Course unit code:
A422U3_4B
Course unit title:
Introduction to Optimal and Predictive control
Mode of delivery, planned learning activities and teaching methods:
lecture – 1 hour weekly (on-site method)
seminar – 1 hour weekly (on-site method)
Credits allocated:
2
Recommended semester:
Process Control – bachelor (full-time, attendance method), 6. semester
Level of study:
1.
Prerequisites for registration:
none
Assesment methods:
 
Learning outcomes of the course unit:
Students gained fundamental knowledge in the application of optimization in process control. Students learned to formulate the optimal control problem for various problems based on industrial practice, such as optimal control of pasteurization units, chemical reactors or fermenters. Students learned to define the objective function and constraints of the optimization problem. Students learned to implement optimal control problems in the Matlab environment.
Course contents:
Recommended or required reading:
Recommended:
  • MACIEJOWSKI, J M. Predictive Control with Constraints. Harlow : Prentice Hall, 2002. 331 s. ISBN 0-201-39823-0.
  • RAWLINGS, J B. – MAYNE, D Q. Model Predictive Control: Theory and design. Madison : Nob Hill Publishing, 2009. 533 s. ISBN 978-0-975-93770-9.
Language of instruction:
Slovak, English
Course supervisor:
doc. Ing. Michal Kvasnica, PhD.
Last modification:
15. 7. 2021

Department:
Department of Information Engineering and Process Control

AIS: 2021/2022  

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