07 Fakultät Konstruktions-, Produktions- und Fahrzeugtechnik

Permanent URI for this collectionhttps://elib.uni-stuttgart.de/handle/11682/8

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Publication Type: search.filters.UBSTyp.ZeitschriftenartikelAuthor: search.filters.author.Allgöwer, Frank

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    Moment dynamics of Zirconia particle formation for optimizing particle size distribution
    (2019) Halter, Wolfgang; Eisele, Rahel; Rothenstein, Dirk; Bill, Joachim; Allgöwer, Frank
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    Schneller sehen durch Regelungstechnik - Moderne Bildgebung in der Nanotechnologie
    (2004) Rieber, Jochen M.; Allgöwer, Frank; Stemmer, Andreas
    Die Nanotechnologie, also die Wissenschaft von Untersuchungen und Manipulationen im Nanometermaßstab, wird als eine der Schlüsseltechnologien des 21. Jahrhunderts angesehen. Wichtige Komponenten dieses aktuellen Forschungszweiges sind das Rastertunnelmikroskop und das Rasterkraftmikroskop, die den Blick in die Nanowelt erlauben. Dieser Artikel gibt einen einführenden Einblick in die Bildgebung der Nanowelt und versucht, den Beitrag von Systemtheorie und Regelungstechnik für die Nanotechnologie anhand der Regelung von Rasterkraftmikroskopen allgemeinverständlich zu beschreiben.
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    μ-Suboptimal design of a robustly performing controller for a chemical reactor
    (1994) Amann, Notker; Allgöwer, Frank
    The design of robustly performing controllers for an important class of control problems is treated. The problem is dealt with in the structured singular value (μ)-framework. The systems considered are characterized by weak nonlinearities and parametric and unstructured uncertainties. Nonlinear effects are taken into account via linearization families. Parametric uncertainty is included in a non-conservative way. Both lead to a μ-synthesis problem with repeated scalar real perturbations. As no direct solution to such a μ-synthesis problem is known to date, an iterative approach comprising both μ-analysis of the actual problem and D-K-iteration for a modified problem is shown. This approach is applied to a realistic continuous stirred-tank reactor for production of cyclopen-tenol to show the applicability to non-trivial MIMO process control problems.
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    Model Predictive Control for flexible job shop scheduling in Industry 4.0
    (2021) Wenzelburger, Philipp; Allgöwer, Frank
    In the context of Industry 4.0, flexible manufacturing systems play an important role. They are designed to provide the possibility to adapt the production process by reacting to changes and enabling customer specific products. The versatility of such manufacturing systems, however, also needs to be exploited by advanced control strategies. To this end, we present a novel scheduling scheme that is able to flexibly react to changes in the manufacturing system by means of Model Predictive Control (MPC). To introduce flexibility from the start, the initial scheduling problem, which is very general and covers a variety of special cases, is formulated in a modular way. This modularity is then preserved during an automatic transformation into a Petri Net formulation, which constitutes the basis for the two presented MPC schemes. We prove that both schemes are guaranteed to complete the production problem in closed loop when reasonable assumptions are fulfilled. The advantages of the presented control framework for flexible manufacturing systems are that it covers a wide variety of scheduling problems, that it is able to exploit the available flexibility of the manufacturing system, and that it allows to prove the completion of the production problem.