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SF2852 Optimal Control Theory 7.5 credits

Information per course offering

Choose semester and course offering to see current information and more about the course, such as course syllabus, study period, and application information.

Termin

Information for Autumn 2025 Start 25 Aug 2025 programme students

Course location

KTH Campus

Duration
25 Aug 2025 - 24 Oct 2025
Periods
P1 (7.5 hp)
Pace of study

50%

Application code

51220

Form of study

Normal Daytime

Language of instruction

English

Course memo
Course memo is not published
Number of places

Places are not limited

Target group

Open for all programmes as long as it can be included in your programme.

Planned modular schedule
[object Object]
Schedule
Schedule is not published

Contact

Examiner
No information inserted
Course coordinator
No information inserted
Teachers
No information inserted

Course syllabus as PDF

Please note: all information from the Course syllabus is available on this page in an accessible format.

Course syllabus SF2852 (Spring 2022–)
Headings with content from the Course syllabus SF2852 (Spring 2022–) are denoted with an asterisk ( )

Content and learning outcomes

Course contents

  • Dynamic programming in continuous and discrete time.
  • Hamilton-Jacobi-Bellman equation.
  • Theory of ordinary differential equations.
  • The Pontryagin maximum principle.
  • Linear quadratic optimization.
  • Infinite horizon optimal control problems.
  • Model predictive control.
  • Numerical methods for optimal control problems.

Intended learning outcomes

To pass the course, the student shall be able to do the following:

  • Formulate optimal control problems on standard form from specifications on dynamics, constraints and control objective. In addition, be able to explain how various control objectives affect the optimal performance.
  • Use the methods in the course to design closed loop and open loop controllers for optimal control problems.
  • Apply the methods given in the course to solve example problems and use computational software to solve realistic problems numerically.

To receive the highest grade, the student shall in addition be able to do the following:

  • Combine and explain the tools of the course and apply them to more complex problems.

Literature and preparations

Specific prerequisites

  • English B / English 6
  • Completed basic course in optimization (SF1811, SF1861 or equivalent)
  • Completed basic course in mathematical statistics (SF1914, SF1918, SF1922 or equivalent)
  • Completed basic course in numerical analysis (SF1544, SF1545 or equivalent)
  • Completed basic course in differential equations (SF1633, SF1683 or equivalent).

Recommended prerequisites

A completed course in control theory.

Literature

You can find information about course literature either in the course memo for the course offering or in the course room in Canvas.

Examination and completion

If the course is discontinued, students may request to be examined during the following two academic years.

Grading scale

A, B, C, D, E, FX, F

Examination

  • HEM2 - Homework, 1.5 credits, grading scale: P, F
  • TEN2 - Written exam, 6.0 credits, grading scale: A, B, C, D, E, FX, F

Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.

The examiner may apply another examination format when re-examining individual students.

Examiner

Ethical approach

  • All members of a group are responsible for the group's work.
  • In any assessment, every student shall honestly disclose any help received and sources used.
  • In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.

Further information

Course room in Canvas

Registered students find further information about the implementation of the course in the course room in Canvas. A link to the course room can be found under the tab Studies in the Personal menu at the start of the course.

Offered by

Main field of study

Mathematics

Education cycle

Second cycle