Course detail

Intelligent Systems

FIT-SINAcad. year: 2026/2027

Intelligent and distributed control systems and their applications. Process control principles and real-time systems. Industrial control system architectures: PLC, DCS, HMI, and SCADA. Industrial communication, interoperability, and cyber-physical systems. IoT, edge, and cloud computing in control. Modeling and model-based system development. PLC programming (IEC 61131-3) and distributed control (IEC 61499). Hierarchical, decentralized, agent-based, and reconfigurable systems. Supervisory and intelligent control using rule-based, fuzzy, neural, adaptive, and learning methods. Applications in smart buildings, transportation systems, and autonomous systems.

Language of instruction

Czech

Number of ECTS credits

5

Assignment to study programme types

Master's

Mode of study

Not applicable.

Guarantor

doc. Ing. Vladimír Janoušek, Ph.D.

Department

Department of Intelligent Systems (UITS)

Entry knowledge

  • Fundamentals of systems theory and simulation. Basic knowledge of programming.
  • Students may utilize additional knowledge in areas such as control systems, embedded systems, computer networks, artificial intelligence, robotics, or other specializations when carrying out their individual projects; however, this is not a mandatory prerequisite for the course.

Rules for evaluation and completion of the course

  • Individual project
  • Project presentation
  • To pass the exam, at least 30 points is required.

Aims

  • The course aims to familiarize students with the principles, architectures, and design methods of intelligent and distributed control systems.
  • Students will acquire the ability to analyze and design control system architectures, appropriately allocate control, communication, supervisory, and intelligent functions among system components, and select suitable tools for modeling, implementation, and communication.
  • Students will gain an understanding of the relationships between classical process control, PLCs and industrial automation, distributed and cyber-physical systems, IoT/edge/cloud technologies, and intelligent control methods.
  • Practical experience in the design, integration, and experimental verification of a distributed system will be gained through working on a project.
  • The course is suitable for students of all specializations taught at FIT.

Study aids

Prerequisites and corequisites

Not applicable.

Basic literature

BRAMBILLA, Marco; CABOT, Jordi; WIMMER, Manuel. Model-Driven Software Engineering in Practice. 2nd ed. Springer, 2017. https://link.springer.com/book/10.1007/978-3-031-02549-5 
DAVID, René; ALLA, Hassane. Discrete, Continuous, and Hybrid Petri Nets. 2nd ed. Springer, 2010. https://link.springer.com/book/10.1007/978-3-642-10669-9
KOPETZ, Hermann; STEINER, Wilfried. Real-Time Systems: Design Principles for Distributed Embedded Applications. 3rd ed. Springer, 2022. https://link.springer.com/book/10.1007/978-3-031-11992-7 
ÅSTRÖM, Karl J.; MURRAY, Richard M. Feedback Systems: An Introduction for Scientists and Engineers. 2nd ed. Princeton University Press, 2021. https://fbsbook.org/ 
ZEIGLER, Bernard P.; MUZY, Alexandre;KOFMAN, Ernesto. Theory of Modeling and Simulation: Discrete Event & Iterative System Computational Foundations. 3rd ed. Academic Press / Elsevier, 2018. https://shop.elsevier.com/books/theory-of-modeling-and-simulation/zeigler/978-0-12-813370-5 
ZOITL, Alois; LEWIS, Robert. Modelling Control Systems Using IEC 61499. 2nd ed. The Institution of Engineering and Technology, 2014. https://shop.theiet.org/model-cont-syst-iec-61499-2nd 

Recommended reading

Not applicable.

Classification of course in study plans

  • Programme MITAI Master's

    specialization NHPC , 0 year of study, winter semester, elective
    specialization NVER , 0 year of study, winter semester, elective
    specialization NIDE , 0 year of study, winter semester, elective
    specialization NISY , 2 year of study, winter semester, compulsory, profile core courses
    specialization NSPE , 0 year of study, winter semester, elective
    specialization NEMB , 0 year of study, winter semester, elective
    specialization NBIO , 0 year of study, winter semester, elective
    specialization NSEN , 0 year of study, winter semester, elective
    specialization NVIZ , 0 year of study, winter semester, elective
    specialization NGRI , 0 year of study, winter semester, elective
    specialization NADE , 0 year of study, winter semester, elective
    specialization NISD , 0 year of study, winter semester, elective
    specialization NMAT , 0 year of study, winter semester, elective
    specialization NSEC , 0 year of study, winter semester, elective
    specialization NNET , 0 year of study, winter semester, elective
    specialization NMAL , 0 year of study, winter semester, elective
    specialization NCPS , 0 year of study, winter semester, elective

Type of course unit

 

Lecture

26 hours, optionally

Teacher / Lecturer

doc. Ing. Vladimír Janoušek, Ph.D.

Syllabus

  1. Introduction – Intelligent and distributed control systems, applications, Industry 4.0.
  2. Basic principles of process control. 
  3. Control system architectures: PLC, DCS, HMI, SCADA.
  4. Industrial Communication, Interoperability, and CPS.
  5. IoT, edge and cloud computing in control. MQTT, Node-RED, and Home Assistant.
  6. Methods and tools for model-based system development.
  7. PLC programming according to IEC 61131-3.
  8. Distributed control and IEC 61499.
  9. Hierarchical and reconfigurable systems, agent-based control.
  10. Supervisory and intelligent layer – rule-based, neural, adaptive, and learning systems.
  11. Intelligent buildings, BAS technologies.
  12. Smart cities and intelligent transportation.
  13. Autonomous and robotic systems.

Project

26 hours, compulsory

Teacher / Lecturer

doc. Ing. Vladimír Janoušek, Ph.D.

Syllabus

  • An individual project focused on the design and implementation of an intelligent or distributed control system, a reusable component, or—by agreement—a new topic for the SIN course.
  • The project typically involves the interconnection of multiple components, a defined communication interface, a simulated or physical process, and experimental verification of the solution.
  • Application areas may include, for example, industrial automation, IoT and edge computing, smart buildings, transportation, robotics, or smart manufacturing.
  • Detailed project options and technical requirements are provided in the course study materials.