Systems Theory and Automatic Control

Bruno Morabito

  Research Assistant
  Institute for Automation Engineering (IFAT)
  Laboratory for Systems Theory and Automatic Control
  Otto-von-Guericke University Magdeburg
  39106 Magdeburg - Germany




State and parameter estimation, Moving Horizon Estimation, Model Predictive Control, Automation of bioreactors for cell culture, autonomous drilling systems.

Proceedings (peer reviewed)

[5] L. Carius, J. Pohlodek, B. Morabito, A. Franz, M. Mangold, R. Findeisen, and A. Kienle. Model-based state estimation utilizing a hybrid cybernetic model. In Advanced Control of Chemical Processes (AdChem), July 2018.
[4] P. Andonov, B. Morabito, A. Savchenko, and R. Findeisen. Admissible Control Parametrization of Uncertain Finite-time Processes With Application to Li-ion Battery Management. In European Control Conference (ECC), pages 2338--2343, Limasol, Cyprus, 2018.
[3] J. Bethge, B. Morabito, J. Matschek, and R. Findeisen. Multi-mode learning supported model predictive control with guarantees. In Proceedings of 6th Nonlinear Model Predictive Control Conference (NMPC), pages 616--621, Madison, United States, 2018.
[2] B. Morabito, R. Klein, and R. Findeisen. Real time feasibility and performance of moving horizon estimation for li-ion batteries based on first principles electrochemical models. In 2017 American Control Conference (ACC), pages 3457--3462, May 2017. [ DOI ]
[1] B. Morabito, M. Kögel, E. Bullinger, G. Pannocchia, and R. Findeisen. Simple and efficient moving horizon estimation based on the fast gradient method. IFAC-PapersOnLine, 48(23):428 -- 433, 2015. 5th IFAC Conference on Nonlinear Model Predictive Control NMPC 2015. [ DOI | http ]

Submitted Proceedings (accepted)

[1] B. Morabito, A. Kienle, R. Findeisen, and L. Carius. Multi-mode model predictive control and estimation for uncertain biotechnological processes. In Submitted to DYCOPS 2019, July 2019.

Submitted Proceedings (to be peer reviewed)

[2] M. Ibrahim, J. Matschek, B. Morabito, and R. Findeisen. Improved area covering in dynamic environments by nonlinear model predictive path following control. In Proceedings of 8th IFAC Symposium on Mechatronic Systems (MECHATRONICS 2019), Vienna, Austria, 2019. submitted.
[1] M. Ibrahim, J. Matschek, B. Morabito, and R. Findeisen. Hierarchical model predictive control for autonomous vehicle area coverage. In Proceedings of 21st IFAC Symposium on Automatic Control in Aerospace (ACA 2019), Cranfield, UK, 2019. submitted.

  • Directional prediction using drill bit steerability models within a trajectory control system - Muhammad Adnan Hanif (2019)
  • Nichtlineare modellpraediktive Regelung fuer Pfandverfolgungsprobleme im Bereich Tiefbohrtechnik unter Berueksichtigung von Beschraenkungen und Kommunikationskosten- Philip Trennt (2016)
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Research Experiences

  • 2016 - Currently: Member of the International Max Planck Research School (IMPRS), Max Planck Institute - Magdeburg, Germany

  • 2016 - Currently: Research assistant, Otto von Gueriche University, Magdeburg, Germany

  • August 2015 - March 2016: Intership at Robert Bosch Research and Technology Center, Palo Alto, California, USA

  • September 2013 - March 2014: Student assistent, Otto von Guericke University, Magdeburg, Germany


  • 2012 - 2014: Master's in Chemical Engineering, University of Pisa, Pisa, Italy

  • 2009 - 2012: Bachelor's in Chemical Engineering, University of Pisa, Pisa, Italy

  • 2004 - 2009: High school "A.Panella" Chemistry Section, Reggio Calabria, Italy

  • Optimal Control tutorials WS 2017-2018
  • Optimal Control tutorials WS 2016-2017
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