Prof. Dr.-Ing. Paolo Mercorelli
Werdegang
- In der Liste von World’s Top 2% Scientists 2025 aus Elsevier Database und gekennzeichnet von Stanford University
- Summer 2025- Vorlesung durch the University Studies Abroad Consortium (USAC) an der University of North Caroline at Wilmington, (USA) im Summersemester 2025
- Summersemeter 2025 Visiting Professor an der Technische Universität Lublin (Poland) of Technology und verantwortlich für den Kurs "Kalman Filters and its Applications".
- In der Liste von World’s Top 2% Scientists 2024 aus Elsevier Database und gekennzeichnet von Stanford University
- Wintersemeter 2024/2025 Visiting Professor an der Technische Universität Lublin (Poland) of Technology und verantwortlich für den Kurs "Control Systems".
- Frühling 2024 - Visiting Professor at the University of Miskolc in the context of the PhD School. Department of Automation and Communication Technology, Miskolc (Hungary)
- In der Liste von World’s Top 2% Scientists 2023 aus Elsevier Database und gekennzeichnet von Stanford University
- Summer 2023- Vorlesung durch the University Studies Abroad Consortium (USAC) an der National Public Research Universtiy of Kentucky, Kentucky, (USA)
- Visiting Professor at Chandigarh University (India) und verantwortlich für den Kurs "Control of Nonlinear Systems", 13th Februar-5th Mai 2023
- In der Liste von World’s Top 2% Scientists 2022 aus Elsevier Database und gekennzeichnet von Stanford University
- Editor-in-Chief für die Section „Engineering Mathematics“ in „Mathematics“, Open Access Journal von MDPI, Basel, Switzerland
- In der Liste von World’s Top 2% Scientists 2021 aus Elsevier Database und gekennzeichnet von Stanford University
- Summer 2021- Vorlesung durch the University Studies Abroad Consortium (USAC) an der National Public Research Wright Universtiy (Ohio State University)
- In der Liste von World’s Top 2% Scientists 2020 aus Elsevier Database und gekennzeichnet von Stanford University
- Summer 2020- Vorlesung durch the University Studies Abroad Consortium (USAC) an der Nevada Universität (Las Vegas und Reno) und and Arkansas Universität (Fayetteville)
- Wintersemester 2020 - Visiting Professor at the University of Craiova in the context of 1st International Doctoral Workshop on Advanced Approaches in Robotics, Control and Computing of the Faculty of Automation, Computers and Electronics, Craiova (Romania)
- In der Liste von World’s Top 2% Scientists 2019 aus Elsevier Database und gekennzeichnet von Stanford University
- Der Zahlendreher: Article in PRISE - Das Lifestylemagazin
- Herbst 2019 - Visiting Professor at the University of Miskolc in the context of the PhD School. Department of Automation and Communication Technology, Miskolc (Hungary)
- seit Wintersemester 2017/2018 - International Distinguished Visiting Professor Fellowship at institute of Automatic Control of Lodz University of Technology (Poland). Er ist Verantwortlicher für den Kurs „Modelling of Industrial Control Systems“ und für den Kurs “Modeling Methods of Analog Circuits” am Master Course in Automatic Control and Robotics.
- seit 2018 International Visiting Scientist Fellowship at Academic of Science of Prague (Czech Republic)
- seit 01.03.2012 W3-Professor (Lehrstuhlinhaber) für "Regelungs- und Antriebstechnik" an der Leuphana Universität Lüneburg (Deutschland)
- 2011 Gastprofessor für System Dynamics der Villanova University (Pennsylvania, USA)
- 2011 Ruf für Full Professor für System Dynamics an der Villanova University (Pennsylvania, USA). Der Ruf wurde in eine Gastprofessur umgewandelt um in Deutschland zu bleiben.
- In 2010 im dem "short list" und am zweite Platz für Associate Professor in Electrical and Hybrid Drive Systems, VL-2010-0004 of the KTH Royal Institute of Technology of Stocholm
- 2009 Gastprofessor für Mechatronik an der German University in Kairo (Egypt)
- 2009 Ruf für Full Professor für Mechatronics an der German University in Kairo (Egypt). Der Ruf wurde in einer Gastprofessur umgewandelt um in Deutschland zu bleiben.
- 01.03.2005 - 29.02.2012 W2-Professor für "Prozessinformatik" an der Ostfalia Hochschule für angewandte Wissenschaften in Wolfsburg (Deutschland)
- 01.03.2002-28.02.2005 Leiter der Regelungstechnik-Gruppe an der IAI GmbH (Institut für Automatisierung und Informatik, Zentrum für Industriellen Forschung und Entwicklung) Wernigerode (Deutschland)
- 01.04.2001-29.02.2002 wissenschaftlicher Mitarbeiter an der Uni-Siena (Italien)
- 20.07.1998-31.03.2001 Post Doctoral Fellowship durch European Commission (Marie-Skłodowska-Curie Program/wissenschaftlicher Mitarbeiter), ABB (Asea Brown Boveri) Corporate Research AG in Heidelberg (Deutschland). Damit werden europäische Doktoranden und Postdocs gefördert, die außerhalb ihres Heimatlands forschen möchten. Es handelt sich dabei gleichzeitig um eine der begehrtesten und renommiertesten Auszeichnungen der EU für interdisziplinäre Forschung und internationale Kollaboration.
- 01.01.1997-30.11.1997 wissenschaftliche Tätigkeit an der Universität von Santa Barbara (California) (USA) entsprechend dem Promotionsprogramm
- 01.11.1994-31.12.1998 wissenschaftliche Tätigkeit an der Alma Mater Studiorum Universität von Bologna entsprechend dem Promotionsprogramm
- 1992 Diplomingenieur an der Universität von Florenz (Italien)
Publikationen
Beiträge in Sammelwerken
- A sufficient asymptotic stability condition in generalised model predictive control to avoid input saturation
Paolo Mercorelli (Autor*in) , 01.01.2019 , S. 251-257 , 7 S.Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
- Model predictive control for switching gain adaptation in a sliding mode controller of a DC drive with nonlinear friction
Benedikt Haus (Autor*in) , Jan Hendrik Röhl (Autor*in) , Paolo Mercorelli (Autor*in) , Harald Aschemann (Autor*in) , 01.11.2018 Piscataway , S. 765-770 , 6 S.Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
- Observer Strategies for Virtual Sensing of Embroidered Metal-Polymer Heater Structure
Manuel Schimmack (Autor*in) , Florian Poschke (Autor*in) , Horst Schulte (Autor*in) , Paolo Mercorelli (Autor*in) , 08.10.2018 , S. 887-892 , 6 S.Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
Lehrveranstaltungen
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Introduction on Matlab/Simulink; the most important Matlab/Simulink functions; structure of a Matlab/Simulink model simulation through different examples (technical systems, economic systems, biologic systems,...). The course embraces stochastic and deterministic methods of identification and control of dynamical systems. Static and Recursive Least Squares Methods to estimate parameters of systems (simple technical and economic systems). Nonconvex optimization: Particle Swarm Optimization Methods. Modelling and observers: examples of usage of observers in technical, economic and biologic systems. (Examples: 1. electrical motor with mechanical load. 2. Simple capital investment system. Lotka-Volterra model). 3. A control strategy: Sliding Mode Control. Examples of control of a simple capital investment system. Control of an electrical motor.
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The module covers necessary mathematical foundations (deepening of ordinary differential equations, Fourier, Laplace, and Z-transformations) and imparts knowledge of properties of dynamic systems (continuous, discrete, static, dynamic, autonomous, controlled). In addition, the module covers topics such as modeling, stability and convergence analysis, behavior, and simulation of continuous and discrete systems. Aspects such as modeling, observability, and controllability of dynamic systems, stability criteria, transfer functions, stability analysis of root locus, controller design through pole placement, and classic (P, I, PD, PI, PID) and cascade controllers are also covered. The module's contribution to digitization and Industry 4.0 lies mainly in the area of discrete control systems.
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MATLAB is a platform for scientific calculation and high-level programming which uses an interactive environment that allows to conduct complex calculation tasks more efficiently than with traditional languages, such as C, C++ and FORTRAN. It is the one of the most popular platforms currently used in the sciences and engineering. Optimization techniques can be applied in a wide interdisciplinary range of applications in control, estimation and identification problems. Using Matlab, the course embraces the most important optimization techniques and methods which can be used in control systems. The proposed techniques, e.g. Model Predictive Control, Two Point Boundary Optimization Problem, etc. are implemented using Matlab/Simulink. Through discussions on the mathematical origin of the proposed techniques and methods and their inspiring ideas the students should reach, not only a good command on the software, but also a critical spirit to interpret the nature of the algorithms and to reflect on their foundations and structures.
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MATLAB is a platform for scientific calculation and high-level programming which uses an interactive environment that allows to conduct complex calculation tasks more efficiently than with traditional languages, such as C, C++ and FORTRAN. It is the one of the most popular platforms currently used in the sciences and engineering. Optimization techniques can be applied in a wide interdisciplinary range of applications in control, estimation and identification problems. Using Matlab, the course embraces the most important optimization techniques and methods which can be used in control systems. The proposed techniques, e.g. Model Predictive Control, Two Point Boundary Optimization Problem, etc. are implemented using Matlab/Simulink. Through discussions on the mathematical origin of the proposed techniques and methods and their inspiring ideas the students should reach, not only a good command on the software, but also a critical spirit to interpret the nature of the algorithms and to reflect on their foundations and structures.
⌄
The module covers necessary mathematical foundations (deepening of ordinary differential equations, Fourier, Laplace, and Z-transformations) and imparts knowledge of properties of dynamic systems (continuous, discrete, static, dynamic, autonomous, controlled). In addition, the module covers topics such as modeling, stability and convergence analysis, behavior, and simulation of continuous and discrete systems. Aspects such as modeling, observability, and controllability of dynamic systems, stability criteria, transfer functions, stability analysis of root locus, controller design through pole placement, and classic (P, I, PD, PI, PID) and cascade controllers are also covered. The module's contribution to digitization and Industry 4.0 lies mainly in the area of discrete control systems.