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