SubjectsSubjects(version: 863)
Course, academic year 2019/2020
  
Advanced Control Engineering - AP445010
Title: Advanced Control Engineering
Guaranteed by: Department of Computing and Control Engineering (445)
Actual: from 2019
Semester: both
Points: 0
E-Credits: 0
Examination process:
Hours per week, examination: 3/0 other [hours/week]
Capacity: winter:unknown / unknown (unknown)
summer:unknown / unknown (unknown)
Min. number of students: unlimited
Language: English
Teaching methods: full-time
Level:  
For type: doctoral
Note: course is intended for doctoral students only
can be fulfilled in the future
you can enroll for the course in winter and in summer semester
Guarantor: Hrnčiřík Pavel doc. Ing. Ph.D.
Mareš Jan doc. Ing. Ph.D.
Interchangeability : D445023, P445010
Annotation -
Last update: Pátková Vlasta (19.11.2018)
The course deals with advanced process control methodology: (i) adaptive control, (ii) advanced predictive control, (iii) expert systems. Soft skills training is an integral part of the course. Students have to prepare a draft of scientific paper and have to defend their projects.
Aim of the course -
Last update: Pátková Vlasta (19.11.2018)

Students will be able to:

use advanced predictive control and nonlinear predictive control of technological process

use artificial intelligence for modelling and control

Literature -
Last update: Pátková Vlasta (19.11.2018)

Z: CAMACHO, E.F., BORDONS, C. Model Predictive Control. London : Springer-Verlag London Limited, 2007. 978-1-85233-694-3

Z: MACIEJOWSKI, J. M. Predictive Control with Constraints. Harlow (UK) : Prentice Hall, 2002. ISBN 0-201-39823-0.

D: BAOTIC, M., CHRISTOPHERSEN, F. J.,MORARI, M. Constrained Optimal Control of Hybrid Systems With a Linear Performance Index. IEEETrans. on Automatic Control, 51(12):1903-1919, December 2006.

Learning resources -
Last update: Pátková Vlasta (19.11.2018)

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

Teaching methods -
Last update: Pátková Vlasta (19.11.2018)

lectures, project and solving of case stidies

Requirements to the exam -
Last update: Pátková Vlasta (19.11.2018)

3 individual projects: 0 - 25 bodů

Oral exam: 0-75 bodů

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

Syllabus -
Last update: Pátková Vlasta (19.11.2018)

1. Adaptive methods of proces control in chemistry

2. State estimation

3. Advanced predictive control in technological praxis

4. Piece wise affine predictive control

5. Nonlinear predictive control

6. Case study: Nonlinear predictive control

7. Artificial intelligence in proces control

8. Fuzzy systems in prcess control

9. Expert systems in proces control

10. Expert systems in bioproces control

11. Case study: Bioprocess control

Entry requirements -
Last update: Pátková Vlasta (19.11.2018)

none

Registration requirements -
Last update: Pátková Vlasta (19.11.2018)

none

Course completion requirements -
Last update: Pátková Vlasta (19.11.2018)

3 individual projects: 0 - 25 points

Oral exam: 0-75 points

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

 
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