Publications de Jicheng Shi | EPFL Graph Search

Chattez avec Graph Search

Posez n’importe quelle question sur les cours, conférences, exercices, recherches, actualités, etc. de l’EPFL ou essayez les exemples de questions ci-dessous.

AVERTISSEMENT : Le chatbot Graph n'est pas programmé pour fournir des réponses explicites ou catégoriques à vos questions. Il transforme plutôt vos questions en demandes API qui sont distribuées aux différents services informatiques officiellement administrés par l'EPFL. Son but est uniquement de collecter et de recommander des références pertinentes à des contenus que vous pouvez explorer pour vous aider à répondre à vos questions.

Data-driven control approaches for the minimization of energy consumption of buildings have the potential to significantly reduce deployment costs and increase the uptake of advanced control in this sector. A number of recent approaches based on the applic ...

In the field of model predictive control, Dataenabled Predictive Control (DeePC) offers direct predictive control, bypassing traditional modeling. However, challenges emerge with increased computational demand due to recursive data updates. This paper intr ...

Noise pollution from heat pumps (HPs) has been an emerging concern to their broader adoption, especially in densely populated areas. This paper explores a model predictive control (MPC) approach for climate control of buildings, aimed at minimizing the noi ...

By providing various services, such as Incentive-based Demand Response (IBDR), buildings can play a crucial role in the energy market due to their significant energy consumption. However, effectively commissioning buildings for such desired functionalities ...

This letter proposes a data-driven input reconstruction method from outputs (IRO) based on the Willems' Fundamental Lemma. Given only output measurements, the unknown inputsestimated recursively by the IRO asymptotically converge to the true input without ...

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, preprocessin ...

This manuscript offers the perspective of experimentalists on a number of modern data-driven techniques: model predictive control relying on Gaussian processes, adaptive data-driven control based on behavioral theory, and deep reinforcement learning. These ...

Jicheng Shi

Chattez avec Graph Search

Adaptive Robust Data-Driven Building Control via Bilevel Reformulation: An Experimental Result

Efficient Recursive Data-enabled Predictive Control

Model predictive building climate control for mitigating heat pump noise pollution

Adaptive data-driven prediction in a building control hierarchy: A case study of demand response in Switzerland

Data-Driven Input Reconstruction and Experimental Validation

Physically Consistent Multiple-Step Data-Driven Predictions Using Physics-Based Filters

Lessons Learned from Data-Driven Building Control Experiments: Contrasting Gaussian Process-based MPC, Bilevel DeePC, and Deep Reinforcement Learning