Institute of Information Theory and Automation

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Dept.: AS 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. High...
Dept.: AS Duration: 2010 - 2011
Many engineering systems can be characterised as complex since they have a nonlinear behaviour incorporating a stochastic uncertainty. Urban traffic systems or traffic pollution propagation models are typical representatives of such complex systems. One of the most appropriate methods for modelling such systems is based on the application of Gaussian processes. Gaussian process models provide a...
Dept.: AS Duration: 2010 - 2013
Cílem projektu je zavedení moderního programového systému HARP a jeho asimilačního subsystému ASIM do praxe. Je určen pro podporu krizového řízení při zvládání následků mimořádných průmyslových nehod a havárií spojených s únikem radioaktivního znečistění do životního prostředí. Pravděpodobnostní verze vyvíjeného environmentálního kódu umožní analýzu šíření neurčitostí parametrů modelu s ohledem...
Dept.: AS Duration: 2009
Dept.: AS Duration: 2009 - 2013
This long-term applied project covers various research and development activities according to specification of the industrial partner.
Dept.: AS Duration: 2009 - 2012
The project aims to develop a novel on-line estimator of the key process variable in rolling mills by mixing multiple models with different sensitivities to inaccuracy in process data. The approach relies on the systematic treatment of uncertainty and merging of all available information.
Dept.: AS Duration: 2008 - 2011
Dynamic decision making (DM) maps knowledge into DM strategy, which ensures reaching DM aims under given constraints. Under general conditions, Bayesian DM, minimizing expected loss over admissible strategies, has to be used. Existing limitations of the paradigm impede its applicability to complex DM as: 1) Complexity of the information processing often crosses resources accessible. 2)...
Dept.: AS Duration: 2008 - 2009
Dept.: AS Duration: 2008 - 2010
Stochastic decentralized control of distributed systems is studied from theoretical and algorithmic point of view. Decentralization is formalized by imposing conditional independence assumptions in the centralized control problem. However, local models and aims are in general incompatible with this structure and a suitable projections must be found. A range of probabilistic approaches has been...