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Graduate courses

Departments' graduate courses for PhD-students.

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Syllabus for

Academic year
SSY165 - Discrete event systems
 
Syllabus adopted 2014-02-26 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, Electrical Engineering
Department: 32 - ELECTRICAL ENGINEERING

The current course round has limited places. Please contact the student center if you are not able to add the course to your selection.
Teaching language: English
Open for exchange students
Block schedule: C

Course module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0107 Examination 5,0c Grading: TH   5,0c   28 Oct 2014 am M,  05 Jan 2015 am M,  25 Aug 2015 am M
0207 Laboratory 2,5c Grading: UG   2,5c    

In programs

MPBME BIOMEDICAL ENGINEERING, MSC PROGR, Year 2 (elective)
MPPEN PRODUCTION ENGINEERING, MSC PROGR, Year 2 (elective)
MPSYS SYSTEMS, CONTROL AND MECHATRONICS, MSC PROGR, Year 1 (compulsory)

Examiner:

Professor  Bengt Lennartson


Course evaluation:

http://document.chalmers.se/doc/b99ef594-e994-4184-938c-e3d1e0f695d7


Eligibility:


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

Basic mathematical and programming skills. A basic knowledge in control engineering is recommended.

Aim

The course aims to give fundamental knowledge and skills in the area of discrete event systems and especially modeling and specification formalisms, simulation, synthesis, optimization and control function implementation. Typical applications are control functions for embedded systems, control of automated production systems, and communication systems.

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

* Use basic discrete mathematics in order to be able to analyze discrete event systems.
* Give an account of different formalisms for modeling discrete event systems, especially finite state automata, formal languages, Petri nets, extended finite state automata, timed and hybrid automata, and demonstrate skill to choose between them.
* Present different kinds of specifications, such as progress and safety specifications, defining what a system should and should not do.
* Compute and analyze different properties of discrete event systems such as reachability, coreachability, and controllability.
* Give an account for the meaning of supervisor synthesis, verification, and simulation.
* Use computer tools in order to perform synthesis and optimization of control functions based on given system models and specifications of desired behavior for the total closed loop system.
* Formulate and analyze hybrid systems including discrete and continuous dynamics.
* Explain and apply basic Markov processes and queuing theory for performance analysis of systems including uncertainties.

Content

The course covers the following topics: Basic discrete mathematics, propositional logic, predicate logic, sets and operations on sets, relations, functions, abstract algebra and morphisms. Modeling and specification of logic and sequential behaviors. Examples of modeling formalisms include formal languages, finite automata, Petri nets, extended finite automata including variables, timed and hybrid automata. Verification of safety and liveness properties, such as reachability, blocking, deadlock and forbidden states, through state-space search methods. Synthesis and optimization of control functions based on given system models and specification of desired behavior of the controlled system. Analysis of hybrid systems including discrete and continuous dynamics. Markov processes and queuing theory for analysis of systems including stochastic uncertainties.

Organisation

The course comprises lectures, exercises, and a number of assignments that address important parts of the course. These assignments involve modeling, specification, and synthesis and are to be handed in.

Literature

Bengt Lennartson: Introduction to Discrete Event Systems - Lecture Notes

Examination

Written exam and passed hand-in-assignments.


Page manager Published: Thu 04 Feb 2021.