Stability and robustness in data-driven predictive control:
Spray polymerisation has a long time been discussed as a promising process, yet, with little knowledge on cause-and-effect relationships between drying and chemical reactions. This work develops a new single droplet model of combined solution drying and free radical homopolymerisation, based on the...
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Abschlussarbeit Buch |
| Sprache: | English |
| Veröffentlicht: |
Berlin
Logos Verlag
[2022]
|
| Schlagworte: | |
| Zusammenfassung: | Spray polymerisation has a long time been discussed as a promising process, yet, with little knowledge on cause-and-effect relationships between drying and chemical reactions. This work develops a new single droplet model of combined solution drying and free radical homopolymerisation, based on the method of moments. New, consistent approaches for momentsâ diffusion and the reaction-diffusion system are derived to ensure conservation. Simulations reveal peculiarities of the process such as that, due to drying, polymerisation happens mostly in bulk and monomer evaporation leads to a poor yield. Various process variants and simulation models are discussed. The impact of process parameters is examined by means of numerical DoEs. The second part presents a novel approach for the simulation of structure evolution in suspension drying. The meshfree SPH method is used to model the relevant physical effects on a detailed scale during the first and second drying period. New implementations of physical effects are derived: heat and mass transfer based on linear driving forces, an implicit solution of the heat equation, several approaches for crust formation and a new formulation of surface tension by pairwise forces. The formation of dense structures as well as hollow granules can be simulated. Model parameters influence crust formation during the second drying period concerning shape and microporosity and can be interpreted in a physical sense |
| Beschreibung: | xvi, 247 Seiten Diagramme |
| ISBN: | 9783832555313 |
Internformat
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| 245 | 1 | 0 | |a Stability and robustness in data-driven predictive control |c Julian Berberich ; Hauptberichter: Prof. Dr.-Ing. Frank Allgöwer |
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| 520 | 3 | |a Spray polymerisation has a long time been discussed as a promising process, yet, with little knowledge on cause-and-effect relationships between drying and chemical reactions. This work develops a new single droplet model of combined solution drying and free radical homopolymerisation, based on the method of moments. New, consistent approaches for momentsâ diffusion and the reaction-diffusion system are derived to ensure conservation. Simulations reveal peculiarities of the process such as that, due to drying, polymerisation happens mostly in bulk and monomer evaporation leads to a poor yield. Various process variants and simulation models are discussed. The impact of process parameters is examined by means of numerical DoEs. The second part presents a novel approach for the simulation of structure evolution in suspension drying. The meshfree SPH method is used to model the relevant physical effects on a detailed scale during the first and second drying period. New implementations of physical effects are derived: heat and mass transfer based on linear driving forces, an implicit solution of the heat equation, several approaches for crust formation and a new formulation of surface tension by pairwise forces. The formation of dense structures as well as hollow granules can be simulated. Model parameters influence crust formation during the second drying period concerning shape and microporosity and can be interpreted in a physical sense | |
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Datensatz im Suchindex
| _version_ | 1804185282076999680 |
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| adam_txt | |
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| author | Berberich, Julian |
| author_GND | (DE-588)1274267064 (DE-588)143665820 |
| author_facet | Berberich, Julian |
| author_role | aut |
| author_sort | Berberich, Julian |
| author_variant | j b jb |
| building | Verbundindex |
| bvnumber | BV049011594 |
| classification_rvk | ZQ 5290 |
| ctrlnum | (DE-599)KXP1822474345 |
| dewey-full | 629.8312 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 629 - Other branches of engineering |
| dewey-raw | 629.8312 |
| dewey-search | 629.8312 |
| dewey-sort | 3629.8312 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Mess-/Steuerungs-/Regelungs-/Automatisierungstechnik / Mechatronik |
| discipline_str_mv | Mess-/Steuerungs-/Regelungs-/Automatisierungstechnik / Mechatronik |
| format | Thesis Book |
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| illustrated | Not Illustrated |
| index_date | 2024-07-03T22:11:48Z |
| indexdate | 2024-07-10T09:52:45Z |
| institution | BVB |
| isbn | 9783832555313 |
| language | English |
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| spelling | Berberich, Julian Verfasser (DE-588)1274267064 aut Stability and robustness in data-driven predictive control Julian Berberich ; Hauptberichter: Prof. Dr.-Ing. Frank Allgöwer Berlin Logos Verlag [2022] xvi, 247 Seiten Diagramme txt rdacontent n rdamedia nc rdacarrier Dissertation Universität Stuttgart 2022 Spray polymerisation has a long time been discussed as a promising process, yet, with little knowledge on cause-and-effect relationships between drying and chemical reactions. This work develops a new single droplet model of combined solution drying and free radical homopolymerisation, based on the method of moments. New, consistent approaches for momentsâ diffusion and the reaction-diffusion system are derived to ensure conservation. Simulations reveal peculiarities of the process such as that, due to drying, polymerisation happens mostly in bulk and monomer evaporation leads to a poor yield. Various process variants and simulation models are discussed. The impact of process parameters is examined by means of numerical DoEs. The second part presents a novel approach for the simulation of structure evolution in suspension drying. The meshfree SPH method is used to model the relevant physical effects on a detailed scale during the first and second drying period. New implementations of physical effects are derived: heat and mass transfer based on linear driving forces, an implicit solution of the heat equation, several approaches for crust formation and a new formulation of surface tension by pairwise forces. The formation of dense structures as well as hollow granules can be simulated. Model parameters influence crust formation during the second drying period concerning shape and microporosity and can be interpreted in a physical sense Archivierung/Langzeitarchivierung gewährleistet 2022 DISS pdager DE-93 Modellprädiktive Regelung (DE-588)1135937567 gnd rswk-swf Regelkreis (DE-588)4133165-5 gnd rswk-swf Robustheit (DE-588)4126481-2 gnd rswk-swf Reglerentwurf (DE-588)4177447-4 gnd rswk-swf Stabilität (DE-588)4056693-6 gnd rswk-swf Datenbasierte Regelung Lernende Systeme Prädiktive Regelung Regelungstechnik Systemtheorie Angewandte Mathematik Energietechnik, Elektrotechnik und Energiemaschinenbau Maschinelles Lernen Optimierung Sensoren (DE-588)4113937-9 Hochschulschrift gnd-content Modellprädiktive Regelung (DE-588)1135937567 s Reglerentwurf (DE-588)4177447-4 s Regelkreis (DE-588)4133165-5 s Robustheit (DE-588)4126481-2 s Stabilität (DE-588)4056693-6 s DE-604 Allgöwer, Frank 1962- (DE-588)143665820 dgs Stuttgart (DE-588)4058282-6 gnd uvp |
| spellingShingle | Berberich, Julian Stability and robustness in data-driven predictive control Modellprädiktive Regelung (DE-588)1135937567 gnd Regelkreis (DE-588)4133165-5 gnd Robustheit (DE-588)4126481-2 gnd Reglerentwurf (DE-588)4177447-4 gnd Stabilität (DE-588)4056693-6 gnd |
| subject_GND | (DE-588)1135937567 (DE-588)4133165-5 (DE-588)4126481-2 (DE-588)4177447-4 (DE-588)4056693-6 (DE-588)4113937-9 |
| title | Stability and robustness in data-driven predictive control |
| title_auth | Stability and robustness in data-driven predictive control |
| title_exact_search | Stability and robustness in data-driven predictive control |
| title_exact_search_txtP | Stability and robustness in data-driven predictive control |
| title_full | Stability and robustness in data-driven predictive control Julian Berberich ; Hauptberichter: Prof. Dr.-Ing. Frank Allgöwer |
| title_fullStr | Stability and robustness in data-driven predictive control Julian Berberich ; Hauptberichter: Prof. Dr.-Ing. Frank Allgöwer |
| title_full_unstemmed | Stability and robustness in data-driven predictive control Julian Berberich ; Hauptberichter: Prof. Dr.-Ing. Frank Allgöwer |
| title_short | Stability and robustness in data-driven predictive control |
| title_sort | stability and robustness in data driven predictive control |
| topic | Modellprädiktive Regelung (DE-588)1135937567 gnd Regelkreis (DE-588)4133165-5 gnd Robustheit (DE-588)4126481-2 gnd Reglerentwurf (DE-588)4177447-4 gnd Stabilität (DE-588)4056693-6 gnd |
| topic_facet | Modellprädiktive Regelung Regelkreis Robustheit Reglerentwurf Stabilität Hochschulschrift |
| work_keys_str_mv | AT berberichjulian stabilityandrobustnessindatadrivenpredictivecontrol AT allgowerfrank stabilityandrobustnessindatadrivenpredictivecontrol |