Computer Simulation

Subject description

Introduction: definitions, modelling and simulation as a unified cyclic procedure, applicability in the field of control systems.

Basics of modelling: balance equations, theoretical and experimental modelling, examples.

Types of models and simulations: continuous, discrete-event, hybrid, simulation in real time.

Simulation methods: indirect and implicit method, simulation of transfer functions – nested and partitioned method, simulation systems with large delays.

Simulation tools: the basic features.

Simulation using the basic functions of Matlab environment.

Simulation in Matlab – Simulink: basic capabilities, advanced capabilities: subsystems and masking, conditionally executable systems, analysis and optimization of Simulink models: execution of Simulink models from Matlab, linearization, steady state analysis, optimization, S- functions.

Multi-domain, object-oriented modelling: causal and non-causal models, important properties of OO environments. Language Modelica, a standard library, Modelica environments, Dymola environment.

How digital simulation works. Numerical integration, sorting algorithm, simulation using general purpose programming languages.

Numerical methods and problems: integration methods, numerical stability, the problem of discontinuities, the problem of algebraic loops.

Simulation of discrete-event systems. The strategy of the triggering with event graphs and process flows, examples with Matlab, SimEvents, Enterprise Dynamics, AnyLogic. Statistical features in discrete event modelling and simulation.

Engineering approach in experimental modelling. Experimental modelling of proportional and integral processes. Engineering understanding of the responses and simplified models.

The subject is taught in programs

Objectives and competences

Computer simulation is the most important, the most common but also relatively simple approach for the analysis and design of systems, also control systems. The basic objective is to present areas in an interesting way through a series of examples and using computer tools. Students will learn the basic approaches to modelling of continuous systems as well as discrete event systems, the basic approaches to simulation, they learn the basic and advanced capabilities of computer tools and become familiar with numerical problems in digital simulation.

Teaching and learning methods

Lectures and laboratory exercises.

Expected study results

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

-develop mathematical models of simple processes with theoretical modelling,

-develop mathematical models of simple processes with an engineering approach of experimental modelling,

– to explain how digital simulation works,

– to select a computer tool for modelling and simulation,

-use computer tools for modelling and simulation: Matlab-Simulink and Dymola-Modelica,

– to develop even more demanding simulation models in the Matlab-Simulink, Dymola-Modelica or in the general-purpose programming language,

– to choose the appropriate numerical integration algorithm.

Basic sources and literature


  1. B. Zupančič,  Računalniška simulacija, učbenik v delovni verziji,  Univerza v Ljubljani, Fakulteta za elektrotehniko, 2017.
  2. B. Zupančič,  Modelica, učbenik v delovni verziji,  Univerza v Ljubljani, Fakulteta za elektrotehniko, 2017.
  3. B. Zupančič, R. Karba, D. Matko, I. Škrjanc,  Simulacija dinamičnih sistemov,  Založba FE in FRI, Univerza v Ljubljani, Fakulteta za elektrotehniko , 2010.
  4. J.B. Dabney, T.L. Harman , Mastering SIMULINK , Prentice Hall, Upper Saddle River, N.J., USA, 200
  5. S. Oblak, I. Škrjanc, Matlab s Simulinkom : priročnik za laboratorijske vaje, 1. izdaja, Založba FE in FRI, Univerza v  Ljubljani, Fakulteta za elektrotehniko, 200


  1. D. Matko, B. Zupančič, R. Karba , Simulation and Modelling of Continuous Systems – A Case Study Approach, Prentice Hall, 1992.
  2. Dymola, Dynamic Modeling Laboratory, Users manual, ver 2014 FD01. Dessault Systems, Dynasim AB, Sweden, Lund, 2013.
  3. R. Karba, Modeliranje procesov, 1. izdaja, Univerza v Ljubljani, Fakulteta za elektrotehniko, 1999.
  4. F.E. Cellier, Continuous System Modeling, Springer – Verlag, NY, USA, 1991.
  5. F.E. Cellier, E. Kofman, Continuous System Simulation, Springer Science+Business Media, Inc., NY, USA, 2006
  6. P. Fritzson, Principles of Object Oriented Modeling and Simulation with Modelica 2.1, IEEE Press, John Wiley&Sons, Inc., Publication, USA, 2004
  7. S. Raczynski, Modeling and Simulation, John Wiley & Sons, Ltd., England, 2006

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