Systems Dynamics Modeling and Simulation

Course Description

An overview of the mathematical and graphical methods for describing dynamic systems. Defining mathematical descriptions of discrete event systems and distributed parameter systems. Methods for defining mathematical model and parameters of mathematical model. Modeling systems with uncertainties. Application of numerical integration methods to simulate systems in time domain. Application of numerical optimization methods for estimation of model parameters based on measured data.

Learning Outcomes

  1. Apply the methods of mathematical and graphical description of dynamic systems
  2. explain the dynamic changes in the system based on mathematical models
  3. apply physical laws for description of the system by differential equations, difference equations, transfer functions and state space equations
  4. use a mathematical description of the system for design of block diagrams, signal flow graphs and bond graphs
  5. analyze the behavior of the system in steady state and during transient responses
  6. identify system parameters based on dinamic system measurements
  7. assemble different type of models in a single model
  8. assess the credibility of models based on steady state estimates and comparisons with real system responses

Forms of Teaching

Lectures

Exercises

Laboratory

Week by Week Schedule

  1. System modeling principles and model classification
  2. Equation of the dynamical equilibrium and the phenomenological equations
  3. Simulation model; Sort list definition and algebric loops, Fix step integration methods
  4. Fix step integration methods, Variable step integration methods and stiff system solvers
  5. Block scheme oriented simulation tools
  6. Block scheme oriented simulation tools, Variables and operations in simulation language, Functions and block oriented simulation
  7. Graphical representation of the simulation results, Usage of the symbolic and control tools in simulation of the system
  8. Midterm exam
  9. Modeling examples of real dynamic systems
  10. Modeling examples of real dynamic systems
  11. Modeling examples of real dynamic systems
  12. Real time simulation and equivalent models
  13. Real time simulation and equivalent models
  14. Real time electrical equivalent models and normalization
  15. Final exam

Study Programmes

University graduate
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Computational Modelling in Engineering (profile)
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Computer Engineering (profile)
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Computer Science (profile)
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Control Systems and Robotics (profile)
Core-elective courses 2 (1. semester)
Data Science (profile)
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Electrical Power Engineering (profile)
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Electric Machines, Drives and Automation (profile)
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Electronic and Computer Engineering (profile)
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Electronics (profile)
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Information and Communication Engineering (profile)
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Network Science (profile)
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Software Engineering and Information Systems (profile)
Free Elective Courses (1. semester) (3. semester)

Literature

(.), D. J. Cloud: Applied Modeling and Simulation: An Integrated Approach to Development and Operation, McGraw-Hill 1998, ISBN/ISSN 0072283033,
(.), D. C. Karnopp, D. L. Margolis, R. C. Rosenberg, System Dynamics: Modeling and Simulation of Mechatronic Systems, John Wiley & sons, In, 2000, ISBN/ISSN 0471333018 ,
(.), Ž. Ban, J. Matuško, I. Petrović: Primjena programskog sustava Matlab za rješavanje tehničkih problema, Graphis, Zagreb 2010, ISBN/ISSN 978-953-279-011-5 ,
(.), H. S. Sarjoughian, F. E. Cellier: Discrete Event Modeling and Simulation Technologies: A Tapestry of Systems and AI-Based Theories and Methodologies, Springer, 2001, ISBN/ISSN 0387950656,

For students

General

ID 222450
  Winter semester
5 ECTS
L3 English Level
L1 e-Learning
30 Lectures
15 Exercises
16 Laboratory exercises