Course detail
Modelling and Simulation
FIT-IMSAcad. year: 2010/2011
Introduction to modelling and simulation concepts. System analysis and classification. Abstract and simulation models. Continuous, discrete, and combined models. Heterogeneous models. Using Petri nets and finite automata in simulation. Pseudorandom number generation and testing. Queuing systems. Monte Carlo method. Continuous simulation, numerical methods, Modelica language. Simulation experiment control. Visualization and analysis of simulation results.
Language of instruction
Number of ECTS credits
Mode of study
Guarantor
Department
Learning outcomes of the course unit
Prerequisites
Co-requisites
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Course curriculum
- Introduction to modelling and simulation. System analysis, clasification of systems. System theory basics, its relation to simulation.
- Model classification: conceptual, abstract, and simulation models. Heterogeneous models. Methodology of model building.
- Simulation systems and languages, means for model and experiment description. Principles of simulation system design.
- Parallel process modelling. Using Petri nets and finite automata in simulation.
- Models o queuing systems. Discrete simulation models. Model time, simulation experiment control.
- Continuous systems modelling. Overview of numerical methods used for continuous simulation. System Dymola/Modelica.
- Combined simulation. The role of simulation in digital systems design.
- Special model classes, models of heterogeneous systems.
- Cellular automata and simulation.
- Checking model validity, verification of models. Analysis of simulation results.
- Simulation results visualization. Model optimization.
- Generating, transformation, and testing of pseudorandom numbers. Stochastic models, Monte Carlo method.
- Overview of commonly used simulation systems.
Work placements
Aims
Specification of controlled education, way of implementation and compensation for absences
The knowledge of students is examined by the projects and
by the final exam. The minimal number of points which
can be obtained from the final exam is 30. Otherwise,
no points will be assigned to a student.
Recommended optional programme components
Prerequisites and corequisites
- recommended prerequisite
Algorithms - recommended prerequisite
Signals and Systems - recommended prerequisite
Introduction to Programming Systems - recommended prerequisite
Linear Algebra - recommended prerequisite
Mathematical Analysis 1 - recommended prerequisite
Discrete Mathematics - recommended prerequisite
Mathematical Analysis 2 - recommended prerequisite
Probability and Statistics
Basic literature
Recommended reading
Classification of course in study plans
Type of course unit
Lecture
Teacher / Lecturer
Syllabus
- Introduction to modelling and simulation. System analysis, clasification of systems. System theory basics, its relation to simulation.
- Model classification: conceptual, abstract, and simulation models. Heterogeneous models. Methodology of model building.
- Simulation systems and languages, means for model and experiment description. Principles of simulation system design.
- Parallel process modelling. Using Petri nets and finite automata in simulation.
- Models o queuing systems. Discrete simulation models. Model time, simulation experiment control.
- Continuous systems modelling. Overview of numerical methods used for continuous simulation. System Dymola/Modelica.
- Combined simulation. The role of simulation in digital systems design.
- Special model classes, models of heterogeneous systems.
- Cellular automata and simulation.
- Checking model validity, verification of models. Analysis of simulation results.
- Simulation results visualization. Model optimization.
- Generating, transformation, and testing of pseudorandom numbers. Stochastic models, Monte Carlo method.
- Overview of commonly used simulation systems.
Fundamentals seminar
Teacher / Lecturer
Syllabus
- discrete simulation: using Petri nets, using SIMLIB/C++
- continuous simulation: differential equations, block diagrams, examples of models in SIMLIB/C++
Exercise in computer lab
Teacher / Lecturer
Syllabus
- Introduction to Dymola simulation system, continuous simulation.
E-learning texts