{"status":"public","publication_identifier":{"issn":["1474-6670"]},"date_updated":"2025-02-14T09:23:18Z","type":"journal_article","author":[{"full_name":"Proß, Sabrina","last_name":"Proß","first_name":"Sabrina"},{"orcid":"0000-0002-4339-0438","full_name":"Bachmann, Bernhard","id":"33931","first_name":"Bernhard","orcid_put_code_url":"https://api.orcid.org/v2.0/0000-0002-4339-0438/work/102900347","last_name":"Bachmann"}],"main_file_link":[{"open_access":"1"}],"year":"2012","volume":45,"publication":"IFAC Proceedings Volumes","publisher":"Elsevier BV","page":"1041-1046","issue":"2","citation":{"apa":"Proß, S., &#38; Bachmann, B. (2012). Hybrid Modelling and Process Optimization of Biological Systems. <i>IFAC Proceedings Volumes</i>, <i>45</i>(2), 1041–1046. <a href=\"https://doi.org/10.3182/20120215-3-AT-3016.00184\">https://doi.org/10.3182/20120215-3-AT-3016.00184</a>","alphadin":"<span style=\"font-variant:small-caps;\">Proß, Sabrina</span> ; <span style=\"font-variant:small-caps;\">Bachmann, Bernhard</span>: Hybrid Modelling and Process Optimization of Biological Systems. In: <i>IFAC Proceedings Volumes</i> Bd. 45, Elsevier BV (2012), Nr. 2, S. 1041–1046","ieee":"S. Proß and B. Bachmann, “Hybrid Modelling and Process Optimization of Biological Systems,” <i>IFAC Proceedings Volumes</i>, vol. 45, no. 2, pp. 1041–1046, 2012.","mla":"Proß, Sabrina, and Bernhard Bachmann. “Hybrid Modelling and Process Optimization of Biological Systems.” <i>IFAC Proceedings Volumes</i>, vol. 45, no. 2, Elsevier BV, 2012, pp. 1041–46, doi:<a href=\"https://doi.org/10.3182/20120215-3-AT-3016.00184\">10.3182/20120215-3-AT-3016.00184</a>.","ama":"Proß S, Bachmann B. Hybrid Modelling and Process Optimization of Biological Systems. <i>IFAC Proceedings Volumes</i>. 2012;45(2):1041-1046. doi:<a href=\"https://doi.org/10.3182/20120215-3-AT-3016.00184\">10.3182/20120215-3-AT-3016.00184</a>","short":"S. Proß, B. Bachmann, IFAC Proceedings Volumes 45 (2012) 1041–1046.","bibtex":"@article{Proß_Bachmann_2012, title={Hybrid Modelling and Process Optimization of Biological Systems}, volume={45}, DOI={<a href=\"https://doi.org/10.3182/20120215-3-AT-3016.00184\">10.3182/20120215-3-AT-3016.00184</a>}, number={2}, journal={IFAC Proceedings Volumes}, publisher={Elsevier BV}, author={Proß, Sabrina and Bachmann, Bernhard}, year={2012}, pages={1041–1046} }","chicago":"Proß, Sabrina, and Bernhard Bachmann. “Hybrid Modelling and Process Optimization of Biological Systems.” <i>IFAC Proceedings Volumes</i> 45, no. 2 (2012): 1041–46. <a href=\"https://doi.org/10.3182/20120215-3-AT-3016.00184\">https://doi.org/10.3182/20120215-3-AT-3016.00184</a>."},"keyword":["hybrid systems","process control","Petri-nets","biological processes","hybrid optimization","open-loop control","Modelica evolution strategy","Hooke-Jeeves method"],"_id":"1514","title":"Hybrid Modelling and Process Optimization of Biological Systems","abstract":[{"lang":"eng","text":"An environment has been developed which comprises mathematical methods, concepts, and tools to enable the processing of experimental data to usable new insights about biological systems. Therefore, a mathematical modelling concept - Hybrid Petri-Nets for biological applications (HPNbio) – has been defined which is properly adapted to the demands of biological process. This concept has been implemented with the object-oriented modelling language Modelica. The developed Modelica library, called PNlib (Petri Net library), in combination with an appropriate Modelica-tool enables graphical hierarchical modelling, hybrid simulation, and animation of HPNbio-models. Thereby, an additional Modelica library, called PNproBio (Petri Nets for process modelling of Biological systems), provides wrapped HPNbio which offers on the one hand an easy-use-model at the top level with an intuitive and familiar adapted biological view and on the other hand the flexibility and generality of the HPNbio concept at a lower level. Based on an established model, the underlying processes can be optimized. This process optimization procedure is performed by means of hybrid optimization methods, i.e. a global method is combined with a local method by use of a specific switching strategy, in order to realize an open-loop control for biological processes."}],"language":[{"iso":"eng"}],"date_created":"2021-11-09T13:59:28Z","oa":"1","user_id":"35437","publication_status":"published","intvolume":"        45","doi":"10.3182/20120215-3-AT-3016.00184"}