Course Syllabus for

Feedback Control of Computing Systems
Reglering av datorsystem

FRT185F, 5 credits

Valid from: Autumn 2017
Decided by: Professor Thomas Johansson
Date of establishment: 2017-12-07

General Information

Division: Automatic Control
Course type: Third-cycle course
Teaching language: English


Control theory is spreading into the computing system domain and is today being applied in for instance CPU scheduling, clock synchronisation, thermal/power/performance management, and self-adaptive software. The aim of the course is to bridge the gap between computer science and automatic control and enable cooperation between specialists within the two domains.


Knowledge and Understanding

For a passing grade the doctoral student must

Competences and Skills

For a passing grade the doctoral student must

Judgement and Approach

For a passing grade the doctoral student must have gained insight into how models and approaches are different between automatic control and computer science.

Course Contents

Control-theoretical design of scheduling policies and synchronization protocols. Mathematical modelling of computing systems. Modelica as a language for simulating and designing control strategies for computing systems. Control of queues.

Course Literature

A reading list of research papers will be provided in class. ---- other possible references - A. Leva, M. Maggio, A.V. Papadopoulos, F. Terraneo, "Control-based operating system design", IET, London, 2012. - A. Filieri, H. Hoffmann, M. Maggio, "Automated design of self-adaptive software with control-theoretical formal guarantees", Proc. 36th International Conference on Software Engineering, Hyderabad 2014, 299-310. - A.V. Papadopoulos, M. Maggio, F. Terraneo, A. Leva, "A dynamic modelling framework for control-based computing system design", Mathematical and Computer Modelling of Dynamical Systems 21(3), 2015, 251-271.

Instruction Details

Types of instruction: Lectures, project. The project will be carried out in groups of maximum three people.

Examination Details

Examination formats: Written report, written assignments. Participation in the lectures is mandatory. Student performance is assessed in the form of a project to be completed after the lecture series. A course report is required in the form of a short paper.
Grading scale: Failed, pass

Admission Details

Assumed prior knowledge: Basic knowledge of modeling and dynamic systems.

Further Information

The course is given in the form of five full-day lectures and has a final project.

Course Occasion Information

Contact and Other Information

Course coordinators:
Web page:

Complete view