AA 203: Optimal and Learning-Based Control

Course Description

Optimal control solution techniques for systems with known and unknown dynamics. Dynamic programming, Hamilton-Jacobi reachability, and direct and indirect methods for trajectory optimization. Introduction to model predictive control. Adaptive control, model-based and model-free reinforcement learning, and connections between modern reinforcement learning and fundamental optimal control ideas.

Instructors

Marco Pavone	Daniele Gammelli

Course Assistants

Daniel Morton	Matt Foutter

Meeting Times

Lectures are held on Mondays and Wednesdays from 1:30pm to 2:50pm in Huang Engineering Center 18.

Lecture recordings will be available on Canvas.

Recitations are held on Fridays from 9:00am to 10:30am for the first four weeks of the quarter. Recitations are hybrid sessions, held both in Durand 251 and on Zoom (link on Canvas). Each recitation will be recorded and available offline on Canvas.

Office Hours

Office hours will begin in the second week of the quarter

Marco Pavone's office hours are on Tuesdays 1:00pm to 2:00pm in Durand 261 and by appointment.

Daniele Gammelli's office hours are on Thursdays 1:30pm to 2:30pm in Durand 217 (project discussion).

Daniel Morton's office hours are on Fridays 3:00pm to 5:00pm in Durand 217.

Matt Foutter's hybrid office hours are on Mondays 3:00pm to 4:00pm and Thursdays 5:00pm to 6:00pm in Durand 251.

Syllabus

The class syllabus can be found here.

Schedule

Subject to change.