaining 10% = class participation (attendance + in-class discussion), assessed weekly.
Assessment & submission
How to hand in your work
Submit through the MUST LMS
The six lab reports, the team case study, and the final project (code, report, slides) are submitted through the official MUST learning-management system — not on this site. This page is your materials hub; the LMS is your gradebook and dropbox.
Open the MUST LMS LMS URL — TO FILL
Each lab sheet repeats the exact filename, format, and deadline for that week's deliverable.
Grade breakdown
| Component | Weight |
|---|---|
| Attendance & participation | 10% |
| 6 lab reports (Wks 4–9) | 30% |
| Team case study (Wk 10) | 20% |
| Final project — code, report, presentation & demo | 40% |
Textbook & references
Reading
No single required textbook; materials are provided in class. Primary references:
- Introduction to Multicopter Design and Control — Quan Quan, Springer 2017. (quadrotor modeling & control — primary)
- Small Unmanned Aircraft: Theory and Practice — Beard & McLain, Princeton 2012. (frames, 6-DOF EOM, estimation)
- Aircraft Control and Simulation, 3rd ed. — Stevens, Lewis & Johnson, Wiley 2015.
- Model Predictive Control, 2nd ed. — Rawlings, Mayne & Diehl, 2017. (MPC weeks)
- Reinforcement Learning: An Introduction, 2nd ed. — Sutton & Barto, MIT 2018. (RL weeks)