@article{62021,
  author       = {{Kersting, Lukas and Arian, Bahman and Rozo Vasquez, Julian and Trächtler, Ansgar and Homberg, Werner and Walther, Frank}},
  issn         = {{2405-8963}},
  journal      = {{IFAC-PapersOnLine}},
  number       = {{1}},
  pages        = {{109--114}},
  publisher    = {{Elsevier BV}},
  title        = {{{State-space modelling approach for control and observer design in property-controlled reverse flow forming}}},
  doi          = {{10.1016/j.ifacol.2025.03.020}},
  volume       = {{59}},
  year         = {{2025}},
}

@article{63475,
  author       = {{Dennstädt, Dario}},
  issn         = {{2405-8963}},
  journal      = {{IFAC-PapersOnLine}},
  number       = {{14}},
  pages        = {{7--12}},
  publisher    = {{Elsevier BV}},
  title        = {{{A low-complexity funnel control approach for non-linear systems of higher-order}}},
  doi          = {{10.1016/j.ifacol.2025.12.117}},
  volume       = {{59}},
  year         = {{2025}},
}

@inproceedings{59791,
  author       = {{Maslovskaya, Sofya and Ober-Blöbaum, Sina}},
  booktitle    = {{IFAC-PapersOnLine}},
  issn         = {{2405-8963}},
  number       = {{17}},
  pages        = {{85--90}},
  publisher    = {{Elsevier BV}},
  title        = {{{Symplectic Methods in Deep Learning}}},
  doi          = {{10.1016/j.ifacol.2024.10.118}},
  volume       = {{58}},
  year         = {{2024}},
}

@article{50070,
  author       = {{Junker, Annika and Pape, Keno Egon Friedrich and Timmermann, Julia and Trächtler, Ansgar}},
  issn         = {{2405-8963}},
  journal      = {{IFAC-PapersOnLine}},
  keywords     = {{General Medicine}},
  number       = {{3}},
  pages        = {{625--630}},
  publisher    = {{Elsevier BV}},
  title        = {{{Adaptive Koopman-Based Models for Holistic Controller and Observer Design}}},
  doi          = {{10.1016/j.ifacol.2023.12.094}},
  volume       = {{56}},
  year         = {{2023}},
}

@article{33982,
  author       = {{Koppert, Steven and Henke, Christian and Trächtler, Ansgar and Möhringer, Stefan}},
  issn         = {{2405-8963}},
  journal      = {{IFAC-PapersOnLine}},
  keywords     = {{Control and Systems Engineering}},
  number       = {{2}},
  pages        = {{554--560}},
  publisher    = {{Elsevier BV}},
  title        = {{{Tool Wear Monitoring of a Tree Log Bandsaw using a Deep Convolutional Neural Network on challenging data}}},
  doi          = {{10.1016/j.ifacol.2022.04.252}},
  volume       = {{55}},
  year         = {{2022}},
}

@article{50071,
  author       = {{Junker, Annika and Timmermann, Julia and Trächtler, Ansgar}},
  issn         = {{2405-8963}},
  journal      = {{IFAC-PapersOnLine}},
  keywords     = {{Control and Systems Engineering}},
  number       = {{12}},
  pages        = {{389--394}},
  publisher    = {{Elsevier BV}},
  title        = {{{Learning Data-Driven PCHD Models for Control Engineering Applications*}}},
  doi          = {{10.1016/j.ifacol.2022.07.343}},
  volume       = {{55}},
  year         = {{2022}},
}

@article{23277,
  abstract     = {{We exploit a recently developed funnel control methodology for linear non-minimum phase systems to design an output error feedback controller for a nonlinear robotic manipulator, which is not minimum phase. We illustrate the novel control design by a numerical case study where we simulate end-effector output tracking of the robotic manipulator.}},
  author       = {{Berger, Thomas and Lanza, Lukas Johannes}},
  issn         = {{2405-8963}},
  journal      = {{IFAC-PapersOnLine}},
  pages        = {{178--185}},
  title        = {{{Output tracking for a non-minimum phase robotic manipulator}}},
  doi          = {{10.1016/j.ifacol.2021.06.074}},
  year         = {{2021}},
}

@article{35576,
  author       = {{Schulze Darup, Moritz and Klädtke, Manuel and Mönnigmann, Martin}},
  issn         = {{2405-8963}},
  journal      = {{IFAC-PapersOnLine}},
  keywords     = {{Control and Systems Engineering}},
  number       = {{6}},
  pages        = {{290--295}},
  publisher    = {{Elsevier BV}},
  title        = {{{Exact solution to a special class of nonlinear MPC problems}}},
  doi          = {{10.1016/j.ifacol.2021.08.559}},
  volume       = {{54}},
  year         = {{2021}},
}

@article{35578,
  author       = {{Faulwasser, Timm and Lucia, Sergio and Schulze Darup, Moritz and Mönnigmann, Martin}},
  issn         = {{2405-8963}},
  journal      = {{IFAC-PapersOnLine}},
  keywords     = {{Control and Systems Engineering}},
  number       = {{6}},
  pages        = {{238--243}},
  publisher    = {{Elsevier BV}},
  title        = {{{Teaching MPC: Which Way to the Promised Land?}}},
  doi          = {{10.1016/j.ifacol.2021.08.551}},
  volume       = {{54}},
  year         = {{2021}},
}

@article{35561,
  author       = {{Darup, Moritz Schulze}},
  issn         = {{2405-8963}},
  journal      = {{IFAC-PapersOnLine}},
  keywords     = {{Control and Systems Engineering}},
  number       = {{2}},
  pages        = {{3508--3514}},
  publisher    = {{Elsevier BV}},
  title        = {{{Encrypted MPC based on ADMM real-time iterations}}},
  doi          = {{10.1016/j.ifacol.2020.12.1708}},
  volume       = {{53}},
  year         = {{2021}},
}

@inproceedings{22894,
  abstract     = {{The first order optimality conditions of optimal control problems (OCPs) can
be regarded as boundary value problems for Hamiltonian systems. Variational or
symplectic discretisation methods are classically known for their excellent
long term behaviour. As boundary value problems are posed on intervals of
fixed, moderate length, it is not immediately clear whether methods can profit
from structure preservation in this context. When parameters are present,
solutions can undergo bifurcations, for instance, two solutions can merge and
annihilate one another as parameters are varied. We will show that generic
bifurcations of an OCP are preserved under discretisation when the OCP is
either directly discretised to a discrete OCP (direct method) or translated
into a Hamiltonian boundary value problem using first order necessary
conditions of optimality which is then solved using a symplectic integrator
(indirect method). Moreover, certain bifurcations break when a non-symplectic
scheme is used. The general phenomenon is illustrated on the example of a cut
locus of an ellipsoid.}},
  author       = {{Offen, Christian and Ober-Blöbaum, Sina}},
  issn         = {{2405-8963}},
  keywords     = {{optimal control, catastrophe theory, bifurcations, variational methods, symplectic integrators}},
  location     = {{Berlin, Germany}},
  pages        = {{334--339}},
  title        = {{{Bifurcation preserving discretisations of optimal control problems}}},
  doi          = {{https://doi.org/10.1016/j.ifacol.2021.11.099}},
  volume       = {{54(19)}},
  year         = {{2021}},
}

@inproceedings{8812,
  author       = {{Schulze Darup, Moritz and Redder, Adrian and Quevedo, Daniel E.}},
  booktitle    = {{IFAC-PapersOnLine}},
  issn         = {{2405-8963}},
  pages        = {{535--542}},
  title        = {{{Encrypted cloud-based MPC for linear systems with input constraints}}},
  doi          = {{10.1016/j.ifacol.2018.11.035}},
  year         = {{2018}},
}

@article{16657,
  author       = {{Peitz, Sebastian and Schäfer, Kai and Ober-Blöbaum, Sina and Eckstein, Julian and Köhler, Ulrich and Dellnitz, Michael}},
  issn         = {{2405-8963}},
  journal      = {{IFAC-PapersOnLine}},
  pages        = {{8674--8679}},
  title        = {{{A Multiobjective MPC Approach for Autonomously Driven Electric Vehicles * *This research was funded by the German Federal Ministry of Education and Research (BMBF) within the Leading-Edge Cluster Intelligent Technical Systems OstWestfalenLippe (it’s OWL).}}},
  doi          = {{10.1016/j.ifacol.2017.08.1526}},
  year         = {{2017}},
}

@article{8756,
  abstract     = {{We present a new algorithm for model predictive control of non-linear systems with respect to multiple, conflicting objectives. The idea is to provide a possibility to change the objective in real-time, e.g. as a reaction to changes in the environment or the system state itself. The algorithm utilises elements from various well-established concepts, namely multiobjective optimal control, economic as well as explicit model predictive control and motion planning with motion primitives. In order to realise real-time applicability, we split the computation into an online and an offline phase and we utilise symmetries in the open-loop optimal control problem to reduce the number of multiobjective optimal control problems that need to be solved in the offline phase. The results are illustrated using the example of an electric vehicle where the longitudinal dynamics are controlled with respect to the concurrent objectives arrival time and energy consumption.}},
  author       = {{Peitz, Sebastian and Schäfer, Kai and Ober-Blöbaum, Sina and Eckstein, Julian and Köhler, Ulrich and Dellnitz, Michael}},
  issn         = {{2405-8963}},
  journal      = {{Proceedings of the 20th World Congress of the International Federation of Automatic Control (IFAC)}},
  number       = {{1}},
  pages        = {{8674--8679}},
  title        = {{{A multiobjective MPC approach for autonomously driven electric vehicles}}},
  doi          = {{10.1016/j.ifacol.2017.08.1526}},
  volume       = {{50}},
  year         = {{2017}},
}

@article{20809,
  author       = {{Jean, Frédéric and Maslovskaya, Sofya and Zelenko, Igor}},
  issn         = {{2405-8963}},
  journal      = {{IFAC-PapersOnLine}},
  pages        = {{500--505}},
  title        = {{{Inverse Optimal Control Problem: the Sub-Riemannian Case }}},
  doi          = {{10.1016/j.ifacol.2017.08.105}},
  year         = {{2017}},
}