SubjectsSubjects(version: 965)
Course, academic year 2019/2020
  
Predictive Control - M445019
Title: Prediktivní řízení
Guaranteed by: Department of Computing and Control Engineering (445)
Faculty: Faculty of Chemical Engineering
Actual: from 2019 to 2020
Semester: summer
Points: summer s.:5
E-Credits: summer s.:5
Examination process: summer s.:
Hours per week, examination: summer s.:2/2, C+Ex [HT]
Capacity: unlimited / unlimited (unknown)
Min. number of students: unlimited
State of the course: taught
Language: Czech
Teaching methods: full-time
Level:  
Note: course can be enrolled in outside the study plan
enabled for web enrollment
Guarantor: Mareš Jan prof. Ing. Ph.D.
Hrnčiřík Pavel doc. Ing. Ph.D.
Interchangeability : N445085
Examination dates   Schedule   
This subject contains the following additional online materials
Annotation -
Predictive control is a course which summarises advanced control techniques. Continuous or discrete mathematical model is the basics for all these methods. Introduction to diofantic equatoins is ana essential part of the lectures. The course contains also application examples in order for the students to apply the acquired knowledge to the solution of engineering problems.
Last update: Pátková Vlasta (20.04.2018)
Course completion requirements - Czech

Vypracování a obhajoba sedmi ročníkových projektů: 0 - 25 bodů

Ústní zkouška: 0-75 bodů

Celkové bodové hodnocení: 100-90 A, 89-80 B, 79-70 C, 69-60 D, 59-50 E, méně než 50 F.

Last update: Mareš Jan (03.10.2023)
Literature -

R: Mareš, J. Hrnčiřík, P., Základy prediktivního řízení, VŠCHT Praha, 2012, 9788070808238

A: Balátě, J. Automatické řízení, BEN, Praha, 2004, 8073001489

Last update: Mareš Jan (03.10.2023)
Requirements to the exam - Czech

ústní zkouška

Last update: Mareš Jan (04.10.2023)
Syllabus -

1) Continuous and discrete domain, difference equations, Z-transform.

2) Stability in discrete domain, delta models, discrete PID, IMC controller.

3) State space description.

4) Nonlinear and MIMO systems.

5) Adaptive control techniques.

6) Standard form of predictive control. Cost function, prediction model

7) Prediction model derivation

8) Numerical solution of control law.

9) Application example I

10) MATLAB Multi Parametric Toolbox.

11) Predictive control of MIMO systems.

12) Predictive control of nonlinear systems.

13) Application example II.

14) Application example III.

Last update: Pátková Vlasta (20.04.2018)
Learning resources -

https://www.honeywellprocess.com/en-us/explore/products

Last update: Pátková Vlasta (20.04.2018)
Learning outcomes -

Students will be able to:

  • use advanced and predictive control techniques (Pole Placement, Predictive Functional Control, Model Predictive Control)
  • Use optimization algorithms (linear programming, quadratic programming)
Last update: Pátková Vlasta (20.04.2018)
Registration requirements -

Mathematics I, Control theory

Last update: Pátková Vlasta (20.04.2018)
Teaching methods
Activity Credits Hours
Účast na přednáškách 1 28
Práce na individuálním projektu 1 28
Příprava na zkoušku a její absolvování 2 56
Účast na seminářích 1 28
5 / 5 140 / 140
Coursework assessment
Form Significance
Regular attendance 20
Report from individual projects 20
Continuous assessment of study performance and course -credit tests 20
Oral examination 40

 
VŠCHT Praha