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13E053MIP - System Modeling and Identification

Course specification
Course title System Modeling and Identification
Acronym 13E053MIP
Study programme Electrical Engineering and Computing
Module
Type of study bachelor academic studies
Lecturer (for classes)
Lecturer/Associate (for practice)
Lecturer/Associate (for OTC)
ESPB 6.0 Status elective
Condition NONE
The goal Introduce students to the fundamentals of continuous and discrete systems modeling and basic identification procedures; Tools for signals and systems simulation and identification, using by time, frequency and complex domain; Understanding and using statistical approaches for model structure selection, model validation and parametric and nonparametric systems identification;
The outcome The student is competent to apply different techniques and use different software tools in order to modeling and identification of signals and systems. The student is familiar with the most commonly used methods of nonparametric and parametric identification.
Contents
Contents of lectures Modeling: model building approaches, mathematical models, bond graphs. Nonparametric identification.Fourier analysis, persistency of excitation. Parametric identification: prediction error methods, prediction models, least - squares method. Model validation. Numerical solution of differential equations.
Contents of exercises Through examples, tasks and problems, the student learns how to apply the theorems and concepts learned in lectures.Student will learn to use the mathematical software and to solve practical tasks and problems.
Literature
  1. Modeling, Identification and Simulation of Dynamical Systems, P.P.J. van den Bosch, A.C. van der Klauw, CRC Press, 1994.
  2. System Identification: Theory for the User, Ljung L, Prentice-Hall, Englewood Cliffs, New Jersey, 1987.
Number of hours per week during the semester/trimester/year
Lectures Exercises OTC Study and Research Other classes
3 1 1
Methods of teaching Lectures (45), exercises (15), discussions, help with assignments and projects using the computer (15).
Knowledge score (maximum points 100)
Pre obligations Points Final exam Points
Activites during lectures 0 Test paper 40
Practical lessons 20 Oral examination 0
Projects
Colloquia 40
Seminars 0