| Autor: |
Lian, Yingzhao, Shi, Jicheng, Jones, Colin N. |
| Rok vydání: |
2023 |
| Předmět: |
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| Zdroj: |
IEEE Control Systems Letters 7 (2023): 1885 - 1890 |
| Druh dokumentu: |
Working Paper |
| DOI: |
10.1109/LCSYS.2023.3282987 |
| Popis: |
(Extended Version) Data-driven control can facilitate the rapid development of controllers, offering an alternative to conventional approaches. In order to maintain consistency between any known underlying physical laws and a data-driven decision-making process, preprocessing of raw data is necessary to account for measurement noise and any inconsistencies it may introduce. In this paper, we present a physics-based filter to achieve this and demonstrate its effectiveness through practical applications, using real-world datasets collected in a building on the Ecole Polytechnique Federale de Lausanne (EPFL) campus. Two distinct use cases are explored: indoor temperature control and demand response bidding. |
| Databáze: |
arXiv |
| Externí odkaz: |
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