Course unit code:
Course unit title:
Mode of delivery, planned learning activities and teaching methods:
lecture – 2 hours weekly (on-site method)
laboratory practice – 2 hours weekly (on-site method)
Credits allocated:
Recommended semester:
Automation and Information Engineering in Chemistry and Food Industry – master (full-time, attendance method), 2. semester
Level of study:
Prerequisites for registration:
Assesment methods:
The course is evaluated as follows: 30% work during the semester, 30% written examination, and 40% oral examination (theory). Evaluation scale follows the standard scale of the faculty.
Learning outcomes of the course unit:
Students know foundations of system identification, are able to estimate process parameters from experimental input/output data from step and frequency responses, to apply regression methods and their recursive variants.
Course contents:
1. Introduction to identification, basic terms, subject of system identification (allowance 1/1)
2. Identification procedure, structure selection, verification, input signals (allowance 1/1)
3. Step responses, 1st order model (allowance 1/1)
4. Step responses, 2nd order model (allowance 1/1)
5. Step responses, higher order models (allowance 1/1)
6. Autotuning (allowance 1/1)
7. Frequency analysis, construction of frequency responses, estimation of transfer functions (allowance 1/1)
8. Regression methods, estimation of parameters, identification of static models (allowance 1/1)
9. Regression methods, identification of dynamic models (allowance 1/1)
10. Recursive least squares, model identifiability, modifications of RLS (allowance 1/1)
11. Recursive LS, continuous-time models (allowance 1/1)
12. Models of linear dynamical systems, model verification (allowance 1/1)
13. Practical issues in identification (allowance 1/1)
Recommended or required reading:
  • MIKLEŠ, J. – FIKAR, M. Identifikácia systémov. Bratislava : STU v Bratislave, 1999. 112 p. ISBN 80-227-1177-2.
  • LJUNG, L. System Identification: Theory for the User. Upper Saddle River : Prentice Hall, 1999. 609 p. ISBN 0-13-656695-2.
Language of instruction:
Slovak, English
Assessed students in total:

A 27.1 %

B 31.8 %

C 20.6 %

D 15 %

E 0.9 %

FX 4.6 %

Name of lecturer(s):
Ľ. Čirka, M. Fikar (2017/2018 – Winter)
Ľ. Čirka, M. Fikar (2016/2017 – Winter)
Ľ. Čirka, M. Fikar (2015/2016 – Winter)
Course supervisor:
prof. Ing. Miroslav Fikar, DrSc.
Last modification:
16. 1. 2018

Department of Information Engineering and Process Control

AIS: 2018/2019   2017/2018  

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