13E053MIP - System Modeling and Identification
Course specification | ||||
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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 | ||||
URL to the subject page | https://automatika.etf.bg.edu.rs/sr/13e053mip | |||
URL to lectures | https://teams.microsoft.com/l/team/19%3aCUdt_a3a4q5_PPTQ7TSZmYxE2NeMAt-3kQQ6QMmv1UA1%40thread.tacv2/conversations?groupId=3dfda4c5-783e-4693-ae66-a6aedcd35a3a&tenantId=1774ef2e-9c62-478a-8d3a-fd2a495547ba | |||
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 | ||||
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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 |