Přístupnostní navigace
E-application
Search Search Close
Branch Details
Original title in Czech: Kybernetika, automatizace a měřeníFEKTAbbreviation: PP-KAMAcad. year: 2013/2014
Programme: Electrical Engineering and Communication
Length of Study: 4 years
Profile
Goals of this program are to educate most qualified specialists for research and scientific development as well.
Key learning outcomes
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.
Occupational profiles of graduates with examples
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.
Guarantor
prof. Ing. Pavel Václavek, Ph.D.
Issued topics of Doctoral Study Program
Bayesian statics a comprehensive conclusion creates statistics on the nature of the search parameters, their distribution and the degree of confidence in the validity of the found solution. Quantitative description of the random variables it uses subjective a priori probability density correction by objective data. By its very nature it is a suitable math resource for solving the General tasks of filtration and estimation, as it allows folding information from many sources. Because the real industrial processes are characterized by the uncertainty of its parameters with the absence of knowledge of the time model changes, the behaviour of the process and generally non-linear dependence of the parameters on the output of the process, the task is to find the best parameters greatly complicated, moreover, often subject to indirect, imprecise and uncertain. The aim of this work is to develop and implement the Bayesian filter is able to locate unbiased estimate for processes where the normal distribution is loaded with information on quantified A/D converter. The filter must compensate for the absence of certainty, and inaccuracies in the model in the form of forgetting, which is interpreted as a statistical decision problem using Kullback-Leibler information.
Tutor: Pivoňka Petr, prof. Ing., CSc.
Design, create and verify data processing algorithms of proximity optical 3D scanner for augmented reality in telepresence mobile robotics. The aim is to create a practically usable system that allows to combine data of stereo-vision pair of color CCD cameras with 3D scanner data, so that the operator was informed of the traffic flow field around the robot. It is therefore expected not only to calculate the cross-country mobility, but also the spatial and holonomic constraints of the used chassis or local path planning. The entire system must be able to work in real time, including the visualization for the operator.
Tutor: Jirsík Václav, doc. Ing., CSc.
The topic is aimed to discrete time non-linear systems analysis. Attention will be paid especially to the problem of nonlinear systems discretization. Discrete time nonlinear systems state observability will be also studied. The research results will be applied in the field of AC drives models.
Tutor: Václavek Pavel, prof. Ing., Ph.D.
The topic is aimed to the research of the methods and algorithms for non-contact localization and characterization of sound and vibration sources. Issues related especially with analysis of the sources with near-field acoustic holography method using microphone array will be studied with respect to its applicability for localization in confined space with reflections and other noise sources and also to increase the prediction accuracy with data fusion from other spatial measurement systems. In addition to the theoretical work, practical implementation of these methods and optimization of calculation algorithms for use in the field of non-contact vibrodiagnostics and localization of noise sources in mechanical systems will be carried out.
Tutor: Beneš Petr, doc. Ing., Ph.D.
The topic is aimed on testing and calibration of the vibration sensors and angular rate sensors for inertial motion units. The objectives of the thesis consist of the analysis of parasitic effects, which affect the overall measurement uncertainty, and the search for new methods for their suppression. There will be available calibration system SPEKTRA CS18 and Dynamic Motion Simulator RMS SDL05 for the research. The topic is going to be supported by Honeywell HTS CZ.
The topic deals with reduction of feature space in supervised learning. To achieve the data reduction efficiently (time and quality demands), filter feature selection (FFS) methods are commonly used. The research will be focused on conditional FFS methods, feature decomposition and cluster analysis. The aim of the thesis is to suggest an original conditional FFS method based on iterative feature decomposition but supporting dichotomous output variable and enabling to combine more criterion functions together.
Tutor: Honzík Petr, Ing., Ph.D.
The first task of this work is to develop models of multiphase and multiplex windings AC drives with the possibility to simulate common faults in these devices. Next part of the work will be oriented to algorithms which enables to monitor these faults firstly with the help of commonly used sensors (phase currents, DC bus voltage, rotor position) and secondly with the help of redundant sensors so as to reach higher reliability of the drive. The goal of the last stage is to design control algorithms which will guarantee partial functionality under the fault conditions.
Tutor: Blaha Petr, doc. Ing., Ph.D.
The topic is aimed on the research of non-linear systems state estimators and their implementation in industry-used hardware. Both theoretical work on the algorithms for AC drives state estimation and their computational optimization for practical use is included in the topic. The developed algorithms will be used for sensorless control and monitoring (fault detection) of drives based on AC induction machine and permanent magnet synchronous machine.
Design, develop and verify methods for creating spatial maps using planar or 3D proximity scanners, thermal cameras and CCD color cameras. The aim is to create a map on the basis of the occupancy grid, which would include also the spatial data information on temperature and color of the object. The project includes the calibration of individual sensors and mutual calibration of the sensors. Algorithms should be independent of the types of sensors. Assumed to be used in mobile robotics for creating advanced environment maps and biomedicine for patient body parts scanning.
Tutor: Žalud Luděk, prof. Ing., Ph.D.