Selected Chaps From Automatic Control
FEKT-DPA-AM1Acad. year: 2022/2023
The subject focuses at studies of the methods of design of advanced control algorithms including classical control structures as well as algorithms of robust, adaptive and predictive control. Attention is also paid to information processing algorithms and state observers for realization of so called virtual sensors and algorithms of sensorless control. Traditional methods for systems control and processing information are complemented by artificial intelligence-based approaches. In addition to the theoretical aspects of the given topic, sample algorithms for advanced drives, mechatronic systems and mobile robots are also solved.
Learning outcomes of the course unit
Recommended optional programme components
Slotine J. J. E., Li W.: Applied Nonlinear Control, Prentice-Hall, 1991 (EN)
Gu D.-W., Petkov P. H.: Robust Control Design with MATLAB, Springer, 2013 (EN)
Russell S., Norvig P.: Artificial Intelligence a Modern Approach. Prentice Hall 2010 (EN)
Voseelman G., Mass H-G. Airborne and Terrestrial Laser Scanning, CRC Press, 2010 (EN)
Goodwin G.C., Seron M.M. , Doná J.A. Constrained Control and Estimation, Springer, 2005 (EN)
Hermann R. ,Krener A., Nonlinear controllability and observability, IEEE Transactions on Automatic Control, vol. 22, no. 5, pp. 728–740, 1977 (EN)
Planned learning activities and teaching methods
Assesment methods and criteria linked to learning outcomes
Language of instruction
2. Robust control of dynamic systems with uncertainty considerations
3. Specific Adaptive Control Problems
4. State controller as the basic structure for model based predictive control
5. State observability theory of nonlinear dynamic systems
6. Principles of using virtual sensors for sensorless control, example of control applications for actuators with asynchronous and synchronous motors
7. Artificial neural networks (NS) and their learning methods.
8. Control theory and artificial intelligence, NS-based control algorithms.
9. Identification of systems using NS, adaptive optimal controller based on NS identification.
10. Modern methods of autonomous outdoor and indoor self-localisation.
11-12. Advanced 3D mapping - sensors, data fusion methods, data representation, practical use.
Classification of course in study plans
- Programme DPA-KAM Doctoral, any year of study, winter semester, 4 credits, compulsory
- Programme DPA-EKT Doctoral, any year of study, winter semester, 4 credits, compulsory-optional
- Programme DPA-MET Doctoral, any year of study, winter semester, 4 credits, compulsory-optional
- Programme DPA-SEE Doctoral, any year of study, winter semester, 4 credits, compulsory-optional
- Programme DPA-TLI Doctoral, any year of study, winter semester, 4 credits, compulsory-optional
- Programme DPA-TEE Doctoral, any year of study, winter semester, 4 credits, compulsory-optional
Type of course unit
Teacher / Lecturer