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Course info
KKY / ZIS
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Course description
Department/Unit / Abbreviation
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KKY
/
ZIS
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Academic Year
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2023/2024
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Academic Year
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2023/2024
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Title
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Intr. to System Ident., Fault Detection
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Form of course completion
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Exam
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Form of course completion
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Exam
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Long Title
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Introduction to System Identification and Fault Detection
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Accredited / Credits
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Yes,
5
Cred.
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Type of completion
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Combined
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Type of completion
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Combined
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Time requirements
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Lecture
2
[Hours/Week]
Tutorial
2
[Hours/Week]
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Course credit prior to examination
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Yes
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Course credit prior to examination
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Yes
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Included in study average
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YES
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Language of instruction
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Czech
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Occ/max
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|
|
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Automatic acceptance of credit before examination
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Yes in the case of a previous evaluation 4 nebo nic.
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Summer semester
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0 / -
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14 / -
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0 / -
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Included in study average
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YES
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Winter semester
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0 / -
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0 / -
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0 / -
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Repeated registration
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NO
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Repeated registration
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NO
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Timetable
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Yes
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Semester taught
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Winter + Summer
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Semester taught
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Winter + Summer
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Minimum (B + C) students
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10
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Optional course |
Yes
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Optional course
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Yes
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Language of instruction
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Czech
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Internship duration
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0
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No. of hours of on-premise lessons |
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Evaluation scale |
1|2|3|4 |
Periodicity |
každý rok
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Evaluation scale for credit before examination |
S|N |
Periodicita upřesnění |
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Fundamental theoretical course |
No
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Fundamental course |
Yes
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Fundamental theoretical course |
No
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Evaluation scale |
1|2|3|4 |
Evaluation scale for credit before examination |
S|N |
Substituted course
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None
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Preclusive courses
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N/A
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Prerequisite courses
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N/A
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Informally recommended courses
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N/A
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Courses depending on this Course
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N/A
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Histogram of students' grades over the years:
Graphic PNG
,
XLS
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Course objectives:
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The aim of the course is to introduce students to system identification and fault detection.
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Requirements on student
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To elaborate four assignments and to understand content of the lectures.
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Content
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Design of mathematical models of systems from experimental data is important for prediction of future behaviour of systems and control system. Fault detection in monitored real systems is crucial for decision making quality and for safety and economic aspects.
1st and 2nd week: basic ideas, system identification, fault detection, signal processing, 3rd - 5th week: nonparametric and parametric methods for identification of linear deterministic and stochastic systems, 6th and 7th week: identification of nonlinear systems, 8th- 12th week: introduction to fault and change detection for deterministic and stochastic systems, 13th week: significance of identification and detection in practical applications.
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Activities
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Fields of study
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Guarantors and lecturers
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-
Guarantors:
Doc. Ing. Ondřej Straka, Ph.D. (100%),
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Lecturer:
Ing. Ivo Punčochář, Ph.D. (100%),
Doc. Ing. Ondřej Straka, Ph.D. (100%),
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Tutorial lecturer:
Ing. Ivo Punčochář, Ph.D. (100%),
Doc. Ing. Ondřej Straka, Ph.D. (100%),
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Literature
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Basic:
Eck V. Identifikace a modelování. ČVUT Praha, 1989.
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Basic:
Witczak, Marcin. Modelling and estimation strategies for fault diagnosis of non-linear systems : from analytical to soft computing approaches. Berlin : Springer, 2007. ISBN 978-3-540-71114-8.
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Extending:
Korbicz, Józef. Fault diagnosis : models, artificial intelligence, applications. Berlin ; Springer, 2004. ISBN 3-540-40767-7.
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Extending:
Šimandl, Miroslav. Identifikace systémů a filtrace. Plzeň : ZČU, 1995. ISBN 80-7082-170-1.
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Recommended:
Liu, G. P. Nonlinear identification and control : a neural network approach. London : Springer, 2001. ISBN 1-85233-342-1.
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On-line library catalogues
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Time requirements
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All forms of study
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Activities
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Time requirements for activity [h]
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Practical training (number of hours)
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26
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Preparation for an examination (30-60)
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45
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Contact hours
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26
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Undergraduate study programme term essay (20-40)
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35
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Total
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132
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Prerequisites
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Knowledge - students are expected to possess the following knowledge before the course commences to finish it successfully: |
disponovat znalostmi základních fyzikálních principů |
disponovat znalostmi základů lineární algebry |
disponovat znalostmi základů teorie praděpodobnosti a statistiky |
Skills - students are expected to possess the following skills before the course commences to finish it successfully: |
pracovat s maticemi, analyzovat jejich vlastnosti |
využít základní vztahy ze statistiky při konstrukci statistických testů |
využít základních fyzikálních principů při popisu chování reálných systémů |
Competences - students are expected to possess the following competences before the course commences to finish it successfully: |
N/A |
N/A |
N/A |
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Learning outcomes
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Knowledge - knowledge resulting from the course: |
disponovat znalostmi základních identifikačních postupů umožňujících nalezení matematického modelu z experimentálních dat |
disponovat znalostmi základních postupů detekce změn a poruch v dynamických systémech |
rozlišit mezi matematickým modelováním a identifikací systémů |
vymezit základní pojmy v oblasti identifikace systémů a detekce změn |
Skills - skills resulting from the course: |
navrhnout detektor chyb využívající odhad parametrů modelu |
navrhnout detektor chyb využívající odhad stavu modelu |
navrhnout detektor chyb využívající paritní rovnice |
navrhnout matematický model reálného systému |
Competences - competences resulting from the course: |
N/A |
N/A |
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Assessment methods
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Knowledge - knowledge achieved by taking this course are verified by the following means: |
Test |
Combined exam |
Skills - skills achieved by taking this course are verified by the following means: |
Individual presentation at a seminar |
Seminar work |
Competences - competence achieved by taking this course are verified by the following means: |
Combined exam |
Individual presentation at a seminar |
Seminar work |
Test |
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Teaching methods
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Knowledge - the following training methods are used to achieve the required knowledge: |
Lecture |
Skills - the following training methods are used to achieve the required skills: |
Practicum |
Competences - the following training methods are used to achieve the required competences: |
Lecture |
Practicum |
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