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. Intelligent Model Predictive Controllers

   Model predictive control (MPC) is an efficient method for the controller design of a large number of processes. However, linear MPC is often inappropriate for controlling nonlinear large-scale systems, while non-linear MPC is, in general, computationally costly. The work will try to find intelligent and optimal design of MPC for controlling of selected nonlinear and complex systems. Research and applications in the areas of advanced control theory, computational intelligence, simulation and practical real-time implementation will be challenges of this work.

   Tutor: Matoušek Radomil, prof. Ing., Ph.D.

4. The methodology for evaluating the current operating status of nuclear power plants devices in the Czech Republic

   Organization IAEA (International Atomic Energy Agency) has promulgated fundamental principles and requirements that encourage the consideration of risk information and analyses along with deterministic and stochastic safety analyses. This evaluation can be appropriately accomplished using IRIDM (Integrated Risk Informed Decision Making) process, which is aimed at the systematic integration of the major considerations influencing nuclear power plant safety. In the thesis a methodology will be created. This methodology will reflect the specific features of Czech nuclear power plants. It will take into account deterministic and stochastic outputs of different control systems and one will create an optimized and comprehensive evaluation of the operating status of each device. Eventually, the system will be implemented using this methodology for selected devices at NP Temelín that will verify the results of the assessment based on the proposed methodology to the current situation.

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