Introduction to Control Systems

The primary goal of this course is to teach students the basic principles of computer control and automation of engineering systems and processes.
Students obtain the following competences:
- basic control principles and general methods of systems' design and assembly,
- approach to control systems as a product (from the aspect of key attributes like, for example, purpose, function, mechanism and structure), a life-cycle aspect to control systems and use of non-engineering aspects of control-systems use
- knowledge of basic methods, tools and elements necessary for control-system design like: mathematical modelling and computer simulation, various methods for control design and implementation of control functions, computer-aided control-system design, sensors, actuators, and supervisory-control software.

Required prerequisit knowledge from courses: Engineering mathematics, Engineering physics, Basics of Information and Communication Technologies and Electrical engineering.

1. Introduction to system theory
2. Control systems (purpose, function)
3. Introduction to control-systems technology
4. Sequential control
5. Higher control levels
6. Modelling and control-systems' analysis
7. Control-systems design

Knowledge and understanding:
Introduction to control system and general control principles are mastered first. The aspect of control system as a product from the aspect of key attributes like purpose, function, mechanism and structure are taught next. Life-cycle aspect of control systems and non-engineering aspects are the next topics. The main part of the course is devoted to basic methods, tools and elements for control-systems design. In this framework the emphasys is on mathematical modelling and computer simulation, various controll-design methods, implementation of control functions, computer-aides control-system design, sensors, actuators, and supervisory-control software.

• J. Kocijan, S. Strmčnik (2016): Osnove avtomatskega vodenja, Založba Univerze v Novi Gorici, Nova Gorica. Založba UNG
• J. Kocijan (2021): Zbirka nalog iz osnov avtomatskega vodenja. Vipava; Ljubljana.
• Več avtorjev (1998): Celostni pristop k računalniškemu vodenju procesov, urednik S. Strmčnik, Založba Fakultete za elektrotehniko, Ljubljana. Catalogue E-version
• J. Kocijan (1996): Načrtovanje vodenja dinamičnih sistemov, Zbirka nalog, Založba FE in FRI, Ljubljana. Catalogue
• B. Zupančič (2011): Avtomatsko vodenje sistemov, Založba FE in FRI, Ljubljana. E-version

• Written exam, which assesses knowledge of the implementation of concepts of basic principles of control-systems analysis and design. • Oral exam, which assesses knowledge of the theoretical and general concepts of control-systems design, control system as a product, Life-cycle aspect of control systems, non-engineering aspects, knowledge of basic methods, tools and elements of control design. 50/50

Prof. dr. Juš Kocijan is currently a senior researcher at the Department of Systems and Control, Jozef Stefan Institute and Professor of Electrical Engineering at the School of Engineering and Management, University of Nova Gorica, Slovenia. His other experience includes: running a number of international and domestic research projects, serving as editor and on editorial boards of research journals, serving as a member of IFAC Technical committee on Computational Intelligence in Control. Prof. Kocijan is a Senior member IEEE, IEEE Control Systems Society, a member of SLOSIM – Slovenian Society for Simulation and Modelling and Automatic control society of Slovenia. His research interests include modelling of dynamic systems with Gaussian process models, Control based on Gaussian process models, Multiple-model approaches to modelling and control, Applied nonlinear control, Individual Channel Analysis and Design.

Selected bibliography

KOCIJAN, Juš. Modelling and control of dynamic systems using Gaussian process models, (Advances in industrial control). Cham [etc.]: Springer, cop. 2016. XVI, 267 str., graf. prikazi. ISBN 978-3-319-21020-9, doi: 10.1007/978-3-319-21021-6. [COBISS.SI-ID 29101607]

KARBA, Rihard, KARER, Gorazd, KOCIJAN, Juš, BAJD, Tadej, ŽAGAR KARER, Mojca, ŽAGAR KARER, Mojca (urednik), FAJFAR, Tanja (urednik). Terminološki slovar avtomatike, (Zbirka Slovarji). Ljubljana: Založba ZRC, 2014. 136 str. ISBN 978-961-254-719-6. [COBISS.SI-ID 275900160]

KOCIJAN, Juš, GRADIŠAR, Dejan, BOŽNAR, Marija, GRAŠIČ, Boštjan, MLAKAR, Primož. On-line algorithm for ground-level ozone prediction with a mobile station. Atmospheric environment, ISSN 1352-2310. [Print ed.], 2016, vol. 131, str. 326-333, doi: 10.1016/j.atmosenv.2016.02.012. [COBISS.SI-ID 29306919]

ALEKSOVSKI, Darko, KOCIJAN, Juš, DŽEROSKI, Sašo. Ensembles of fuzzy linear model trees for the identification of multi-output systems. IEEE transactions on fuzzy systems, ISSN 1063-6706. [Print ed.], 2016, vol. 24, no. 4, str. 916-929, doi: 10.1109/TFUZZ.2015.2489234. [COBISS.SI-ID 28967207]

KOCIJAN, Juš, HANČIČ, Marko, PETELIN, Dejan, BOŽNAR, Marija, MLAKAR, Primož. Regressor selection for ozone prediction. Simulation modelling practice and theory, ISSN 1569-190X, maj 2015, vol. 54, str. 101-115, doi: 10.1016/j.simpat.2015.03.004. [COBISS.SI-ID 28481319]

KOCIJAN, Juš, HVALA, Nadja. Sequencing batch-reactor control using Gaussian-process models. Bioresource technology, ISSN 0960-8524. [Print ed.], jun. 2013, vol. 137, str. 340-348, doi: 10.1016/j.biortech.2013.03.138. [COBISS.SI-ID 26698535]

PETELIN, Dejan, GRANCHAROVA, Alexandra, KOCIJAN, Juš. Evolving Gaussian process models for prediction of ozone concentration in the air. Simulation modelling practice and theory, 2013, vol. 33, str. 68-80, doi: 10.1016/j.simpat.2012.04.005. [COBISS.SI-ID 26629159]

JUŽNIČ-ZONTA, Živko, KOCIJAN, Juš, FLOTATS, Xavier, VREČKO, Darko. Multi-criteria analyses of wastewater treatment bio-processes under an uncertainty and a multiplicity of steady states. Water res. (Oxford). [Print Ed.], 2012, vol. 46, no. 18, str. 6121-6131, doi: 10.1016/j.watres.2012.08.035. [COBISS.SI-ID 26152231]

GRANCHAROVA, Alexandra, KOCIJAN, Juš, JOHANSEN, Tor Arne. Explicit output-feedback nonlinear predictive control based on black-box models. Eng. appl. artif. intell.. [Print ed.], 2011, vol. 24, no. 2, str. 388-397. [COBISS.SI-ID 24397351]

AŽMAN, Kristjan, KOCIJAN, Juš. Dynamical systems identification using Gaussian process models with incorporated local models. Eng. appl. artif. intell.. [Print ed.], 2011, vol. 24, no. 2, str. 398-408. [COBISS.SI-ID 24397095]