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2 parents 10df1a4 + b4438d1 commit 8e2b1e1Copy full SHA for 8e2b1e1
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README.md
@@ -30,7 +30,7 @@ This student-led course explores modern techniques for controlling — and learn
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| # | Date (MM/DD) | Format / Presenter | Topic & Learning Goals | Prep / Key Resources |
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|----|--------------|--------------------|------------------------|----------------------|
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| 1 | 08/22/2025 | Lecture — Andrew Rosemberg | Course map; why PDE-constrained **optimization**; tooling overview; stability & state-space dynamics; Lyapunov; discretization issues | [📚](https://learningtooptimize.github.io/LearningToControlClass/dev/class01/class01/) |
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-| 2 | 08/29/2025 | Lecture - TBD | Numerical **optimization** for control (grad/SQP/QP); ALM vs. interior-point vs. penalty methods | |
+| 2 | 08/29/2025 | Lecture - Arnaud Deza | Numerical **optimization** for control (grad/SQP/QP); ALM vs. interior-point vs. penalty methods | |
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| 3 | 09/05/2025 | Lecture - Zaowei Dai | Pontryagin’s Maximum Principle; shooting & multiple shooting; LQR, Riccati, QP viewpoint (finite / infinite horizon) | |
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| 4 | 09/12/2025 | **External seminar 1** - Joaquim Dias Garcia| Dynamic Programming & Model-Predictive Control | |
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| 5 | 09/19/2025 | Lecture - Guancheng "Ivan" Qiu | **Nonlinear** trajectory **optimization**; collocation; implicit integration | |
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