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Data-driven model reference control in the frequency-domain From model reference selection to controller validation

Abstract : In many applications, no physical description of the plant is easily available and the control law has to be designed on the basis of input-output measurements only. Two control strategies can then be considered : one can either identify a model of the plant and then use any kind of model-based technique (indirect methods) to obtain a control law, or use a data-driven strategy that directly compute the controller from the experimental data (direct methods). This work focuses on data-driven techniques : the objective of this thesis is to propose a new data-driven control technique based on frequency-domain data collected from the system to be controlled. After recalling some basics in feedback control, an overview of data-driven control is given. Then, the proposed method is introduced. It is a model reference technique where the identification problem is moved from the plant to the controller. In this work, two identification techniques are used to that purpose: the Loewner framework and the subspace approach. In addition, a preliminary analysis of the available frequency-domain data allows determining the performance limitations and selecting achievable specifications. Finally, a stability condition, already known in data-driven control, is used during the reduction of the controller to ensure closed-loop internal stability. Along this thesis, the different steps of the method are progressively applied on two numercial examples. In the end, the proposed technique is applied on two irrational systems described by partial differential equations: a continuous crystallizer and an open-channel for hydroelectricity generation. These two examples illustrate the type of applications for which using a data-driven control method is indicated.
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Submitted on : Monday, January 13, 2020 - 5:21:14 PM
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Pauline Kergus. Data-driven model reference control in the frequency-domain From model reference selection to controller validation. Automatic. Institut Supérieur de l'Aéronautique et de l'Espace (ISAE-SUPAERO), 2019. English. ⟨tel-02437362v1⟩



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