- Course unit code:
- A422U3_4B
- Course unit title:
- Introduction to Optimal and Predictive control
- Mode of completion and Number of ECTS credits:
- Exm (2 credits)
- Course supervisor:
- prof. Ing. Michal Kvasnica, PhD.
- Name of lecturer(s):
- M. Kvasnica (2021/2022 – Winter)
- 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.
- Prerequisites for registration:
- none
- 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.
- Planned learning activities and teaching methods:
- Week 1-3: Optimization in process control (role of objective function, role of constraints, types of objective functions, types of constraints, advantages and disadvantages of optimization in process control, applications in continuous and discrete time) Week 4-7: Introduction of LQ control (basic concept of LQ control in industrial practice, implementation in Matlab / Simulink environment, continuous and discrete time control, simulation applications with models of chemical and food processes) Week 8-12: Introduction to predictive control (differences between LQ control and MPC control, types of objective functions, types of constraints, applications with linear models of chemical and food processes) Contact teaching: lectures 13h, exercises 13h Contactless teaching: preparation for exercises (12h), preparation of final project (12h)
- Assesment methods and criteria:
- Evaluation is based 50% on the work during the semester, 50% from final examination. The rating is based on the standard FCHPT scale.
- Language of instruction:
- Slovak, English
Institute of Information Engineering, Automation and Mathematics was established in 1.1.2006 from two departments: Department of Information Engineering and Process Control and Department of Mathematics.
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