https://zhuanlan.zhihu.com/p/395525975
总结一些OCP有用的课程，课件，网页
Outline:
Classic optimal control
Optimal and learning-based control (RL, DeepRL, etc.)
Topic-specific material (DP, shooting method, etc.)
Classic optimal control:
- self-study material for numerical optimal control by Prof. Moritz Diehl (includes videos, lecture slides and exercise)
2. High-level overview slides by Prof. Moritz Diehl
3. Very detailed slides by Prof. Mario Zanon for OCP
4. Short course “Numerical methods for optimal control by Dr. Sebastien Gros.(Course given as part of NTNU PhD course TKTK8115 Numerical Optimal Control. Department of Engineering Cybernetics, NTNU, Trondheim, 11-12 October 2018.) Playlist:
5. Principles of Optimal Control by Prof. Jonathan P. How (MIT open courseware)
8. Book (based on lecture notes):
Calculus of variations and optimal control theory- a concise introduction by Prof. Daniel Liberzon (UIUC)
Manuscript of Numerical Optimal Control by S. Gros and M. Diehl (Draft)
Optimal and learning-based control
1. Optimal Control and Reinforcement Learning by CMU (in the 2019 version of this course, there is also a list of relevant courses you can check out)
2. AA 203: Optimal and Learning-Based Control by Stanford (course material and code are available in Github)
3. Deep Reinforcement Learning and Control Spring 2017, CMU 10703
4. Reinforcement learning and optimal control (book, video lecture and course material, 2021) by Prof. Dimitri P. Bertsekas (MIT)
Topic-specific
- Direct Single and direct multiple shooting by Prof. Moritz Diehl
2. Dynamic Programming by Prof. Russell Tedrake