no code implementations • 19 Feb 2024 • Yu Zhang, Hui-Ling Zhen, Zehua Pei, Yingzhao Lian, Lihao Yin, Mingxuan Yuan, Bei Yu
In this paper, we propose a novel differential logic layer-aided language modeling (DiLA) approach, where logical constraints are integrated into the forward and backward passes of a network layer, to provide another option for LLM tool learning.
no code implementations • 24 Sep 2023 • Jicheng Shi, Yingzhao Lian, Colin N. Jones
This is exemplified through a comparison to Subspace Predictive Control, where the algorithm achieves asymptotically consistent prediction for stochastic linear time-invariant systems.
2 code implementations • 17 Jul 2023 • Jicheng Shi, Yingzhao Lian, Christophe Salzmann, Colin N. Jones
By providing various services, such as Demand Response (DR), buildings can play a crucial role in the energy market due to their significant energy consumption.
1 code implementation • 20 Mar 2023 • Zachary Morrison, Benjamin P. Russo, Yingzhao Lian, Rushikesh Kamalapurkar
The reliable operation of automatic systems is heavily dependent on the ability to detect faults in the underlying dynamical system.
no code implementations • 16 Mar 2023 • Yingzhao Lian, Jicheng Shi, Colin N. Jones
(Extended Version) Data-driven control can facilitate the rapid development of controllers, offering an alternative to conventional approaches.
1 code implementation • 24 Oct 2022 • Jiawei Wang, Yingzhao Lian, Yuning Jiang, Qing Xu, Keqiang Li, Colin N. Jones
This algorithm achieves both computation and communication efficiency, as well as trajectory data privacy, through parallel calculation.
no code implementations • 21 Jun 2022 • Yingzhao Lian, Yuning Jiang, Daniel F. Opila, Colin N. Jones
The proposed algorithm is validated on a simulation of an HVAC system control.
no code implementations • 12 Jun 2022 • Yingzhao Lian, Yuning Jiang, Colin N. Jones, Daniel F. Opila
Smart home appliances can time-shift and curtail their power demand to assist demand side management or allow operation with limited power, as in an off-grid application.
no code implementations • 31 May 2022 • Loris Di Natale, Yingzhao Lian, Emilio T. Maddalena, Jicheng Shi, Colin N. Jones
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.
1 code implementation • 5 Mar 2022 • Jicheng Shi, Yingzhao Lian, Colin N. Jones
This paper addresses a data-driven input reconstruction problem based on Willems' Fundamental Lemma in which unknown input estimators (UIEs) are constructed directly from historical I/O data.
no code implementations • 1 Dec 2021 • Yingzhao Lian, Yuning Jiang, Naomi Stricker, Lothar Thiele, Colin N. Jones
The wide adoption of wireless devices in the Internet of Things requires controllers that are able to operate with limited resources, such as battery life.
no code implementations • 10 Jun 2021 • Yingzhao Lian, Jicheng Shi, Manuel Koch, Colin Neil Jones
Data-driven control approaches for the minimization of energy consumption of buildings have the potential to significantly reduce deployment costs and increase uptake of advanced control in this sector.
no code implementations • 27 Nov 2020 • Jicheng Shi, Yingzhao Lian, Colin N. Jones
Accounting for more than 40% of global energy consumption, residential and commercial buildings will be key players in any future green energy systems.