Programming for process control

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 the use of non-engineering aspects of control-systems use * knowledge of basic methods, tools and elements necessary for control-system design like: the selection of sensors, actuators, controllers and supervisory-control software as well as design of basic algorithms for sequential control.

Required prerequisite knowledge from 1st-year courses: Mathematics, Physics and Statistics.

1. Introduction to system theory
   • Introduction to the course, to systems and system theory
   • Principles of control (open-loop, disturbance compensation, closed-loop)

2. Control systems (purpose, function)
   • Control systems (mechanisms, structure)
   • Control-systems life cycle
   • Non-engineering aspects

3. Introduction to control-systems technology
   • Sensors
   • Actuators
   • Signals in control systems

4. Sequential control
   • Introduction to sequential control
   • Programmable logic controllers

5. Higher control levels
   • Production level, process level
   • Process level, SCADA.

6. Case studies in environmental sciences

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. Students acquire comprehension and ability to analyse the operation of automatic control system. The main part of the course is devoted to basic methods, tools and elements for control-systems design. Students get knowledge how to select sensors, actuators, controllers and supervisory-control software as well as how to design basic algorithms for sequential control.

• Več avtorjev (1998): Celostni pristop k računalniškemu vodenju procesov, urednik S. Strmčnik, Založba Fakultete za elektrotehniko, Ljubljana. Catalogue E-version
• H. Jack (2008): Automating Manufacturing Systems with PLCs, E-version
• 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.

• Written exam, which assesses knowledge of the theoretical concepts and the implementation of concepts of principles of control-systems analysis and design (100 %)

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 the IFAC Technical committee on Computational Intelligence in Control. Prof. Kocijan is a Senior member of the IEEE, IEEE Control Systems Society, a member of the 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]

KOCIJAN, Juš. Modeliranje dinamičnih sistemov z umetnimi nevronskimi mrežami in sorodnimi metodami. 2. izd. V Novi Gorici: Založba Univerze, 2015. Ilustr. ISBN 978-961-6311-92-2. [COBISS.SI-ID 281954560]

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]

GRANCHAROVA, Alexandra, VALKOVA, Ivana, HVALA, Nadja, KOCIJAN, Juš. Distributed predictive control based on Gaussian process models. Automatica, ISSN 1873-2836. [Online ed.], Mar. 2023, vol. 149, [article no.] 110807, str. 1-9, ilustr., doi: 10.1016/j.automatica.2022.110807. [COBISS.SI-ID 135932419]

PERNE, Matija, KOCIJAN, Juš, BOŽNAR, Marija, GRAŠIČ, Boštjan, MLAKAR, Primož. Hybrid forecasting of wind for air pollution dispersion over complex terrain. Journal of environmental informatics, ISSN 1726-2135, 2023, 41, 2, str. 88-103, ilustr. http://www.jeionline.org/index.php?journal=mys&page=article&op=view&path%5B%5D=200600073, doi: 10.3808/jei.202300489. [COBISS.SI-ID 154495235]

KOCIJAN, Juš, HVALA, Nadja, PERNE, Matija, MLAKAR, Primož, GRAŠIČ, Boštjan, BOŽNAR, Marija. Surrogate modelling for the forecast of Seveso-type atmospheric pollutant dispersion. Stochastic environmental research and risk assessment, ISSN 1436-3240, 2023, vol. 37, no. 1, str. 275-290, doi: 10.1007/s00477-022-02288-x. [COBISS.SI-ID 137786371]

KOCIJAN, Juš, PERNE, Matija, GRAŠIČ, Boštjan, BOŽNAR, Marija, MLAKAR, Primož. Sparse and hybrid modelling of relative humidity : the Krško basin case study. CAAI transactions on intelligence technology, ISSN 2468-2322, 2020, vol. 5, no. 1, str. 42-48, doi: 10.1049/trit.2019.0054. [COBISS.SI-ID 33253415]

KOCIJAN, Juš, PERNE, Matija, MLAKAR, Primož, GRAŠIČ, Boštjan, BOŽNAR, Marija. Hybrid model of the near-ground temperature profile. Stochastic environmental research and risk assessment, ISSN 1436-3240, 2019, vol. 33, no. 11/12, str. 2019-2032, doi: 10.1007/s00477-019-01736-5. [COBISS.SI-ID 32875815]

KOCIJAN, Juš, GRADIŠAR, Dejan, STEPANČIČ, Martin, BOŽNAR, Marija, GRAŠIČ, Boštjan, MLAKAR, Primož. Selection of the data time interval for the prediction of maximum ozone concentrations. Stochastic environmental research and risk assessment, ISSN 1436-3240, 2018, vol. 32, no. 6, str. 1759-1770, doi: 10.1007/s00477-017-1468-y. [COBISS.SI-ID 31210023]

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]