@inproceedings{Kistner2023,
  address = {Nürnberg},
  author = {Kistner, Lars and Schmoll, Robert and Kroll, Andreas},
  booktitle = {Sensor and Measurement Science International Conference (SMSI) 2023},
  interhash = {f9f8bd2c735d254097e7b4bbbafe26b0},
  intrahash = {1e2bc2dfaea4f8566a25127a163fe4bc},
  month = May,
  mrtnote = {nopeer},
  note = {accepted},
  organization = {AMA Verband für Sensorik und Messtechnik e.V.},
  owner = {kistner},
  title = {An Airborne Measurement System to Detect, Locate and Quantify Methane Emissions},
  year = 2023
}

@inproceedings{RehmerGMACI2022,
  address = {Berlin},
  author = {Rehmer, Alexander and Kroll, Andreas},
  booktitle = {32. Workshop Computational Intelligence},
  interhash = {8b44d3b09dca6c4b61512ae57e97ee49},
  intrahash = {69a02485ac2afe82d2460e1de5b98d6d},
  location = {Berlin},
  month = {1. - 2. Dezember 2022},
  mrtnote = {nopeer, IdRNN},
  organization = {GMA-FA 5.14},
  owner = {rehmer},
  pages = {133-150},
  publisher = {KIT Scientific Publishing},
  title = {Eine Python-Toolbox zur datengetriebenen Modellierung des Spritzgieprozsses und Lösung von Optimalsteuerungsproblemen zur Steuerung der Bauteilqualität},
  url = {https://library.oapen.org/handle/20.500.12657/59840?show=full},
  year = 2022
}

@inproceedings{RezazadehGMACI2022,
  author = {Rezazadeh, Farzad and Kroll, Andreas},
  booktitle = {32. Workshop Computational Intelligence},
  doi = {10.5445/KSP/1000151141},
  interhash = {a20931a906af754b8b035107cfb071d2},
  intrahash = {c0949ec95b894781c4c0530eb1c58b3f},
  location = {Berlin},
  month = {1.-2. December},
  mrtnote = {nopeer},
  organization = {GMA-FA 5.14},
  owner = {rezazadeh},
  pages = {53-75},
  publisher = {KIT Scientific Publishing},
  title = {Predicting the compressive strength of concrete up to 28 days-ahead: Comparison of machine learning algorithms on benchmark datasets},
  url = {https://doi.org/10.5445/KSP/1000151141},
  year = 2022
}

@article{SchmollJSSS2021,
  author = {Schmoll, Robert and Schramm, Sebastian and Breitenstein, Tom and Kroll, Andreas},
  doi = {10.5194/jsss-11-41-2022},
  interhash = {db7a86846ec4edb041aed5b37e45f6c4},
  intrahash = {b8b2e45898c525d7769867f6cbb6bffb},
  journal = {Journal of Sensors and Sensor Systems (JSSS)},
  owner = {schmoll},
  pages = {41--49},
  title = {Method and Experimental Investigation of Surface Heat Dissipation Measurement using 3D Thermography},
  url = {https://jsss.copernicus.org/articles/11/41/2022/},
  volume = 11,
  year = 2022
}

@inproceedings{Mendez2023,
  address = {Nürnberg},
  author = {Mendez, Miguel and Schramm, Sebastian and Schmoll, Robert and Kroll, Andreas},
  booktitle = {Sensor and Measurement Science International Conference (SMSI) 2023},
  interhash = {9fe3c9448400efdf6760e0ddfbaf0d79},
  intrahash = {375dba1dbf598b9b92cf543f431f513d},
  month = May,
  mrtnote = {nopeer},
  note = {accepted},
  organization = {AMA Verband für Sensorik und Messtechnik e.V.},
  owner = {Mendez},
  title = {Integration of a High-Precision 3D Sensor into a 3D Thermography System},
  year = 2023
}

@inproceedings{Rehmer-ICSTCC-2022,
  abstract = {Recurrent Neural Networks are applied in areas such as speech recognition, natural language and video processing, and the identification of nonlinear state space models. Conventional Recurrent Neural Networks, e.g. the Elman Network, are hard to train. A more recently developed class of recurrent neural networks, so-called Gated Units, outperform their counterparts on virtually every task. This paper aims to provide additional insights into the differences between RNNs and Gated Units in order to explain the superior perfomance of gated recurrent units. It is argued, that Gated Units are easier to optimize not because they solve the vanishing gradient problem, but because they circumvent the emergence of large local gradients.},
  address = {Sinaia, Romania},
  author = {Rehmer, Alexander and Kroll, Andreas},
  booktitle = {Proceedings of the 26th International Conference on System Theory, Control and Computing (ICSTCC)},
  interhash = {01dc9231b7de9c6d317b55fb73d3f07c},
  intrahash = {ace12b2b404d8d990d1420736720eb49},
  journal = {IFAC-PapersOnLine},
  language = {english},
  month = {19.-21- October},
  mrtnote = {peer,IdRNN},
  owner = {rehmer},
  pages = {446-451},
  title = {On affine quasi-LPV System Identification with unknown state-scheduling using (deep) Recurrent Neural Networks},
  year = 2022
}

@inproceedings{Pereira-IFAC-2023,
  address = {Yokohama},
  author = {Pereira, Guilherme and Jelicic, Goran and Kroll, Andreas},
  booktitle = {22nd IFAC World Congress},
  interhash = {fb72bf818e3eefe1155e6a1d5beb7edf},
  intrahash = {a713dea34d8807001d21f6e0d9b33e02},
  month = {Juli},
  mrtnote = {peer},
  note = {accepted},
  organization = {IFAC},
  owner = {gp},
  title = {Spatio-temporal LPV model of 2D workpiece temperature for Direct Laser Deposition},
  year = 2023
}

@article{Wegener_HTM2021,
  author = {Wegener, Thomas and Liehr, Alexander and Bolender, Artjom and Degener, Sebastian and Wittich, Felix and Kroll, Andreas and Niendorf, Thomas},
  doi = {https://doi.org/10.1515/htm-2021-0023},
  interhash = {f39818262d86287aafa15e734fad516f},
  intrahash = {8724667f1a37709d543e8fea50780e8f},
  journal = {HTM Journal of Heat Treatment and Materials},
  language = {english},
  mrtnote = {peer, HartDrehen},
  number = 2,
  owner = {wittich},
  pages = {156 -- 172},
  title = {Calibration and validation of micromagnetic data for non-destructive analysis of near-surface properties after hard turning},
  volume = 77,
  year = 2022
}

@inbook{EmergMeth_Rehmer_2022,
  author = {Rehmer, Alexander and Klute, Marco and Kroll, Andreas and Heim, Hans-Peter},
  booktitle = {Modeling, Identification, and Control for Cyber-Physical Systems Towards Industry 4.0},
  edition = {1st},
  editor = {Mercorelli, Paolo and Zhang, Weicun and Nemati, Hamidreza and Zhang, YuMing},
  interhash = {7cabce7909ac72e45d7cb6310ab5eebc},
  intrahash = {94960dbd8ac315f134cd05c9e29ede54},
  mrtnotes = {submitted, IdRNN},
  note = {accepted},
  publisher = {Elsevier},
  series = {Emerging Methodologies and Applications in Modelling, Identification and Control},
  title = {A Digital Twin for Part QualityPrediction and Control in Plastic Injection Molding},
  url = {https://www.elsevier.com/books/modeling-identification-and-control-for-cyber-physical-systems-towards-industry-40/mercorelli/978-0-323-95207-1},
  year = 2023
}

@inproceedings{Rehmer-CCTA-2022,
  abstract = {Recurrent Neural Networks are applied in areas such as speech recognition, natural language and video processing, and the identification of nonlinear state space models. Conventional Recurrent Neural Networks, e.g. the Elman Network, are hard to train. A more recently developed class of recurrent neural networks, so-called Gated Units, outperform their counterparts on virtually every task. This paper aims to provide additional insights into the differences between RNNs and Gated Units in order to explain the superior perfomance of gated recurrent units. It is argued, that Gated Units are easier to optimize not because they solve the vanishing gradient problem, but because they circumvent the emergence of large local gradients.},
  address = {Trieste, Italy},
  author = {Rehmer, Alexander and Klute, Marco and Kroll, Andreas and Heim, Hans-Peter},
  booktitle = {6th IEEE Conference on Control Technology and Applications (CCTA)},
  interhash = {d1b9b51dedda5b5c67717390d6d9c8c4},
  intrahash = {389f47d7fa855d74fae6cf90ae6aeadd},
  journal = {IFAC-PapersOnLine},
  language = {english},
  month = {22.-25- August},
  mrtnote = {peer,IdRNN},
  organization = {IFAC},
  owner = {rehmer},
  pages = {1427-1432},
  publisher = {Elsevier},
  title = {An internal dynamics approach to predicting batch-end product quality in plastic injection molding using Recurrent Neural Networks},
  volume = 53,
  year = 2022
}

@inproceedings{Schott_CIRP2020,
  address = {Sheffield, UK},
  author = {Schott, Christopher and Wittich, Felix and Kroll, Andreas and Niendorf, Thomas},
  booktitle = {Procedia CIRP},
  doi = {10.1016/j.procir.2020.10.002},
  interhash = {fc67dab5fd1e964fbcf06b2a5db0e859},
  intrahash = {23b6123e1e7cd2df46172a56128aa33d},
  language = {english},
  mrtnote = {peer, HartDrehen},
  owner = {wittich},
  pages = {1-4},
  title = {Prediction of near surface residual stress states for hard turned specimens using data driven nonlinear models},
  url = {https://www.sciencedirect.com/science/article/pii/S2212827121006429},
  volume = 101,
  year = 2021
}

@article{Dierks2016a,
  author = {Dierks, Sören and Retz, Stefanie and Klaus, Dominik and Supply, Carsten and Hensel, Oliver and Kroll, Andreas},
  interhash = {3bff270b0df3cd47d808d1ece152c8d8},
  intrahash = {ff41350b24232839d74f92a02bbce0ff},
  journal = {gwf -- Gas + Energie},
  language = {german},
  mrtnote = {BioGas,nopeer},
  number = 9,
  owner = {dierks},
  pages = {690-695},
  title = {Schwachstellenanalyse und fernmesstechnische Ermittlung von Methanemission aus Biogasanlagen},
  url = {https://www.di-verlag.de/de/GWF-Gas-Energie},
  volume = 157,
  year = 2016
}

@article{kroll2006b,
  author = {Kroll, Andreas},
  interhash = {7bf0e852d4a8c8ae1a8a5f47ea2a8494},
  intrahash = {b911636335fb1bc83ae5843828cfa44f},
  journal = {Automatisierungstechnische Praxis},
  language = {english},
  month = May,
  mrtnote = {peer},
  number = 5,
  owner = {liebermann},
  pages = {71-78},
  title = {Computer-based training "control performance monitoring" for personnel of process plants},
  volume = 48,
  year = 2006
}

@inproceedings{Zaidi-GMA-2012,
  address = {Dortmund},
  author = {Zaidi, Salman and Kroll, Andreas and Sommer, Hanns-Jakob},
  booktitle = {22. Workshop Computational Intelligence},
  editor = {Hoffmann, Frank and Hüllermeier, Eike},
  interhash = {48a4b7ac22293bb8c28ae53129cdf964},
  intrahash = {906352ff7c34e976aebc884379801719},
  language = {english},
  month = {6-7. Dezember},
  mrtnote = {nopeer,FuzzyT2,pke},
  organization = {GMA-FA 5.14},
  owner = {duerrbaum},
  pages = {179-199},
  publisher = {KIT Scientific Publishing},
  title = {On Description and Identification of Uncertainties in System Modeling with Fuzzy Logic},
  url = {http://www.rst.e-technik.tu-dortmund.de/cms/de/Veranstaltungen/GMA-Fachausschuss/index.html},
  year = 2012
}

@inproceedings{RehmerECC2019,
  abstract = {This paper is concerned with the test signal design for the identification of the partition parameters of locally affine Takagi-Sugeno-(TS-)Models. The basic idea is that data should be generated in local model transition areas in the scheduling space. A reference system output that represents the desired path in the scheduling space is forced upon the underlying system through a combination of a feed-forward and feedback control scheme. The system is then identified in an iterative closed-loop identification procedure. This method has been applied to an artificial system to demonstrate its potential.},
  address = {Naples, Italy},
  author = {Rehmer, Alexander and Kroll, Andreas},
  booktitle = {Preprints of the 18th European Control Conference (ECC)},
  interhash = {4bee8ec8c5ca00426c0a434506352cfb},
  intrahash = {caa85f0975dfe7174d72c95f30ef352f},
  month = {25.-28. Juni},
  mrtnote = {peer},
  organization = {IFAC},
  owner = {rehmer},
  pages = {2504-2509},
  title = {On Using Gated Recurrent Units for Nonlinear System Identification},
  url = {https://www.ifac-control.org/events/european-control-conference-in-cooperation-with-ifac-ecc-2019},
  year = 2019
}

@inproceedings{ICAISC2012,
  address = {Zakopane, Poland},
  author = {Liu, Chun and Kroll, Andreas},
  booktitle = {11th International Conference on Artificial Intelligence and Soft Computing, ICAISA 2012},
  doi = {http://dx.doi.org/10.1007/978-3-642-29350-4_56},
  editor = {Rutkowski, L. et al},
  file = {ICAISC2012:M\:\\Bibliothek\\MRT\\Publikationen\\ICAISC2012\\A                  Centralized Multi-Robot Task Allocation for                  Industrial Plant Inspection by Using A and Genetic                  Algorithms.pdf:PDF},
  interhash = {bf67f0259c15b72797a6ce24610b8051},
  intrahash = {2956b5e69d0d4ffe45ac561352272be9},
  language = {english},
  month = {April 29 - May 3},
  mrtnote = {MultiRobot,peer},
  pages = {466-474},
  series = {LNCS 7268},
  title = {A Centralized Multi-Robot Task Allocation for Industrial Plant Inspection by Using A* and Genetic Algorithms},
  year = 2012
}

@inproceedings{Kroll2010GMAb,
  address = {Dortmund},
  author = {Kroll, Andreas and Dürrbaum, Axel},
  booktitle = {20. Workshop Computational Intelligence},
  editor = {Hoffmann, Frank and Hüllermeier, Eike},
  interhash = {4462165eb976383c8da40eeb092d66e8},
  intrahash = {f83f87613c0baa03d8ecb89c231331d4},
  language = {german},
  month = {1.-3. Dezember},
  mrtnote = {FuzzyIdControl,nopeer},
  owner = {liebermann},
  pages = {161 -- 174},
  series = {Schriftenreihe des Instituts für Angewandte Informatik / Automatisierungstechnik},
  title = {Zur regelungsspezifischen Ableitung dynamischer Tagaki-Sugeno-Modelle aus rigorosen Modellen},
  year = 2010
}

@inproceedings{RehmerIFAC2017,
  abstract = {Multivariate Statistical Process Control (MSPC) techniques such as Principal Component Analysis (PCA) and Partial Least Squares (PLS) have found wide application especially in the statistical modeling and monitoring of chemical processes. However, real industrial processes often violate the assumptions underlying MSPC since they exhibit timevarying and non-stationary behavior. Adaptive PCA-based monitoring procedures such as Moving Window PCA (MWPCA) and Recursive PCA (RPCA) have been proposed to tackle this issue. Although the parameter selection for those procedures is critical to their proper implementation, this topic is rarely covered in the literature. This paper examines two methods for MWPCA and RPCA parameter selection using the Tennessee Eastman process as an example. Based on the findings a novel procedure for RPCA parameter selection as well as a extension to RPCA will be proposed and demonstrated.},
  author = {Rehmer, Alexander and Kroll, Andreas},
  booktitle = {Proceedings of the 20th IFAC World Congress},
  interhash = {558622cc877a3643bbee4fd70764be68},
  intrahash = {cdd80201e5fda51d8d1ece2280eccddc},
  mrtnote = {FEE,peer},
  organization = {IFAC},
  owner = {rehmer},
  pages = {15329-15334},
  title = {An extension to RPCA parameter selection and process monitoring},
  year = 2017
}

@inproceedings{Geiger2014a,
  address = {Magdeburg},
  author = {Geiger, Andreas and Kroll, Andreas},
  booktitle = {EKA 2014 Entwurf komplexer Automatisierungssysteme},
  interhash = {48b6740102515d9716e57342b704a3b0},
  intrahash = {cc3af3254302f82a889bc7d3164c5ebd},
  language = {deutsch},
  month = {14.-15. Mai},
  mrtnote = {Netze, peer,pke},
  owner = {geiger},
  title = {Komplexe Netzwerke zur Modellierung und Analyse von Anlagen: Qualitative Detektion des Inverse-Response-Verhaltens von Systemen höherer Ordnung},
  year = 2014
}

@inproceedings{GuentherSAS2016,
  address = {Catania, Italy},
  author = {Guenther, Thomas and Kroll, Andreas},
  booktitle = {IEEE Sensors Applications Symposium (SAS)},
  doi = {10.1109/SAS.2016.7479830},
  interhash = {45d964d21930c219f585b4919f4b1e93},
  intrahash = {243edcb711964640656e94075fc41097},
  language = {english},
  month = {20.-22. April},
  mrtnote = {robotair, peer},
  owner = {guenther},
  pages = {116 -- 121},
  title = {Automated Detection of Compressed Air Leaks Using a Scanning Ultrasonic Sensor System},
  year = 2016
}