Systems Modeling & Simulation

Course Information
TitleΠΡΟΣΟΜΟΙΩΣΗ ΚΑΙ ΜΟΝΤΕΛΟΠΟΙΗΣΗ ΣΥΣΤΗΜΑΤΩΝ / Systems Modeling & Simulation
CodeΗΥ3102
FacultyEngineering
SchoolElectrical and Computer Engineering
Cycle / Level1st / Undergraduate
Teaching PeriodSpring
CoordinatorGeorgios Rovithakis
CommonNo
StatusActive
Course ID20000606

Class Information
Academic Year2018 – 2019
Class PeriodWinter
Faculty Instructors
Weekly Hours3
Class ID
600130528
Course Type 2016-2020
  • Scientific Area
Course Type 2011-2015
Specific Foundation / Core
Mode of Delivery
  • Face to face
Digital Course Content
Language of Instruction
  • Greek (Instruction, Examination)
  • English (Examination)
Learning Outcomes
Upon successfull completion of the course, the students will be able to: a) construct mathematical models from data and they will implement them in MATLAB, b) design and analyze off-line and on-line parameter estimation algorithms and they will implement them in MATLAB, c) perform model validation.
General Competences
  • Apply knowledge in practice
  • Retrieve, analyse and synthesise data and information, with the use of necessary technologies
  • Work autonomously
  • Generate new research ideas
  • Advance free, creative and causative thinking
Course Content (Syllabus)
Models of dynamical systems Linear parameterization Off-line parameter estimation algorithms and the Least-Squares method On-line parametrer estimation algorithms (the parameter drift phenomenon, σ-modification, switching σ-modification, dead-zone, projection modification) Model structure selection methods Model validation
Keywords
Mathematical models, parameter estimation, validation
Educational Material Types
  • Notes
  • Slide presentations
  • Book
Use of Information and Communication Technologies
Use of ICT
  • Use of ICT in Course Teaching
  • Use of ICT in Laboratory Teaching
  • Use of ICT in Communication with Students
Course Organization
ActivitiesWorkloadECTSIndividualTeamworkErasmus
Lectures39
Project120
Total159
Student Assessment
Description
Final Written Examination Oral Project Examination
Student Assessment methods
  • Written Exam with Multiple Choice Questions (Summative)
  • Written Exam with Short Answer Questions (Summative)
  • Written Assignment (Summative)
  • Performance / Staging (Summative)
  • Written Exam with Problem Solving (Summative)
  • Labortatory Assignment (Summative)
Bibliography
Additional bibliography for study
1.L. Ljung, System Identification Theory for the User, Prentice Hall, New Jersey, 1999. 2.R. Johansson, System Modeling & Identification, Prentice Hall, New Jersey, 1993. 3.O. Nelles, Nonlinear System Identification, Springer, Berlin, 2001.
Last Update
30-11-2020