Modelling and control of systems with flow

S. van Mourik

    Research output: ThesisPhD Thesis - Research UT, graduation UT

    63 Downloads (Pure)

    Abstract

    In practice, feedback control design consists of three steps: modelling, model reduction and controller design for the reduced model. Systems with flow are often complicated, and there is yet no standard algorithm that integrates these steps. In this thesis we make a modest effort by considering two applications: climate control for food storage, and UV disinfection of fluids. The goal is twofold. First, the aim is to come to a controller design that is practically relevant. The controller has to easy implementable and of high quality. Second, we try to retain as much physical information from the system as possible. The advantage of a controller that contains physical information lies in the time saving when designing the system and the controller simultaneously. For the food storage room a realistic but relatively simple model is derived. This model is validated and calibrated by experimental results. The factors that stand in the way of standard model reduction and controller design, are air flow and the input that is not continuous, but switches between two values. Via a combination of standard model reduction techniques (Pad\'{e} approximation, linearization, timescale decomposition) the system is reduced to a first order linear system with the switching time as input. For this, a simple and high quality controller is designed. The controller is tested successfully on the basic model. The system dynamics is parameterized by the physical properties of the system, which can give great numerical advantages for the system design. For a UV disinfection reactor a realistic basic model is derived. The factors that stand in the way of standard model reduction and controller design, are flow, nonlinear input, and the extremely large state space that is needed for an accurate discretisation. Via a combination of standard model reduction techniques (Pad\'{e} approximation, linearization, input/output balancing) the system is reduced to a first order linear system. For this, a simple and high quality controller is designed. The controller is tested successfully on the basic model. A drawback is that the input/output balancing does not retain any physical system information. Further, the model describes a very specific case. As an alternative, a modelling technique is designed that uses the measured residence time distribution. The advantage here is that the resulting model is linear and suited for practical controller design. Moreover, the model is automatically calibrated to the experimental data that it is based on. The drawback is that the model does not hold any physical system information.
    Original languageUndefined
    Awarding Institution
    • University of Twente
    Supervisors/Advisors
    • Zwart, Heiko J., Advisor
    • Keesman, K.J., Advisor
    • Bagchi, Arunabha, Supervisor
    Thesis sponsors
    Award date29 Feb 2008
    Place of PublicationEnschede
    Publisher
    Print ISBNs978-90-365-2617-3
    DOIs
    Publication statusPublished - 29 Feb 2008

    Keywords

    • EWI-12051
    • METIS-250893
    • IR-58695

    Cite this

    van Mourik, S. (2008). Modelling and control of systems with flow. Enschede: University of Twente. https://doi.org/10.3990/1.9789036526173
    van Mourik, S.. / Modelling and control of systems with flow. Enschede : University of Twente, 2008. 146 p.
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    abstract = "In practice, feedback control design consists of three steps: modelling, model reduction and controller design for the reduced model. Systems with flow are often complicated, and there is yet no standard algorithm that integrates these steps. In this thesis we make a modest effort by considering two applications: climate control for food storage, and UV disinfection of fluids. The goal is twofold. First, the aim is to come to a controller design that is practically relevant. The controller has to easy implementable and of high quality. Second, we try to retain as much physical information from the system as possible. The advantage of a controller that contains physical information lies in the time saving when designing the system and the controller simultaneously. For the food storage room a realistic but relatively simple model is derived. This model is validated and calibrated by experimental results. The factors that stand in the way of standard model reduction and controller design, are air flow and the input that is not continuous, but switches between two values. Via a combination of standard model reduction techniques (Pad\'{e} approximation, linearization, timescale decomposition) the system is reduced to a first order linear system with the switching time as input. For this, a simple and high quality controller is designed. The controller is tested successfully on the basic model. The system dynamics is parameterized by the physical properties of the system, which can give great numerical advantages for the system design. For a UV disinfection reactor a realistic basic model is derived. The factors that stand in the way of standard model reduction and controller design, are flow, nonlinear input, and the extremely large state space that is needed for an accurate discretisation. Via a combination of standard model reduction techniques (Pad\'{e} approximation, linearization, input/output balancing) the system is reduced to a first order linear system. For this, a simple and high quality controller is designed. The controller is tested successfully on the basic model. A drawback is that the input/output balancing does not retain any physical system information. Further, the model describes a very specific case. As an alternative, a modelling technique is designed that uses the measured residence time distribution. The advantage here is that the resulting model is linear and suited for practical controller design. Moreover, the model is automatically calibrated to the experimental data that it is based on. The drawback is that the model does not hold any physical system information.",
    keywords = "EWI-12051, METIS-250893, IR-58695",
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    van Mourik, S 2008, 'Modelling and control of systems with flow', University of Twente, Enschede. https://doi.org/10.3990/1.9789036526173

    Modelling and control of systems with flow. / van Mourik, S.

    Enschede : University of Twente, 2008. 146 p.

    Research output: ThesisPhD Thesis - Research UT, graduation UT

    TY - THES

    T1 - Modelling and control of systems with flow

    AU - van Mourik, S.

    N1 - 10.3990/1.9789036526173

    PY - 2008/2/29

    Y1 - 2008/2/29

    N2 - In practice, feedback control design consists of three steps: modelling, model reduction and controller design for the reduced model. Systems with flow are often complicated, and there is yet no standard algorithm that integrates these steps. In this thesis we make a modest effort by considering two applications: climate control for food storage, and UV disinfection of fluids. The goal is twofold. First, the aim is to come to a controller design that is practically relevant. The controller has to easy implementable and of high quality. Second, we try to retain as much physical information from the system as possible. The advantage of a controller that contains physical information lies in the time saving when designing the system and the controller simultaneously. For the food storage room a realistic but relatively simple model is derived. This model is validated and calibrated by experimental results. The factors that stand in the way of standard model reduction and controller design, are air flow and the input that is not continuous, but switches between two values. Via a combination of standard model reduction techniques (Pad\'{e} approximation, linearization, timescale decomposition) the system is reduced to a first order linear system with the switching time as input. For this, a simple and high quality controller is designed. The controller is tested successfully on the basic model. The system dynamics is parameterized by the physical properties of the system, which can give great numerical advantages for the system design. For a UV disinfection reactor a realistic basic model is derived. The factors that stand in the way of standard model reduction and controller design, are flow, nonlinear input, and the extremely large state space that is needed for an accurate discretisation. Via a combination of standard model reduction techniques (Pad\'{e} approximation, linearization, input/output balancing) the system is reduced to a first order linear system. For this, a simple and high quality controller is designed. The controller is tested successfully on the basic model. A drawback is that the input/output balancing does not retain any physical system information. Further, the model describes a very specific case. As an alternative, a modelling technique is designed that uses the measured residence time distribution. The advantage here is that the resulting model is linear and suited for practical controller design. Moreover, the model is automatically calibrated to the experimental data that it is based on. The drawback is that the model does not hold any physical system information.

    AB - In practice, feedback control design consists of three steps: modelling, model reduction and controller design for the reduced model. Systems with flow are often complicated, and there is yet no standard algorithm that integrates these steps. In this thesis we make a modest effort by considering two applications: climate control for food storage, and UV disinfection of fluids. The goal is twofold. First, the aim is to come to a controller design that is practically relevant. The controller has to easy implementable and of high quality. Second, we try to retain as much physical information from the system as possible. The advantage of a controller that contains physical information lies in the time saving when designing the system and the controller simultaneously. For the food storage room a realistic but relatively simple model is derived. This model is validated and calibrated by experimental results. The factors that stand in the way of standard model reduction and controller design, are air flow and the input that is not continuous, but switches between two values. Via a combination of standard model reduction techniques (Pad\'{e} approximation, linearization, timescale decomposition) the system is reduced to a first order linear system with the switching time as input. For this, a simple and high quality controller is designed. The controller is tested successfully on the basic model. The system dynamics is parameterized by the physical properties of the system, which can give great numerical advantages for the system design. For a UV disinfection reactor a realistic basic model is derived. The factors that stand in the way of standard model reduction and controller design, are flow, nonlinear input, and the extremely large state space that is needed for an accurate discretisation. Via a combination of standard model reduction techniques (Pad\'{e} approximation, linearization, input/output balancing) the system is reduced to a first order linear system. For this, a simple and high quality controller is designed. The controller is tested successfully on the basic model. A drawback is that the input/output balancing does not retain any physical system information. Further, the model describes a very specific case. As an alternative, a modelling technique is designed that uses the measured residence time distribution. The advantage here is that the resulting model is linear and suited for practical controller design. Moreover, the model is automatically calibrated to the experimental data that it is based on. The drawback is that the model does not hold any physical system information.

    KW - EWI-12051

    KW - METIS-250893

    KW - IR-58695

    U2 - 10.3990/1.9789036526173

    DO - 10.3990/1.9789036526173

    M3 - PhD Thesis - Research UT, graduation UT

    SN - 978-90-365-2617-3

    PB - University of Twente

    CY - Enschede

    ER -

    van Mourik S. Modelling and control of systems with flow. Enschede: University of Twente, 2008. 146 p. https://doi.org/10.3990/1.9789036526173