Subject Datasheet
Download PDFBudapest University of Technology and Economics | |
Faculty of Transportation Engineering and Vehicle Engineering |
1. Subject name | Control theory | ||||
2. Subject name in Hungarian | Irányításelmélet | ||||
3. Code | BMEKOKAM142 | 4. Evaluation type | exam grade | 5. Credits | 3 |
6. Weekly contact hours | 2 (9) Lecture | 1 (5) Practice | 0 (0) Lab | ||
7. Curriculum | Vehicle Engineering MSc (J) Transportation Engineering MSc (K) |
8. Role | Mandatory (mc) at Vehicle Engineering MSc (J) Mandatory (mc) at Transportation Engineering MSc (K) |
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9. Working hours for fulfilling the requirements of the subject | 90 | ||||
Contact hours | 42 | Preparation for seminars | 8 | Homework | 0 |
Reading written materials | 13 | Midterm preparation | 12 | Exam preparation | 15 |
10. Department | Department of Control for Transportation and Vehicle Systems | ||||
11. Responsible lecturer | Dr. Gáspár Péter | ||||
12. Lecturers | Dr. Gáspár Péter | ||||
13. Prerequisites | |||||
14. Description of lectures | |||||
Introduction. Recap on the basic concepts of control theory and stability theory (stability conditions, stability of closed loop systems). State space theory (state space representations and properties, transformations). Continuous state space of linear time-variant dynamic systems. Control in state space. State feedback design. Optimal controls. Linear Quadratic Controller Design (LQR). Computer controlled systems. Designing discrete controls. Observability, controllability properties. Stability. State estimation. Kalman filtering. Problems from different means of transport :road, air, logistics. Presentation of design tasks through vehicle, transport and logistic examples. Computer-oriented control theory tasks. Outlook (introductory, problematic). Postmodern techniques. Predictive controls. Error detection and importance in transport. MIMO systems. Nonlinear systems. |
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15. Description of practices | |||||
Implementation of the methods learned during the lectures | |||||
16. Description of labortory practices | |||||
17. Learning outcomes | |||||
A. Knowledge
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18. Requirements, way to determine a grade (obtain a signature) | |||||
Two midsemester exams, min. 70% presence on lectures and seminars, which are the prerequisite of the final exam. The final grade depends only on the final exam. | |||||
19. Opportunity for repeat/retake and delayed completion | |||||
Both midsemester exams can be retried once. | |||||
20. Learning materials | |||||
Lecture Notes, Kailath: Linear Systems, Prentice Hall | |||||
Effective date | 10 October 2019 | This Subject Datasheet is valid for | Inactive courses |