Courses

Modelling and Simulation

General

Course Contents

1 – System Modelling
1.1 Description of dynamic systems (inputs, outputs, disturbances)
1.2 Extraction of a mathematical model from basic principles
(electrical, mechanical, electromechanical, thermal, hydraulic)
1.3 Frequency response models
1.4 Linear and non-linear state space models
1.5 Linearization techniques of nonlinear systems
2 – System identification
2.1 Introduction to least squares methods
2.2 Model fitting to Input-Output Data
2.3 Parameter estimation of parametric models
2.4 Selection of input signals (steps, PRBS, white noise)
2.5 Representative Examples and Solutions with MATLAB
3 – Simulation
3.1 Simulation models
3.2 Types of simulation
3.3 Continuous-time modeling
3.4 Simulation through equations and block diagrams
3.5 Development of discrete-time models
3.6 Development of simulation programs
3.7 MATLAB / SIMULINK simulation models
3.8 Sampling methods
3.9 Random Number Generators
3.10 Monte Carlo method
3.11 Analysis of results
3.12 Simulation of specialized systems (inventory, production and
queues)
Exercises and applications in MATLAB.

Educational Goals

The course focuses on modern trends and methods related to mathematical modeling and simulation of a variety of dynamic systems, which are found in practice in many different fields of application in industry and employ the production engineer. It covers the classical modelling theory in engineering curricula, where continuous time representations are used, and the basic modelling techniques of different types of dynamic systems (electrical, mechanical, thermal, hydraulic, etc.) with the fundamental principles (first principles), the methods of solving the corresponding linear or non-linear equations, and simulation methods with various numerical integration techniques on a digital computer. In addition, basic systems identification techniques based on experimental data after sampling are covered and parametric estimation of discrete time parameters with least squares techniques, with emphasis on the practical application of the computer recognition process in MATLAB / SIMULINK environment. Finally, simulation techniques for problems with a stochastic character (discrete events, random number generators, Monte Carlo) and
related result analysis techniques are examined, with emphasis on specialized systems of interest to the production engineer, from the point of view of business research. Consistent and successful attendance of the course has as expected result to make the student competent:
– to represent systems in the form of a mathematical model based on fundamental principles and make transformations from one form to another;
– to determine and calculate the time response as well as the stability of dynamic systems of different types, by solving the relevant equations and numerical integration in PC,
– to formulate appropriately and use simulation techniques in problems of a contemplative character as well as to have the ability to analyze results and design experiments and evaluate results from the point of view of business research.
– to implement all the above with appropriate programming and visualization in MATLAB / SIMULINK environment with the help of specialized toolboxes.

General Skills

Research, analysis and synthesis of data and information using corresponding technologies, decision making, adaptation to new situations, Promoting free, creative and inductive thinking, independent work, Teamwork.

Teaching Methods

Lectures, Exercises, Online guidance, Projected Presentations, E-mail communication, Online Synchronous and Asynchronous Teaching Platform (Moodle).

Students Evaluation

Assessment Language: English / Greek
The final grade of the course is formed by 80% by the grade of the theoretical part, and 20% by the grade of project work.
The grade of the theoretical part is based on a written final examination.
The written final examination of the theoretical part may include:
Solving problems of application of the acquired knowledge, Short answer questions etc.

Recommended Bibliography

1. Principles of Modeling and Simulation, a multidisciplinary approach, Eds. Sokolowski, Banks, Wiley, 2009
2. Μοdeling and Simulation Fundamentals, Theoretical Underpinnings and Practical Domains, Eds. Sokolowski, Banks, Wiley, 2010
3. Discrete-Event System Simulation, Fifth Edition Jerry Banks, John S.Carson, Barry L.Nelson, David M.Nicol, Prentice Hall, 2005