Course detail

Intelligent Systems

FIT-SINAcad. year: 2021/2022

Intelligent control systems. Hierarchical control, holonic and agent systems. Communication infrastructure for home automation and industrial automation. PLC, application of soft computing. Communication of subsystems within IoT. SCADA. Distributed control systems. Smart Buildings and Smart Home. Smart Cities and intelligent transport.

Language of instruction

Czech

Number of ECTS credits

5

Mode of study

Not applicable.

Learning outcomes of the course unit

Ability to model and design intelligent (smart) systems and their control using current methods and technologies.
Students acquire knowledge of principles, architectures and design of smart systems of various kinds using current technologies.

Prerequisites

Basics of systems theory, simulation.
Students can use any other special knowledge to implement an individual project.

Co-requisites

Not applicable.

Planned learning activities and teaching methods

Not applicable.

Assesment methods and criteria linked to learning outcomes

  • Individual project
  • Project presentation

Course curriculum

Not applicable.

Work placements

Not applicable.

Aims

To acquaint students with principles, architectures, and methods of design of intelligent control systems.
The course is suitable for students of all specializations taught at FIT.

Specification of controlled education, way of implementation and compensation for absences

Not applicable.

Recommended optional programme components

Not applicable.

Prerequisites and corequisites

Not applicable.

Basic literature

Not applicable.

Recommended reading

Automatizace. http://www.automatizace.cz/
Cassandras, C. G.,  Lafortune, S.: Introduction to discrete event systems, Springer, 2008.
David, R., Alla, H.: Petri Nets and Grafcet: Tools for Modelling Discrete Event Systems, Prentice Hall, 1992, ISBN-10: 013327537X, ISBN-13: 978-0133275377,
Mehta, B.R., Reddy, Y.J.: Industrial Process Automation Systems: Design and Implementation, Elsevier, 2015, ISBN 978-0-12-800939-0
Přibyl, P., Svítek, M.: Inteligentní dopravní systémy, Nakladatelství BEN, Praha 2001, ISBN 80-7300-029-6
Russel, S., Norvig, P.: Artificial Intelligence, a Modern Approach, Pearson Education Inc., 2003, ISBN 0-13-080302-2
Valeš, M.: Inteligentní dům. Brno, Vydavatelství ERA, 2006.
Zeigler, B.P.: Theory of Modeling and Simulation, Academic Press; 2 edition (March 15, 2000), ISBN 978-0127784557

Classification of course in study plans

  • Programme IT-MSC-2 Master's

    branch MBI , 0 year of study, winter semester, compulsory-optional
    branch MBS , 0 year of study, winter semester, elective
    branch MGM , 0 year of study, winter semester, compulsory-optional
    branch MIN , 2 year of study, winter semester, compulsory
    branch MIS , 0 year of study, winter semester, compulsory-optional
    branch MMM , 0 year of study, winter semester, elective
    branch MPV , 0 year of study, winter semester, compulsory-optional
    branch MSK , 2 year of study, winter semester, compulsory-optional

  • Programme MITAI Master's

    specialization NADE , 0 year of study, winter semester, elective
    specialization NBIO , 0 year of study, winter semester, elective
    specialization NCPS , 0 year of study, winter semester, elective
    specialization NEMB , 0 year of study, winter semester, elective
    specialization NGRI , 0 year of study, winter semester, elective
    specialization NHPC , 0 year of study, winter semester, elective
    specialization NIDE , 0 year of study, winter semester, elective
    specialization NISD , 0 year of study, winter semester, elective
    specialization NMAL , 0 year of study, winter semester, elective
    specialization NMAT , 0 year of study, winter semester, elective
    specialization NNET , 0 year of study, winter semester, elective
    specialization NSEC , 0 year of study, winter semester, elective
    specialization NSEN , 0 year of study, winter semester, elective
    specialization NSPE , 0 year of study, winter semester, elective
    specialization NVER , 0 year of study, winter semester, elective
    specialization NVIZ , 0 year of study, winter semester, elective
    specialization NISY up to 2020/21 , 2 year of study, winter semester, compulsory
    specialization NISY , 2 year of study, winter semester, compulsory

Type of course unit

 

Lecture

26 hod., optionally

Teacher / Lecturer

Syllabus

  1. Introduction. Intelligent and distributed control systems and applications.
  2. Systems and models. Hierarchical control, holonic and agent systems, CPS.
  3. Elements and architectures of intelligent and distributed control systems, PLC, SCADA, DCS, IoT.
  4. Communication infrastructure for home automation and industrial automation.
  5. Communication of subsystems within IIOT, MQTT.
  6. Distributed control systems (DCS). Modeling and programming DCS, IEC61499.
  7. Programming DCS, Distributed Node-Red, ROS.
  8. Application of soft computing in control systems - fuzzy control and reinforcement learning. 
  9. Reconfigurable and agent-based control systems.
  10. Smart Buildings and Smart Home.
  11. Smart cities and intelligent transport.
  12. Case study.
  13. Summary, conclusion.

Project

26 hod., compulsory

Teacher / Lecturer

Syllabus

  • Individual project - implementation of distributed intelligent control in a simulated environment. The application area can be Smart Home, Transportation Systems Telematics, Smart Manufacturing, etc.