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151-0563-01L
4
Credits
BSC
,
DR
,
MSC
D-MAVT
,
D-INFK
,
D-MATH
,
D-PHYS
,
D-ERDW
,
D-ITET
Dynamic Programming and Optimal Control
Lecturers & Examiners:
Prof. Dr. Raffaello D'Andrea
Last Updated: 2026-06-03 00:07:37
Abstract
Introduction to Dynamic Programming and Optimal Control.
Objective
Covers the fundamental concepts of Dynamic Programming & Optimal Control.
Content
Dynamic Programming Algorithm; Deterministic Systems and Shortest Path Problems; Infinite Horizon Problems, Bellman Equation; Deterministic Continuous-Time Optimal Control.
Resources
Literature
Dynamic Programming and Optimal Control by Dimitri P. Bertsekas, Vol. I, 3rd edition, 2005, 558 pages, hardcover.
General Information
- Language
- English
- Levels
- BSC , DR , MSC
- Frequency
- Yearly recurring
Examination
- Type
- session examination
- Mode
- written 150 minutes
- Aids
- A single A4 sheet of paper (double sided; hand-written or computer typed)
There is a written final exam during the examination session, which covers all material taught during the course, i.e. the material presented during the lectures and corresponding problem sets, programming exercises, and recitations.
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture |
Dynamic Programming and Optimal Control
The lecture will start in the 1st week of the Semester.
|
No time listed | 2 h weekly |
| exercise |
Dynamic Programming and Optimal Control
The exercise will start in the 1st week of the Semester.
|
No time listed | 1 h weekly |
Offered In
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Robotics (Only one of the two course units 263-5902-00L Computer Vision resp. 227-0447-00L Image Analysis and Computer Vision may be recognised for credits for the overall (CSE Bachelor and Master) study programmes. Only one of the two course units 263-5210-00L Probabilistic Artificial Intelligence resp. 252-0535-00L Advanced Machine Learning may be recognised for credits in the field of specialisation `Robotics' for the overall (CSE Bachelor and Master) study programmes. However, the other course unit may be recognised for a different category.)
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Robotics, Systems and Control (Focus Coordinator: Prof. Robert Katzschmann)
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Core Courses (The Core Courses in the Master’s program Mechanical Engineering listed below are indicative and include courses designed by the Department at the Master's level. With the approval of the tutor, students may also select Master's-level courses offered by other departments at ETH. These courses will be marked as non-regular in the LAG, but their categorization as Core Courses is possible if included in the approved LAG.)
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Robotics (Only one of the two course units 263-5902-00L Computer Vision resp. 227-0447-00L Image Analysis and Computer Vision may be recognised for credits for the overall (CSE Bachelor and Master) study programmes. Only one of the two course units 263-5210-00L Probabilistic Artificial Intelligence resp. 252-0535-00L Advanced Machine Learning may be recognised for credits in the field of specialisation `Robotics' for the overall (CSE Bachelor and Master) study programmes. However, the other course unit may be recognised for a different category.)
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Application Area (Only necessary and eligible for the Master degree in Applied Mathematics. One of the application areas specified must be selected for the category Application Area for the Master degree in Applied Mathematics. At least 8 credits are required in the chosen application area. Credits from other application areas cannot be recognised for further application areas.)
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Track: Systems and Control (The core courses and specialisation courses below are a selection for students who wish to specialise in the area of "Systems and Control", see . The individual study plan is subject to the tutor's approval.)
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Core Courses (These core courses are particularly recommended for the field of "Systems and Control". You may choose core courses form other fields in agreement with your tutor. A minimum of 24 credits must be obtained from core courses during the MSc EEIT.)
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Specialisation Courses (These specialisation courses are particularly recommended for the area of "Systems and Control", but you are free to choose courses from any other field in agreement with your tutor. Semester / Research Projects are not allowed in this category. A minimum of 40 credits must be obtained from specialisation courses during the Master's Programme.)
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Quantitative Finance Master (see Students in the Joint Degree Master's Programme "Quantitative Finance" must book University of Zurich modules directly at the University of Zurich. Those modules are not listed here.)
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MF (Mathematical Methods in Finance) (For possible additional course offerings see )
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Doctorate Mathematics (More Information at: )
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Subject Specialisation (The list of courses eligible for doctoral students is published each semester in the newsletter of the ZGSM.)
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Graduate School (Official website of the Zurich Graduate School in Mathematics: )
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Doctorate Mechanical and Process Engineering (More Information at: )
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Electives (This is a selection of courses particularly suitable for the MSc QE. In agreement with the tutor, students may choose other courses from the ETH course catalogue.)
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Deep Track Courses (At least 20 credits must be completed within the deep track courses. Surplus credit points can be counted towards the electives.)
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Deep Track Aerospace Engineering (These courses can be credited either as a specialization subject or as an elective subject.)
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Deep Track Robotics (These courses can be credited either as a specialization subject or as an elective subject.)
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