Dissertation/ Thesis
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Direct data-driven control : from linear systems to piecewise affine systems

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Direct data-driven control : from linear systems to piecewise affine systems
Συγγραφείς: Hu, Kaijian, 胡凯建
Στοιχεία εκδότη: The University of Hong Kong (Pokfulam, Hong Kong)
Έτος έκδοσης: 2024
Συλλογή: University of Hong Kong: HKU Scholars Hub
Θεματικοί όροι: Automatic control - Data processing
Περιγραφή: Motivated by the challenges of obtaining accurate system models and the convenience of collecting system data, direct data-driven control (DDC) is becoming increasingly popular in the control community. Compared with model-based control methods, DDC approaches aim to design controllers from data directly, bypassing the construction of the system model. This thesis addresses several new challenges in developing DDC methods for unknown systems, ranging from linear time-invariant (LTI) to piecewise affine (PWA) systems. Firstly, this thesis studies the DDC problem for LTI systems with unmeasurable states. A data-driven output feedback controller is designed using input-output data. Specifically, a novel dimension reduction method is proposed to construct a state using the original input and compressed output. The state-space model based on this new state is proven to be controllable, which enables the construction of a data-based state-space representation with the same input-output relationship as the original system using the pre-collected input-output data. This representation is then used to form a group of data-dependent linear matrix inequalities (LMIs), which are further used to calculate the output feedback control gain. Secondly, this thesis studies the robust DDC problem for LTI systems with unknown and bounded disturbances. A robust data-driven controller is designed to guarantee internal stability and prescribed $H_\infty$ control performance using input-state-output or input-output data, depending on whether the state is measurable. This method first constructs a set containing all systems that can generate the pre-collected input-state-output data and then designs a controller for all systems in the set. To reduce the conservativeness caused by a single dataset, multiple datasets are used in the controller design. Additionally, the obtained results are extended to the autoregressive exogenous (ARX) systems using only input-output data. Thirdly, this thesis studies the data-driven predictive control ...
Τύπος εγγράφου: doctoral or postdoctoral thesis
Γλώσσα: English
Relation: HKU Theses Online (HKUTO); 991044869879903414; https://hub.hku.hk/handle/10722/351018
Διαθεσιμότητα: https://hub.hku.hk/handle/10722/351018
Rights: The author retains all proprietary rights, (such as patent rights) and the right to use in future works. ; This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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Items – Name: Title
  Label: Title
  Group: Ti
  Data: Direct data-driven control : from linear systems to piecewise affine systems
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Hu%2C+Kaijian%22">Hu, Kaijian</searchLink><br /><searchLink fieldCode="AR" term="%22胡凯建%22">胡凯建</searchLink>
– Name: Publisher
  Label: Publisher Information
  Group: PubInfo
  Data: The University of Hong Kong (Pokfulam, Hong Kong)
– Name: DatePubCY
  Label: Publication Year
  Group: Date
  Data: 2024
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  Label: Collection
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  Data: University of Hong Kong: HKU Scholars Hub
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  Data: <searchLink fieldCode="DE" term="%22Automatic+control+-+Data+processing%22">Automatic control - Data processing</searchLink>
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  Label: Description
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  Data: Motivated by the challenges of obtaining accurate system models and the convenience of collecting system data, direct data-driven control (DDC) is becoming increasingly popular in the control community. Compared with model-based control methods, DDC approaches aim to design controllers from data directly, bypassing the construction of the system model. This thesis addresses several new challenges in developing DDC methods for unknown systems, ranging from linear time-invariant (LTI) to piecewise affine (PWA) systems. Firstly, this thesis studies the DDC problem for LTI systems with unmeasurable states. A data-driven output feedback controller is designed using input-output data. Specifically, a novel dimension reduction method is proposed to construct a state using the original input and compressed output. The state-space model based on this new state is proven to be controllable, which enables the construction of a data-based state-space representation with the same input-output relationship as the original system using the pre-collected input-output data. This representation is then used to form a group of data-dependent linear matrix inequalities (LMIs), which are further used to calculate the output feedback control gain. Secondly, this thesis studies the robust DDC problem for LTI systems with unknown and bounded disturbances. A robust data-driven controller is designed to guarantee internal stability and prescribed $H_\infty$ control performance using input-state-output or input-output data, depending on whether the state is measurable. This method first constructs a set containing all systems that can generate the pre-collected input-state-output data and then designs a controller for all systems in the set. To reduce the conservativeness caused by a single dataset, multiple datasets are used in the controller design. Additionally, the obtained results are extended to the autoregressive exogenous (ARX) systems using only input-output data. Thirdly, this thesis studies the data-driven predictive control ...
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  Data: doctoral or postdoctoral thesis
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  Data: The author retains all proprietary rights, (such as patent rights) and the right to use in future works. ; This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
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    Languages:
      – Text: English
    Subjects:
      – SubjectFull: Automatic control - Data processing
        Type: general
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      – TitleFull: Direct data-driven control : from linear systems to piecewise affine systems
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            NameFull: 胡凯建
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              Y: 2024
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