Objective
The technique of guaranteed estimation promises a revolutionary step to how industrial process managers build, handle and adapt the prediction mathematical models. These are used to monitor the equipment operating regimes, to train the
operating personnel and are also exploited to steer the plants' behavior towards the most profitable or the most resource-
efficient modes. Advantages of guaranteed estimation come from the fact that no unnecessary assumptions must be made
regarding the quality and measurement-error distribution of the sensed data, which establishes an increased reliability of the
obtained estimation results. The work on this project develops the essential parts of guaranteed estimation techniques for
real-world exploitation. We focus on the estimation of parameters of the nonlinear dynamic models while combining the
estimation with model validation principles and while creating a hybrid estimation technique that enjoys the advantages of
both guaranteed estimation and conventional approaches. In order to drive the operation of the plant, here we focus on the
plants of chemical industry, to an efficient working regime, the technology of optimal and robust control is required. Our
project builds upon the developments of robust control and develops novel optimal robust control techniques that incorporate
the information on guaranteed estimates into the actions, i.e. manipulations of the plants' degrees of freedom. As a result, a
safe, reliable and resource-efficient operation is established. The theoretical developments of the project are implemented
into a software package and released as an open-source project such that the collaboration with academia and industrial
stakeholders is fostered. A demonstration on a pilot plant is also planned to showcase the benefits of developed techniques
in the real-world environment. A sound dissemination plan of the project ensures that the project reaches its target audience.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencescomputer and information sciencessoftware
- natural sciencesmathematicsapplied mathematicsmathematical model
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Programme(s)
Funding Scheme
MSCA-IF-EF-ST - Standard EFCoordinator
81243 Bratislava
Slovakia