Financing: European Commission - Horizon 2020
Scheme: MSCA-IF-EF-ST (Individual fellowship)
Project dates: June 1, 2018 - May 31, 2020
Persons: M. Fikar (project coordinator), R. Paulen (principal investigator)
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.