@inproceedings{34,
  author       = {{Dellnitz, Michael and Eckstein, Julian and Flaßkamp, Kathrin and Friedel, Patrick and Horenkamp, Christian and Köhler, Ulrich and Ober-Blöbaum, Sina and Peitz, Sebastian and Tiemeyer, Sebastian}},
  booktitle    = {{Progress in Industrial Mathematics at ECMI}},
  issn         = {{2212-0173}},
  pages        = {{633--641}},
  publisher    = {{Springer International Publishing}},
  title        = {{{Multiobjective Optimal Control Methods for the Development of an Intelligent Cruise Control}}},
  doi          = {{10.1007/978-3-319-23413-7_87}},
  volume       = {{22}},
  year         = {{2016}},
}

@inproceedings{8759,
  abstract     = {{In a wide range of applications, it is desirable to optimally control a system with respect to concurrent, potentially competing goals. This gives rise to a multiobjective optimal control problem where, instead of computing a single optimal solution, the set of optimal compromises, the so-called Pareto set, has to be approximated. When it is not possible to compute the entire control trajectory in advance, for instance due to uncertainties or unforeseeable events, model predictive control methods can be applied to control the system during operation in real time. In this article, we present an algorithm for the solution of multiobjective model predictive control problems. In an offline scenario, it can be used to compute the entire set of optimal compromises whereas in a real time scenario, one optimal compromise is computed according to an operator's preference. The results are illustrated using the example of an industrial laundry. A logistics model of the laundry is developed and then utilized in the optimization routine. Results are presented for an offline as well as an online scenario.}},
  author       = {{Peitz, Sebastian and Gräler, Manuel and Henke, Christian and Molo, Mirko Hessel-von and Dellnitz, Michael and Trächtler, Ansgar}},
  booktitle    = {{Procedia Technology}},
  issn         = {{2212-0173}},
  pages        = {{483--490}},
  title        = {{{Multiobjective Model Predictive Control of an Industrial Laundry}}},
  doi          = {{10.1016/j.protcy.2016.08.061}},
  year         = {{2016}},
}

@inproceedings{8758,
  abstract     = {{In this contribution we compare two different approaches to the implementation of a Model Predictive Controller in an electric vehicle with respect to the quality of the solution and real-time applicability. The goal is to develop an intelligent cruise control in order to extend the vehicle range, i.e. to minimize energy consumption, by computing the optimal torque profile for a given track. On the one hand, a path-based linear model with strong simplifications regarding the vehicle dynamics is used. On the other hand, a nonlinear model is employed in which the dynamics of the mechanical and electrical subsystem are modeled.}},
  author       = {{Eckstein, Julian and Peitz, Sebastian and Schäfer, Kai and Friedel, Patrick and Köhler, Ulrich and Hessel von Molo, Mirko  and Ober-Blöbaum, Sina and Dellnitz, Michael}},
  booktitle    = {{Procedia Technology, 3rd International Conference on System-Integrated Intelligence: New Challenges for Product and Production Engineering}},
  issn         = {{2212-0173}},
  pages        = {{465--472}},
  title        = {{{A comparison of two predictive approaches to control the longitudinal dynamics of electric vehicles}}},
  doi          = {{10.1016/j.protcy.2016.08.059}},
  volume       = {{26}},
  year         = {{2016}},
}

@article{20071,
  author       = {{Dellnitz, M. and Eckstein, J. and Flaßkamp, K. and Friedel, P. and Horenkamp, C. and Köhler, U. and Ober-Blöbaum, Sina and Peitz, S. and Tiemeyer, S.}},
  issn         = {{2212-0173}},
  journal      = {{SysInt 2014 Proceedings}},
  location     = {{Bremen, Germany}},
  pages        = {{285 -- 294}},
  title        = {{{Development of an intelligent cruise control using optimal control methods }}},
  doi          = {{http://dx.doi.org/10.1016/j.protcy.2014.09.082}},
  volume       = {{15}},
  year         = {{2014}},
}