Process simulation and control
This course is part of the programme:
Master’s study programme Environment (2nd level)
Objectives and competences
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,
- 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, and supervisory-control software.
Required prerequisite knowledge of mathematics, physics, and computer science on a Bachelor’s level.
Content (Syllabus outline)
1. Introduction to system theory
- Introduction to the course, to systems and system theory
- Principles of control (open-loop, disturbance compensation, closed-loop)
2. Modelling and computer simulation of dynamic systems
- Mathematical modelling, transfer function, modelling case studies
- Case studies of modelling and computer simulation
- Block diagrams
- System identification with step response
3. Control-systems design
- Systems presenation
- Analysis of control systems in time domain
- Basic industrial control algorithms
- Continuous PID controller design
- Examples of control systems
- Multi-loop control systems
4. Higher control levels
- Production level, process level
- Process level, SCADA.
Intended learning outcomes
Knowledge and understanding:
Introduction to control system and general control principles are mastered first. The main part of the course is devoted to basic methods, tools and elements so that students are able to design simple control systems. In this framework students obtain basic knowledge of mathematical modelling and computer simulation, various control-design methods, implementation of control functions, computer-aided control-system design, and supervisory-control software.
- Multiple authors (1998): Celostni pristop k računalniškemu vodenju procesov, ed. S. Strmčnik, Založba Fakultete za elektrotehniko, Ljubljana.
- J. Kocijan (1996): Načrtovanje vodenja dinamičnih sistemov, Zbirka nalog, Založba FE in FRI, Ljubljana.
*J. Kocijan (2012): Uvod v avtomatsko vodenje, spletni učbenik, Nova Gorica.
- B. Zupančič (1996): Zvezni regulacijski sistemi – 1. del, 2. izdaja, Založba FE in FRI, Ljubljana.
- B. Zupančič (2011): Avtomatsko vodenje sistemov, Založba FE in FRI, 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.
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]
PETELIN, Dejan, KOCIJAN, Juš, GRANCHAROVA, Alexandra. On-line Gaussian process model for the prediction of the ozone concentration in the air. Dokl. B’'lg. akad. nauk., 2011, vol. 64, no. 1, str. 117-124. [COBISS.SI-ID 24443431]
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]
KOCIJAN, Juš, GRANCHAROVA, Alexandra. Gaussian process modelling case study with multiple outputs. Dokl. B’'lg. akad. nauk., 2010, vol. 63, no. 4, str. 601-607. [COBISS.SI-ID 23605799]
AŽMAN, Kristjan, KOCIJAN, Juš. Fixed-structure Gaussian process model. Int. J. Syst. Sci., 2009, vol. 40, no. 12, str. 1253-1262. [COBISS.SI-ID 23224615]
GRANCHAROVA, Alexandra, KOCIJAN, Juš, JOHANSEN, Tor Arne. Explicit stochastic predictive control of combustion plants based on Gaussian process models. Automatica (Oxf.). [Print ed.], 2008, vol. 44, no. 6, str. 1621-1631. [COBISS.SI-ID 21753383]
KOCIJAN, Juš, LIKAR, Bojan. Gas-liquid separator modelling and simulation with Gaussian process models. Simulation modelling practice and theory, 2008, vol. 16, no. 18, str. 910-922. [COBISS.SI-ID 21909543]
LIKAR, Bojan, KOCIJAN, Juš. Predictive control of a gas-liquid separation plant based on a Gaussian process model. Comput. chem. eng.. [Print ed.], 2007, vol. 31, no. 3, str. 142-152. [COBISS.SI-ID 20419367]
AŽMAN, Kristjan, KOCIJAN, Juš. Application of Gaussian processes for black-box modelling of biosystems. ISA trans., 2007, vol. 46, no. 4, str. 443-457. [COBISS.SI-ID 20962087]
University course code: 2OK031
Year of study: 1
- Lectures: 30 hours
- Exercises: 15 hours
- Individual work: 135 hours
Course type: elective
Languages: slovene and english
Learning and teaching methods:
• lectures • tutorials with calculation examples of control-systems analysis and design • exercises with computer software for dynamic-systems simulation • demonstrations of control systems on test rigs. • solving calculation-based excercises individually at home and the presentation of obtained results to other students