The aim of the study is to teach the students how to conduct their own research in control theory, artificial intelligence, soft computing (fuzzy logic, neural networks, evolutionary programming, …) and operations research applied to control of machines and technological processes, scheduling of manufacturing processes, development of expert and information systems and project management. The subjects of Ph.D. theses include identification, modelling, simulation and control of nonlinear systems, development of distributed monitoring and dispatcher systems, solving of complex optimisation problems, design and implementation of robot control and navigation, etc.
Students may continue both their short- and long-term study stays at universities abroad as part of the Socrates/Erasmus and CEEPUS programs. Such universities are in Bristol, Aalborg, Cluny, Utrecht, Tampere, and Maribor.

As the studies combine automation, control, and computer science, thus covering several disciplines, the graduates can apply for research and development positions at both domestic and foreign companies dealing in applications of cutting-edge information technologies, design and manufacture of control and information systems and application of automation tools to the control of machines and technological processes.

prof. Ing. Václav Píštěk, DrSc.

1. Design and implementation of adaptive control of smart buildings

   Dissertation thesis will deal with the development and application verified technologies of adaptive control smart houses, using multivariable analysis of signals obtained during the operation of these systems. Adaptation mechanisms are based on the principles of processing vague information using by Petri nets and knowledge base generated by IF - THEN rules. These tools will be used to compile simulation models and design of adaptive control of smart houses. The objective is to design and implementation an innovative methodology for the analysis and recognition of structures in the data for time-dependent for control of smart buildings.

   Tutor: Šťastný Jiří, prof. RNDr. Ing., CSc.

2. Design of adaptive control using the ROS framework

   A significant development in the area of mobile robotics was noticed in the last time in connection with the arrival of modern, powerful and mainly miniature computers and controllers. The development of mobile robotic devices is also correlative of to the development of sensory systems that are increasingly more accurate, faster and smaller. The role of mobile robots can be different. In some stores, Amazon, for example, a system of autonomous mobile robots is used. These mobile robots are able to bring and carry off cart with the desired goods which is needed. Furthermore, mobile robots are used for example for mapping indoor or outdoor space, such as service robots, or as a part of other mechanism, such as parking assistant in automobiles. The proposed project is focuses on mapping the interior and aims to design and implement algorithms of adaptive control of mobile robots. The project will design a system for obtaining data to create a 3D model of the mapped area. For designing the algorithm and for robot control the ROS framework will be used.

   Tutor: Šťastný Jiří, prof. RNDr. Ing., CSc.

3. Development of control design methods for combustion systems with solid biofuel.

   This thesis deals with developing control methods for solid biofuel combustion system. Designed control system must be able to meet emission limits as well as energy efficiency given by CZ and EU legislation. While focusing on this target, system has to be as simple as it can be designed and affordable to be commercially successful. Inputs for methods will be measuring and analyzing data of combustion system prototype with performance control and DAQ system. Method result output will be deployment design of sensors, which are necessary for combustion system control and control algorithms for low-cost PLC. Solution will be implemented in cooperation with Deptartment of Power Engineering of Energy Institute and with company GEMOS CZ spol, s r.o. with NETME.

   Tutor: Věchet Stanislav, doc. Ing., Ph.D.

4. Development of design methodology of energy efficient hydraulic systems

   The aim of the work is to develop design methodology of hydraulic systems with hydraulic actuators and electrohydraulic pressure working fluid power units. Analysis of energy flow and consumption in both hydraulic and electric circuits is assumed. Results of the analysis will further be applied on model configurations of hydraulic circuits, for which the methodology of hydraulic, sensorics and control system design will be created. Safety standards applicable in the Czech Republic and in the EU must be considered in the developed methodology. The solution will be implemented in cooperation with Bosch Rexroth, spol. s r.o. and will be connected to NETME.

   Tutor: Věchet Stanislav, doc. Ing., Ph.D.

5. Development of design methodology of single-purpose-production-machines and testers

   This thesis aims on development of design methodology of single-purpose-machines and testers for mass production. The result of the thesis, will be the methodology which will simplify and make more efficient the process of designing these machines and testers especially in the design of the control software and the necessary sensors. In the methodology must be included the safety standards which are valid in Czech Republic and EU. The solution will be implemented in collaboration with the following companies TEAZ s.r.o, IMI international – Norgren CZ and other producers. The work on the thesis within VUT will be connected with the NETME program.

   Tutor: Věchet Stanislav, doc. Ing., Ph.D.

6. Nontraditional methods for data classification and prediction in process control

   Artificial intelligence methods belong among modern methods for optimization of process control. Using theese methods is especially suitable for problems which are very difficult to solve using classical mathematical methods or where using deterministic computation methods would require unacceptable simplification of the problem. An acquisition of the optimization data by means of modern methods and algorithms of artificial intelligence is a significant task in object classification. Approaches used by a graduant solving the aforementioned task are as follows: Analysis artificial intelligence methods, analysis algorithms for data classification and prediction.

   Tutor: Šťastný Jiří, prof. RNDr. Ing., CSc.