Optimal Control (TSRT08)
Lectures
Preliminary lecture plan. Select a lecture title to open its slides.
| No. | Title | Sections (book) |
|---|---|---|
| 1 | Introduction and shortest path (slides) | — |
| 2 | Dynamic programming (slides) | 5.5, 8.1–8.3, 8.10.1 |
| 3 | Value iteration (VI) and policy iteration (PI) (slides) | 8.4–8.5 |
| 4 | Model predictive control (MPC) (slides) | 5.6, 8.7–8.8, 8.10.3 |
| 5 | Reinforcement learning (RL) (slides) | 11.1 |
| 6 | VI and PI for RL (slides) | 11.2–11.3 |
| 7 | Approximation in policy space and ILC (slides) | 11.3.3, 11.5.1 |
| 8 | Calculus of variations (slides) | 7.1 |
| 9 | The Pontryagin maximum principle (PMP) (slides) | 7.2–7.3 |
| 10 | Generalizations of the PMP (slides) | 7.4 |
| 11 | Numerical solutions (slides) | 7.5 |
| 12 | Summary | — |