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Special Topics on Optimal Control and Learning — Fall 2025 (ISYE 8803 VAN)

Georgia Institute of Technology – Fridays 2 pm ET

Designers: Andrew Rosemberg & Michael Klamkin
Instructor: Prof. Pascal Van Hentenryck


Overview

This student-led course explores modern techniques for controlling — and learning to control — dynamical systems. Topics range from classical optimal control and numerical optimization to reinforcement learning, PDE-constrained optimization (finite-element methods, Neural DiffEq, PINNs, neural operators), and GPU-accelerated workflows.

Prerequisites

  • Solid linear-algebra background
  • Programming experience in Julia, Python, or MATLAB
  • Basic ODE familiarity

Grading

Component Weight
Participation & paper critiques 25 %
In-class presentations 50 %
Projects 25 %

Weekly Schedule (Fall 2025 – Fridays 2 p.m. ET)

# Date (MM/DD) Format / Presenter Topic & Learning Goals Prep / Key Resources
1 08/22/2025 Lecture — Andrew Rosemberg Course map; why PDE-constrained optimization; tooling overview; stability & state-space dynamics; Lyapunov; discretization issues
2 08/29/2025 Lecture Numerical optimization for control (grad/SQP/QP); ALM vs. interior-point vs. penalty methods
3 09/05/2025 Lecture Pontryagin’s Maximum Principle; shooting & multiple shooting; LQR, Riccati, QP viewpoint (finite / infinite horizon)
4 09/12/2025 External seminar 1 - Joaquim Dias Garcia Dynamic Programming & Model-Predictive Control
5 09/19/2025 Lecture - Guancheng "Ivan" Qiu Nonlinear trajectory optimization; collocation; implicit integration
6 09/26/2025 External seminar 2 - Henrique Ferrolho Trajectory optimization on robots in Julia Robotics
7 10/03/2025 Lecture Essentials of PDEs for control engineers; weak forms; FEM/FDM review
8 10/10/2025 External seminar 3 TBD (speaker to be confirmed) Topology optimization
9 10/17/2025 External seminar 4 — François Pacaud GPU-accelerated optimal control
10 10/24/2025 Lecture - Michael Klamkin Physics-Informed Neural Networks (PINNs): formulation & pitfalls
11 10/31/2025 External seminar 5 - Chris Rackauckas Neural Differential Equations: PINNs + classical solvers
12 11/07/2025 Lecture - Pedro Paulo Neural operators (FNO, Galerkin Transformer); large-scale surrogates
13 11/14/2025 External seminar 6 - Charlelie Laurent Scalable PINNs / neural operators; CFD & weather applications
14 11/21/2025 Lecture Robust control & min-max DDP (incl. PDE cases); chance constraints; Data-driven control & RL-in-the-loop

Reference Material


Repository maintained by the 2025 cohort.
Feel free to open issues or pull requests for corrections and improvements.