Institute of Information Theory and Automation

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Department of Adaptive Systems

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The Department of Adaptive Systems focuses predominantly on the design of decision-making systems, which modify their behavior according to the changing properties of their environment. This essential ability – adaptivity – enhances their efficiency. Decades of research have brought a number of conceptual, theoretical, algorithmic, software and application results. The applicability of adaptive systems is currently being extended toward complex scenarios by improving the classical adaptive systems and by developing their new versions.

The departmental “know-how” serves to resolve national as well as international research projects, running in collaboration with industry and government agencies. The interplay between theory and limited computing power is the common issue linking the various project domains. They include traffic control, management and control of technological systems, radiation protection, nuclear medicine, analysis of financial data, electronic democracy, etc. The increasing complexity of the problems addressed directs the main stream of the research toward decentralized control of large-scale systems and normative decision-making with multiple participants.

2019-10-03 13:46

Department detail

Ing. Lubomír Bakule CSc.
Ing. Květoslav Belda Ph.D.
Ing. Josef Böhm CSc.
Ing. Antonie Brožová
Ing. Jindřich Bůcha CSc.
Ing. Kamil Dedecius Ph.D.
Dr. Siavash Fakhimi Derakhshan Ph.D.
Ing. Tatiana Valentine Guy Ph.D.
Ing. Jitka Homolová Ph.D.
Bc. Adam Jedlička
RNDr. Ladislav Jirsa Ph.D.
Ing. Miroslav Kárný DrSc.
Ing. Lenka Kuklišová Pavelková Ph.D.
Ing. Rudolf Kulhavý DrSc.
Ing. Petr Nedoma CSc.
Bc. Pavla Hermína Neuner
Ing. Petr Pecha CSc.
Ing. Marko Ruman
Ing. Tereza Siváková
Doc. Ing. Václav Šmídl Ph.D.
Ing. Ondřej Tichý Ph.D.
Ing. Petr Zagalak CSc.
Ing. Radomír Žemlička
Duration: 2013 - 2015
The project is aimed to bring a novel type of monitors of the overall control system condition based on hierarchical assessment of its components. The idea combines mathematical models of system's inner relations and priors on components reliability by using a consistent probabilistic approach.
Duration: 2012 - 2014
Differential equations form a tool that is frequently used for describing a great variety of dynamical systems. The developed theory of differential equations gives a possibility to study different kinds of processes like those with a finite number of degrees of freedom (ordinary differential equations), systems with distributed parameters (partial differential equations), systems with memory (d
Duration: 2011 - 2014
The aim of this project is to create, verify and hand over to the industrial partner a prototype of a small urban traffic control system with an open interface. The control system is inspired by an existing macroscopic state-space model of an urban transportation network, that has been tested in real traffic conditions in winter 2010.
Duration: 2011 - 2013
The project deals with control algorithms directed at optimization of fuel consumption in vehicles from economical/ecological point of view. Bayesian methodology is used.
Duration: 2011 - 2014
The aim of this project is to explore new directions in diagnostics, control and parameter identification strategies of ac electric drives under critical operating conditions. Main attention will be paid to sensorless drive control and estimation in standstill and low speeds. We propose to explore suitability of methods from Bayesian identification and stochastic control in this area.