Full-time study

4 years

prof. Ing. Pavel Václavek, Ph.D.

Chairman :
prof. Ing. Pavel Václavek, Ph.D.
Councillor internal :
doc. Ing. Zdeněk Bradáč, Ph.D.
prof. Ing. Pavel Jura, CSc.
doc. Ing. Petr Beneš, Ph.D.
doc. RNDr. Zdeněk Šmarda, CSc.
Councillor external :
prof. Ing. Pavel Ripka, CSc.
Prof. Ing. Roman Prokop, CSc.
doc. Ing. Eduard Janeček, CSc.
prof. Dr. Ing. Alexandr Štefek, Dr.
prof. Ing. Tomáš Vyhlídal, Ph.D.

The doctor study programme "Cybernetics, Control and Measurements" is devoted to the preparation of the high quality scientific and research specialists in various branches of control technology, measurement techniques, automatic systems, robotics, artificial intelligence and computer vision.
The aim is to provide the doctor education in all these particular branches to students educated in university magister study, to make deeper their theoretical knowledge, to give them also requisite special knowledge and practical skills and to teach them methods of scientific work.
Through a systematic and comprehensive view of management and measurement, graduates of the study program successfully apply to key management and managerial positions and functions in which they use system view, knowledge of system analysis and optimal management.

Graduate of doctoral studies is profiled to independent creative work and critical thinking based on the systemic view of both technical and non-technical systems and the world as a whole. The graduate program is equipped with the necessary knowledge of mathematics, physics, electrical engineering, theory and practice of control and regulation, measuring techniques, robotics, artificial intelligence, image processing and other fields of applied electrical engineering and informatics. One of the characteristic features of graduates is the ability to integrate a broad spectrum of knowledge and to create functional technical as well as organizational and economic systems.
All graduates of the doctoral program Cybernetics, Automation and Measurement demonstrate during their studies:
• mathematical, physical and electrotechnical principles relevant to measurement and control;
• electronic measuring systems, embedded systems, communication systems, control theory, automatic control systems and artificial intelligence;
• design and operation of electrotechnical, electronic, measuring, control and communication systems.
The graduates are well versed in modern technologies (Industry 4.0, Artificial Intelligence, Signal Processing, Computer Vision, Advanced Management Methods, Industrial Measurement and Control Systems, Mobile and Stationary Robotics, Communication Systems, Functional and System Security).
The graduates are trained to find the work in technical practice, creative work, research and development, production, management and managerial positions in technical or business firms and companies at the highest qualification levels.

Graduates will apply in particular:
- in research, development and design teams,
- in the field of professional activity in production or business organizations,
- in the academic sphere and in other institutions involved in science, research, development and innovation,
- in all areas of the company where cybernetic systems or cybernetic principles are being applied
Our graduates are particularly experienced in the analysis, design, creation or management of complex measurement or control systems, as well as in the programming, integration, support, maintenance or sale of these systems.

Doctoral studies are carried out according to the individual study plan, which is prepared by the supervisor in the beginning of the study in cooperation with the doctoral student. The individual curriculum specifies all the duties determined in accordance with the BUT Study and Examination Rules, which the doctoral student must fulfill to successfully finish his studies. These responsibilities are time-bound throughout the study period, they are scored and fixed at fixed deadlines.
Students will write and perform tests of obligatory subjects (Selected Chapters of Control Engineering, Selected Chapters of Measurement Techniques and Exam in English before the state doctoral examination), at least two compulsory elective courses in view of the focus of his dissertation, at least two optional subjects (English for PhD students; Quoting in Scientific Practice; Resolving Innovation Assignments; Scientific Publishing from A to Z).
The student may enroll for the state doctoral exam only after all the tests prescribed by his / her individual study plan have been completed. Before the state doctoral exam, the student draws up a dissertation thesis describing in detail the aims of the thesis, a thorough evaluation of the state of knowledge in the area of ​​the dissertation solved, or the characteristics of the methods it intends to apply in the solution.
The defense of the controversy that is opposed is part of the state doctoral exam. In the next part of the exam, the student must demonstrate deep theoretical and practical knowledge in the field of electrical engineering, control technology, cybernetics and measuring techniques. The state doctoral examination is in oral form and, in addition to the discussion on the dissertation thesis, it also consists of thematic areas related to compulsory and compulsory elective subjects.
To defend the dissertation, the student reports after the state doctoral examination and after fulfilling conditions for termination, such as participation in teaching, scientific and professional activity (creative activity) and at least a monthly study or work placement at a foreign institution or participation in an international creative project. The studies are finished by successful defence of the dissertation thesis.

The doctoral studies of a student follow the Individual Study Plan (ISP), which is defined by the supervisor and the student at the beginning of the study period. The ISP is obligatory for the student, and specifies all duties being consistent with the Study and Examination Rules of BUT, which the student must successfully fulfill by the end of the study period. The duties are distributed throughout the whole study period, scored by credits/points and checked in defined dates. The current point evaluation of all activities of the student is summarized in the “Total point rating of doctoral student” document and is part of the ISP. At the beginning of the next study year the supervisor highlights eventual changes in ISP. By October, 15 of each study year the student submits the printed and signed ISP to Science Department of the faculty to check and archive.
Within the first four semesters the student passes the exams of compulsory, optional-specialized and/or optional-general courses to fulfill the score limit in Study area, and concurrently the student significantly deals with the study and analysis of the knowledge specific for the field defined by the dissertation thesis theme and also continuously deals with publishing these observations and own results. In the follow-up semesters the student focuses already more to the research and development that is linked to the dissertation thesis topic and to publishing the reached results and compilation of the dissertation thesis.
By the end of the second year of studies the student passes the Doctor State Exam, where the student proves the wide overview and deep knowledge in the field linked to the dissertation thesis topic. The student must apply for this exam by April, 30 in the second year of studies. Before the Doctor State Exam the student must successfully pass the exam from English language course.
In the third and fourth year of studies the student deals with the required research activities, publishes the reached results and compiles the dissertation thesis. As part of the study duties is also completing a study period at an abroad institution or participation on an international research project with results being published or presented in abroad or another form of direct participation of the student on an international cooperation activity, which must be proved by the date of submitting the dissertation thesis.
By the end of the winter term in the fourth year of study the students submit the elaborated dissertation thesis to the supervisor, who scores this elaborate. The final dissertation thesis is expected to be submitted by the student by the end of the fourth year of studies.
In full-time study form, during the study period the student is obliged to pass a pedagogical practice, i.e. participate in the education process. The participation of the student in the pedagogical activities is part of his/her research preparations. By the pedagogical practice the student gains experience in passing the knowledge and improves the presentation skills. The pedagogical practice load (exercises, laboratories, project supervision etc.) of the student is specified by the head of the department based on the agreement with the student’s supervisor. The duty of pedagogical practice does not apply to students-payers and combined study program students. The involvement of the student in the education process within the pedagogical practice is confirmed by the supervisor in the Information System of the university.

1. Autonomous Operations of Unmanned Aerial Systems in Reconnaissance Robotics

   Research on the field of autonomous unmanned aerial reconnaissance focused on environmental data collection, creation of 3D maps and cooperation of multiple mobile platforms. Current approaches in trajectory planning, creation of various types of 3D maps of the machine surrounding, obstacle avoidance and other areas necessary for safe autonomous operation of air robotic reconnaissance vehicles in a complex outdoor environment will be studied. Based on the current state of knowledge of the issue, suitable algorithms and methods for solving this problem will be chosen. The proposed solution will then be tested in a simulated environment and compared with current best methods. The goal is also the implementation on real unmanned aircrafts, that are available at the DCI.

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

2. Deep Learning Methods in Mobile Robotics

   Research of current approaches to the use of machine learning, especially deep neural networks, for the use in reconnaissance mobile robotics. The current state of knowledge in scientific fields such as real-time terrain traversibility estimation (including 3D), creation of maps around the robot, or multimodal data fusion - typically a combination of data from lidars and cameras - will be investigated. The main emphasis will be on the sub-area of explainable artificial intelligence. The aim will be to examine mainly methods that can be implemented on mobile robotic systems due to computational complexity. After selecting a narrower research area, the selected techniques will be implemented and tested in both simulated and real environments on robotic systems available at DCI.

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

3. Distributed/decentralized real-time systems

   Fast loosely-coupled distributed and/or decentralized systems operating in real time, must be synchronized with each other in time in order to be able to perform diagnostics of the entire systém. Such sychrinization is often solved through IEEE 1588 protocol or similar solutions. However, in order to create a so-called digital shadow of such distributed system and to determine the limitations of this shadow resulting from imperfect synchronization accuracy, it is necessary to model and examine the synchronization protocol and analyze the functional limits that can be achieved in a distributed system conceived in this way. The applicable output of the research is, for example, the derivation of the maximum achievable distributed sampling rate of states in such architecture. The research will be focused on the modeling and analysis of the components of a distributed system based on Ethernet (with the IEEE 1588 protocol) with a focus on modeling the route between network elements, verifying the possibilities of analyzing the distributed system using deterministic or stochastic network calculus (Network Calculus) and deriving the functional limits of such a solution.

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

4. Immersive telepresence for unmanned vehicles

   The problematics of unmanned aerial vehicles (UAVs) and ground vehicles (UGVs) is currently a very important topic in various areas (military, emergency services, etc.). Although today’s leading research directions are mainly aimed at strengthening their autonomy, mediating perceptions from/to a remote environment (telepresence) will still be necessary, even in the case of a fully autonomous vehicle. The aim of the research is to increase the immersivity (the degree of similarity of the virtual perception with the real one) in remote sensing, which is currently still very limited. Cybernetic modelling and simulation of the human operator will be studied, including advanced dynamic and biomechanical models, on the basis of which appropriate telepresence hardware will be designed. The proposed solution will then be implemented in real UAVs and UGVs, which are available at the ÚAMT workplace and will be compared with the current best methods. Multidisciplinary cooperation with experts from non-technical areas (e.g. biomechanics, anatomy, physiology, etc.) is assumed.

   Tutor: Chromý Adam, Ing., Ph.D.

5. Methods for the measurement of mechanical shock

   The topic is aimed on measurement and generation of mechanical shocks - calibration of shock sensors and calibration of artificial sources of mechanical shocks. The aim of the thesis is to analyze the parasitic influences that affect the overall measurement uncertainties and to find new methods for their suppression. The SPEKTRA CS18 calibration system and the AVEX SM110 MP shock machine will be available for research.

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

6. Methods for vibrodiagnostics of non-rotating machines

   The topic is aimed to the research of the methods and algorithms for vibration diagnostic of non-rotating machines, especially for diagnostic method of bearings and gearboxes working under non-stationary conditions. Research will be focused on limiting factors in identification of actual methods for machines with a variable speed. Possibilities of modification or combination of these methods will be studied for achieving mechanical particles state estimation with better accuracy. In addition to the theoretical work, practical implementation and verification of these methods will be accomplished on mock-up.

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

7. Model Order Reduction for Complex Systems Control

   The topic is focused on the problem of model order reduction and related computation complexity reduction of dynamical systems models. The research will deal with methods suitable for linear as well as non-linear systems with respect to preserving system constraints. The goal of the work is to allow application of advanced control methods like MPC for systems, where direct application is not computationally feasible because of high model dimension. The studies will be performed in close relation to international and national research projects in cooperation with industry.

   Tutor: Václavek Pavel, prof. Ing., Ph.D.

8. Modeling and analysis of cyber-physical system with a human operator

   Research focused to elimination of the influence of disturbances introduced into the control system by a human operator due to biophysical characteristics of humans. Research will be focused on measuring and modeling of the movement of the upper limbs in connection with cyber-physical control system by means of electro-mechanical element in order to find a method for separating the active ingredient from the movement disturbances caused by, for example, muscle oscillations. Consequently propose a method to eliminate the disturbances. Part of the research will be focused to quantification of benefits of training, thus assessing the impact of neuro-muscular subsystem on the ability of the operator to implement motion with minimal error component. To verify the model and the proposed methods flight simulators provided by the cooperating workplace (UNOB) will be used.

   Tutor: Bradáč Zdeněk, doc. Ing., Ph.D.

9. Modelling of special safety function with respect on industrial Ethernet

   The topic is aimed on research of new special safety functions special safety functions models for machinery and the process safety. The objectives of the thesis consist of the a thorough analysis of the current safety function models, research a thorough analysis of the current models available safety functions, examining the impact of communication, particularly an industrial Ethernet. The student will be designed new models on the base on the analysis and will develop new algorithms for verification of the relevant safety logic functions and security elements for machinery and process safety. The topic will be solved in relation to national and international projects running in cooperation with industrial partners.

   Tutor: Štohl Radek, Ing., Ph.D.

10. Motor as a sensor

    The concept of autonomous fully electric vehicles requires powertrain with high level of safety. To fulfill this requirement, the redundancy concept is an option. This leads to the development of fail-safe or fail operational systems. Some sensors which are not needed for the normal operation are added to diagnose the correct functionality of the overall drive. The utilization of multiphase motors or special inverter topologies are needed. In multiphase motor control applications, there seems to be an option to use the motor or its part as a redundant sensor. The deterioration of operational parameters is in this case acceptable. Only limited functionality for limited amount of time is needed. The project solution requires to become familiar with different motor types and to select suitable motor type with regard to its usability as a sensor. Later on, the design of motor control algorithms using motor feedback in case of fault will follow. The simulation results will be validated on a real motor with the help of rapid prototyping tools.

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

11. Research of methods to improve localization accuracy inside buildings

    Research of indoor localization algorithms and methods based on wireless localization and communication system. Research is focused on assuring of quantitative localization parameters in wireless localization systems to assure quantification of quality and reliability of distance (location) measurement. The research will take advantage of data fusion methods in order to improve location accuracy based on combination of wireless localisation and information from inertial sensors. Research will therefore cover methods of data fusion, filtration and model based estimation to achieve acceptable indoor localization accuracy in challenging indoor conditions. One of the expected research outcomes is a methodology for placement of radio-beacons in order to minimize amount of beacons while maximizing location accuracy.

    Tutor: Bradáč Zdeněk, doc. Ing., Ph.D.

12. Resilience methods with a focus on industrial embedded systems

    Research in methods for increasing resilience with a focus on embedded systems (containing a multiprocessor or heterogeneous structure in cooperation with a real-time operating system) with application in industrial control systems in comply with the Industry 4.0 initiative. In the initial phase, a categorization of current approaches with a focus on formal approaches (e.g. model-driven architecture - MDA) is assumed. A significant part of the activities will be devoted to methods detecting and masking errors or attacks (both hardware and software) in the system, while using formal mathematical tools (e.g. Petri nets or transitional systems for modeling and verification, temporal logic for requirements definition) and machine learning techniques. Practical verification of research results can be validated on a microprocessor in FPGA environment (RTL logic). The goal of the research is to explore the possibilities of formal methods and machine learning techniques for increasing the reliability and security of embedded systems.

    Tutor: Arm Jakub, doc. Ing., Ph.D.

13. Virtual Sensors for Control and Diagnostics of Electrical Drives

    Modern control algorithms used for electric drives require information about a number of variables measured on the drive. A large number of sensors then means a complication in terms of both mechanical arrangement and the cost of the drive. The topic is focused on the research and development of algorithms for virtual sensors that enable a sufficiently accurate estimate of selected variables based on measurements of other variables on the drive. Although this approach is known, for example, in the context of sensorless speed or motor position control, existing algorithms still do not achieve sufficient accuracy, especially in the area of very low or, conversely, high speeds. This is precisely the situation that the proposed research will focus on. At the same time, the possibility of virtual redundancy of sensors will be studied in connection with their diagnosis.

    Tutor: Václavek Pavel, prof. Ing., Ph.D.

14. Visual Telepresence in Mobile Robotics

    Research in the field of modern progressive approaches to immersive visual telepresence for use in reconnaissance and service mobile robotics. The research will focus on achieving the best possible visual perception and will include the following sub-areas - stereovision, low latency of the sensing, transmission and imaging chain, high resolution, wireless transmission, head position sensing and head movement prediction and more. After selecting a suitable research direction, a custom solution with verification of parameters will be designed and technically implemented. Experimental deployment on one of the robotic devices available at Brno University of Technology is expected.

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

1. round (applications submitted from 01.04.2023 to 30.04.2023)

1. Mathematical methods for signal processing and reconstruction

   The topic is focused on researching modern methods for processing and analyzing signals, such as signal transformations, methods of sparse representation of signals, or machine learning. The goal is to find methods suitable for detecting signs and/or anomalies, or increasing the quality of signals based on exact quantification using appropriate criteria. The subject of the research are methods for the collection, fusion and subsequent analysis of complex data obtained from real measurements in frame of cooperation with the application sphere. The research is primarily focused on off-line data processing and identification of negative factors influencing the resulting signal quality. However, it is also expected to verify the possibilities of methods for on-line processing in general conditions.

   Tutor: Jirgl Miroslav, Ing., Ph.D.

2. Modeling and analysis of communicating cyber-physical systems operating in real time

   Embedded loosely coupled real-time systems can be synchronized via IEEE 1588 protocols or similar solutions. Communicating systems and their parameters can be modeled using, among other things, network calculus (Network Calculus), but the results of analyzes using deterministic network calculus provide significantly more pessimistic estimates than those observed in practice. Therefore, the research will be focused on the modeling of an embedded system with a communication interface and HW support of IEEE 1588 with the aim of using knowledge about the internal SW architecture of the embedded system to find such deterministic or stochastic models that will allow the subsequent analyzes to be more accurate.

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