On February 8, we organized a scientific seminar on “Soft Sensors: Applications and Rumination”. The scientific seminar was led by Yuri Shardt, a full professor at the Department of Automation Engineering at the Technical University of Ilmenau, Germany. The scientific seminar was organised in the framework of the FrontSeat project, as part of the seminar series on “Research Seminar on Smart Cybernetics”.

Yuri Shardt


As the world becomes increasingly interconnected and tightly controlled, the need to measure each and every variable becomes increasingly important. Unfortunately, not every variable can be measured accurately in real time, for example, concentrations of complex, multiphase mixtures or the chemical properties of films may be extremely difficult to measure accurately in real time as quickly as necessary for process monitoring and control purposes. One common solution is the use of soft sensors that take the available process information and provide a forecast or prediction of the difficult-to-measure variables. Soft sensors are essentially a mathematical model relating the easy-to-measure variables with the difficult-to-measure variables. These models are developed using methods ranging from simple regression analysis to the most complex machine learning and artificial intelligence. However, not only must the models be accurate, but the configuration of the soft-sensor system within the overall process must be considered. An improper configuration can lead to poor overall soft-sensor forecasts. Additional concerns include updating the models as the underlying process changes over time. Such methods such as adaptive learning, just-in-time modelling, or re-identification can be considered. This presentation will focus on providing an overview of soft sensors, their application, and future directions.

This project has received funding from the European Union’s Horizon under grant no. 101079342 (Fostering Opportunities Towards Slovak Excellence in Advanced Control for Smart Industries).


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