Course syllabus

Prediktiv reglering
Predictive Control

FRTN15, 7,5 credits, A (Second Cycle)

Valid for: 2013/14
Decided by: Education Board B
Date of Decision: 2013-04-10

General Information

Elective for: C4, C4-ssr, D4, D4-ssr, E4, E4-ra, F4, F4-ssr, Pi4
Language of instruction: The course will be given in English on demand


The aim of the course is to provide advanced knowledge and skills about design of control systems that include predictive, adaptive and learning algorithms for control of time-variable and partially unknown processes with disturbances, including stability and interaction between control and identification.

Learning outcomes

Knowledge and understanding
For a passing grade the student must

Competences and skills
For a passing grade the student must

Judgement and approach
For a passing grade the student must


Real-time identification, Recursive identification, Automatic controller tuning, Gain scheduling, Automatic calibration, Discrete-time linear systems, Pole-placement, Model reference system, Disturbance models, Optimal prediction, Optimal model-based predictive control, Adaptive control, Self-tuning control, Stochastic adaptive control, Model reference adaptive control, Stability, Passivity, Robustness, Model-predictive control, Iterative learning control, Iterative controller tuning, Applications and software

Examination details

Grading scale: TH
Assessment: Written exam (5 hours), project, three laboratory exercises, two hand-in problems. In the case of less than five registered students, the second and third exam may be given on oral form.

Code: 0107. Name: Examination.
Credits: 7,5. Grading scale: TH.
Code: 0207. Name: Laboratory Work 1.
Credits: 0. Grading scale: UG.
Code: 0307. Name: Laboratory Work 2.
Credits: 0. Grading scale: UG.
Code: 0407. Name: Laboratory Work 3.
Credits: 0. Grading scale: UG.
Code: 0507. Name: Project Work.
Credits: 0. Grading scale: UG.
Code: 0607. Name: Hand-in Problem 1.
Credits: 0. Grading scale: UG.
Code: 0707. Name: Hand-in Problem 2.
Credits: 0. Grading scale: UG.


Required prior knowledge: FRT010 Automatic Control, Basic Course.
The number of participants is limited to: No

Reading list

Contact and other information

Course coordinator: Professor Rolf Johansson,
Course coordinator: Professor Bo Bernhardsson,
Course homepage: