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Graduate courses

Departments' graduate courses for PhD-students.


Syllabus for

Academic year
SSY220 - Discrete event control and optimization
Syllabus adopted 2014-02-13 by Head of Programme (or corresponding)
Owner: MPSYS
7,5 Credits
Grading: TH - Five, Four, Three, Not passed
Education cycle: Second-cycle
Major subject: Automation and Mechatronics Engineering

Teaching language: English
Open for exchange students
Block schedule: D

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0108 Examination 5,0 c Grading: TH   5,0 c   28 May 2016 am M,  06 Apr 2016 pm EKL,  24 Aug 2016 am M
0208 Laboratory 2,5 c Grading: UG   2,5 c    

In programs



Professor  Martin Fabian


In order to be eligible for a second cycle course the applicant needs to fulfil the general and specific entry requirements of the programme that owns the course. (If the second cycle course is owned by a first cycle programme, second cycle entry requirements apply.)
Exemption from the eligibility requirement: Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling these requirements.

Course specific prerequisites

Discrete Event Systems (or comparable knowledge acquired by other means).


The course aims to give advanced knowledge about formal methods and how these may be used for reasoning about and analyzing the performance of discrete event systems. Typical applications for using formal methods are verification and synthesis of control functions for embedded systems, control and optimization of automated production systems, and communication systems. The course focuses on modeling, specification, simulation, verification, synthesis, and optimization.

Learning outcomes (after completion of the course the student should be able to)

* Confidently use the common terminology within the formal methods research area.

* Give a detailed account of formalisms for modeling discrete event systems, especially various types of finite state machines.

* Analyse properties such as reachability, coreachability, controllability, observability using discrete mathematics.

* Perform synthesis and optimization of control functions based on given system models and specification of desired behavior for the total closed-loop system.

* Give an account of different verification and synthesis algorithms.

* Understand and present how optimization algorithms such as A* and MILP work.

* Use existing algorithms to perform optimization tasks.

* Understand and present how advanced verification and synthesis algorithms, such as modular, and compositional abstraction-based, work.

* Use existing algorithms to perform synthesis and verification tasks. 


The course covers the following topics: Theory and practice of modeling and specification of logic and sequential behaviors. Examples of modeling formalisms include formal languages, finite state machines. Theory and practice of verification of safety and liveness properties, such as reachability, blocking, deadlock and forbidden states, through state-space search methods. Theory and practice of synthesis and optimization of control functions based on given system models and specification of desired behavior of the controlled system. Theory and practice of general optimization techniques such as mixed integer-linear programming, branch and bound and other discrete optimization algorithms (Dijkstra's, A*).


The course comprises lectures, exercises, and a number of assignments that address important parts of the course. These hand-in assignments involve modeling, specification, verification, synthesis, and optimization. The hand-in assignments are peer-reviewed in a scientific conference type of setting.


Martin Fabian, DECO Lecture notes. Additionally scientific papers and other extra material may be handed out.


Examination is based on a conventional written exam, as well as passed hand-ins.

Page manager Published: Thu 04 Feb 2021.