Prof. Dr.-Ing.  Paolo Mercorelli
Institute of Product and Process Innovation,
Leuphana University of Lueneburg,Germany
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Kalman’s optimum linear filter has proved to be very popular. Nevertheless, very often it is not always possible to use a linear system in practical applications. Extended Kalman Filters (EKFs) are used in different fields of industrial applications to reduce the number of sensors and simultaneously to improve the quality of the signals available from the process. EKFs are numerical efficient structures applied through microcontrollers in real industrial applications. Therefore, EKF approach appears to be one of the most suitable ones for problem estimation. The strategic choice of an EKF approach can be justified if the deterministic part of the model can be considered “dominant” and thus in this context, a first order linearized approach, which the EKF is based on, can be taken into consideration for possible industrial applications. After a short overview on the fundamental aspects of the background of EKF, this presentation intends to show how EKFs can be applied as an estimator in different fields of applications such as, for instance, in Thermal Systems, Flexible Actuators, Electromagnetic Actuators, Lithium-Ion Battery as well as in Permanent Magnet Synchronous Motors and other systems. Each System is analyzed in accordance with its physical inside, its intrinsic challenges and dedicated EKFs are proposed to solve specific issues of the considered real application. Measured results related to each application are shown and discussed.

Brief Biography: Paolo Mercorelli received a Ph.D. degree in Systems Engineering from his Alma Mater, Studiorum University of Bologna, Bologna, Italy, in 1998. In 1997, he was a visiting researcher for one year in the Department of Mechanical and Environmental Engineering, University of California, Santa Barbara, USA. He received an award from the Marie Curie Actions research fellowship program sponsored by The European Commission in year 1998. Thanks to this scholarship, from 1998 to 2001, Paolo Mercorelli was a postdoctoral researcher with ABB (Asea Brown Boveri) Corporate Research, Heidelberg, Germany. During the Heidelberg period he introduced, for the first time in ABB, software structures based on wavelet packets for fault detection and data reconciliation and he developed industrial trading software using these wavelet packets. He was the inventor cited in three patents in which the applicant was ABB Zuerich. Moreover, these wavelet packet structures were implemented and integrated in the Inferential Modelling Platform of the Advanced Control and Simulation Solution Responsible Unit within the ABB industry division. From 2002 to 2005, he was a senior researcher with the Institute of Automation and Informatics, Wernigerode, Germany, where he was the leader of the control group. From 2005 to 2011, Paolo Mercorelli was an Associate Professor of Process Informatics with Ostfalia University of Applied Sciences, Wolfsburg, Germany. In Wolfsburg, he was involved in various projects with the Volkswagen AG Research Center developing different control systems which have been implemented in production series of vehicles as, for instance, the control algorithms for Intelligent Parking Assist System. Since 2012 he has had the position of Full Professor and Head of the Chair of Control and Drive Systems at the Institute of Product and Process Innovation, Leuphana University of Lueneburg, Lueneburg, Germany. Since 2018 he has obtained an international visiting professor fellowship at the Institute of Automatic Control of Lodz University of Technology (Poland) and he is responsible for two courses at the Master’s in “Automation and Robotics“. In Fall 2019 he was visiting Professor at the University of Miskolc (Hungary) giving lectures at the Master’s and PhD programs. His actual interests include Applications with Kalman Filters, Robotics, Wavelets, Geometric Control, Sliding Mode Control and Application with Sliding Mode Control.

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