Modelling Methods

Subject description

Introduction (the reasons for the construction of models, basic definitions, approaches to model design)

Introduction of similarities or analogies and their importance in the context of systems’ engineering,

Illustration of the importance of modelling with examples from technical and non – technical areas,

Analysis and model simplification / extension (structural simplification / extension and linearization),

Consideration of some specific types of models,

Quantitative and qualitative evaluation of models,

Conventional approaches to models‘ optimization and usage of global and hybrid approaches,

Usage of software tools (MATLAB, Simulink, Control System Toolbox) and the presentation of some additional toolboxes in MATLAB and in some other programs, suitable also for the so called system dynamics and visualization,

illustrative examples of model design of complex laboratory pilot plants.

The subject is taught in programs

Objectives and competences

Course goals are:

to present advanced knowledge in the field of process modelling,

to accent the wide and multidisciplinary nature of the area and thus its broad meaning,

to describe typical and also some specific forms of models and their scope,

to present some of the software tools and their usefulness in support of the issue being discussed,

to acquaint students with the experiments design and their implementation in support to theoretical modelling approach,

to present verification and evaluation in modelling of real systems from technical and non – technical fields,

to acquaint students with appropriate literature selection, research work, and appropriate written and oral presentation of professional, or scientific work results.

Teaching and learning methods

Lectures, homeworks, laboratory exercises, seminar and project work

Expected study results

After the successful completion of the exam students should be able to:

  • use a systematic approach to problem solving by modelling (theoretical , experimental and combined) in technical and non – technical areas;
  • analysis of dynamic mathematical models;
  • experiment with linear and nonlinear models and to perform corresponding comparison and qualitative and quantitative evaluation;
  • optimize mathematical models using conventional, global, and hybrid methods;
  • present adequately a developed modelling results in both written and oral form.

Basic sources and literature

  1. ATANASIJEVIĆ-KUNC, Maja. Metode modeliranja, Študijsko gradivo. Fakulteta za elektrotehniko, Univerza v Ljubljani, 2016.
  2. KARBA, Rihard, Modeliranje procesov, Fakulteta za elektrotehniko, Založba FE in FRI, Univerza v Ljubljani, 1999.
  3. ATANASIJEVIĆ-KUNC, Maja. Modeliranje procesov: Zbirka primerov z ilustracijami v okolju Matlab-Simulink. Fakulteta za elektrotehniko, Založba FE in FRI, 2008.
  4. CELLIER, François, E.. Continuous system modeling, Springer-Verlag, New York, 1991.
  5. GODFREY, Keith. Compartmental Models and Their Application. Academic Press, London, 1983.
  6. FOGEL, D.B.. Evolutionary Computation, Toward a New Philosophy of Machine Intelligence, IEEE Press Series on Computational Intelligence, 200
  7. MAGRAB, Edward B., AZRAM, Shapour, BALACHANDRAN, Balakumar, DUNCAN, James H., HEROLD, Keith E., WALSH, Gregory C.. An Engineer's Guide to MATLAB with Applications from Mechanical, Aerospace, Electrical, and Civil Engineering. Pearson Prentice Hall, New Jersey, 2005.
  8. MONSEF Youssef. Modelling and simulation of complex systems, concepts, methods and tools. Erlangen: Society for Computer Simulation Int.; 1997.

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