Lian, YingzhaoShi, JichengJones, Colin N.2023-07-172023-07-172023-07-172023-01-0110.1109/LCSYS.2023.3282987https://infoscience.epfl.ch/handle/20.500.14299/199113WOS:001012654500002Data-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 letter, 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.Automation & Control SystemsAutomation & Control Systemsphysics consistencydata-driven methodfiltertext::journal::journal article::research article