Goals of this program are to educate most qualified specialists for research and scientific development as well.

Graduates have outstanding knowledge in special area, determined by his/her PhD. project.
Special orientation is given by thesis;graduates are qualified for high positions in all branch.
Leader of research team,managers in industry.

The graduate of the subject field obtains broad knowledge of subject of cybernetics control and/or measuremet. The knowledge is build mainly on theoretical background of the subject. Moreover the graduate will obtain deep special knowledge aimed in direction of his/her thesis. The graduate will be able to perform scientific and/or applied research based on up to date theoretical knowledge. The graduate will be able to organize and lead a team of researchers in the studied subject.

prof. Ing. Pavel Václavek, Ph.D.

1. Adaptation in neural- fuzzy systems.

   Application of infinitely differentiable functions with a finite and compact support as membership functions in neuro-fuzzy systems. Tha aim is comparison results of adaptation (rate of convergence, stability etc.) using these functions with standard membership functions for example Gauss.

   Tutor: Jura Pavel, prof. Ing., CSc.

2. Adaptive and optimal controlers with artificial intelligence principle

   Discrette identifications and adaptive optimal control systems with classical and artificial principles.

   Tutor: Pivoňka Petr, prof. Ing., CSc.

3. Cooperative Exploration Using Heterogeneous Mobile Robots

   Design and develop a group of mobile heterogeneous robots for cooperative exploration of a given area. Propose appropriate algorithms and evaluate them.

   Tutor: Žalud Luděk, prof. Ing., Ph.D.

4. Cooperative Exploration Using Heterogeneous Mobile Robots

   Design and develop a group of mobile heterogeneous robots for cooperative exploration of a given area. Propose appropriate algorithms and evaluate them.

   Tutor: Žalud Luděk, prof. Ing., Ph.D.

5. Inertial Sensors Calibration

   The topic deals with design of the inertial sensors calibration.

   Tutor: Beneš Petr, doc. Ing., Ph.D.

6. Modelling of Shape Memory Alloys

   Make scientific digest of shape memory alloys. Compose a model of shape memory alloy behaviour and evaluate it. Propose a model of hysteresis of these materials.

   Tutor: Žalud Luděk, prof. Ing., Ph.D.

7. Non contact diagnostics circuit boards

   Analysis of principles and sensors (probes) available for non-contact diagnostic patterns (wiring) PCB. Comparison and evaluation, particularly for current measurement.

   Tutor: Bejček Ludvík, doc. Ing., CSc.

8. Non contact diagnostics (thermal imagers)

   Using thermography display units (thermal imager) for contactless diagnostics with a focus on new and unusual methods, in particular in industrial practice

   Tutor: Bejček Ludvík, doc. Ing., CSc.

9. Orthogonal systems functions and its application at a dynamic systems identification

   The aim of the task is application of orthogonal systems functions (namely Laguerre) at the dynamic systems identification. The method is based on the Laguerre transform of an input and output time signal. The Laguerre orthogonal series are transformed using Laplace transform. Their ratio determines the tranfer function of the system.

   Tutor: Jura Pavel, prof. Ing., CSc.

10. Power Harvesting

    Selfgenerating sensors and micropower electronics for power harvesting application.

    Tutor: Beneš Petr, doc. Ing., Ph.D.

11. Robust control of electrical drives

    The aim of this work is to analyze the robustness of existing algorithms for electrical drives control and robustness analysis of flux and speed estimators. Based on realized analysis the robust controller synthesis with specified allowed parameter changes will follow.

    Tutor: Blaha Petr, doc. Ing., Ph.D.

12. The analysis of digital image components with using neural networks

    Nowadays, the problematic of pattern recognition in digital image is part of many automatic and semiautomatic systems. Although exploratory studies show very good results, the credibility and accurancy of this methodology is in use lowered by the influence of external disturbing factors. One of many alternatives is using of artificial neural networks as a classifier. Its robustness and ability of generalization based on incomplete data is in this point of view very perspective for application in sphere of image analysis.

    Tutor: Jirsík Václav, doc. Ing., CSc.

13. Using of Computer Vision for Augmented Reality in Technical Applications

    Work is focused on using of image processing and computer vision technics for augmented reality tasks. Appliacations with technical character are postulated (robots navigation, products completion, building industry, construction, electrotechnics etc.).

    Tutor: Janáková Ilona, Ing., Ph.D.

14. Using of Computer Vision for Augmented Reality in Technical Applications

    Work is focused on using of image processing and computer vision technics for augmented reality tasks. Appliacations with technical character are postulated (robots navigation, products completion, building industry, construction, electrotechnics etc.).

    Tutor: Janáková Ilona, Ing., Ph.D.