no code implementations • 11 Apr 2024 • Audrey Blizard, Colin N. Jones, Stephanie Stockar
The demand-side control of district heating networks is notoriously challenging due to the large number of connected users and the high number of states to be considered.
no code implementations • 8 Feb 2024 • Wenjie Xu, Wenbin Wang, Yuning Jiang, Bratislav Svetozarevic, Colin N. Jones
We study the problem of preferential Bayesian optimization (BO), where we aim to optimize a black-box function with only preference feedback over a pair of candidate solutions.
1 code implementation • 23 Nov 2023 • Loris Di Natale, Muhammad Zakwan, Philipp Heer, Giancarlo Ferrari Trecate, Colin N. Jones
This manuscript details the SIMBa toolbox (System Identification Methods leveraging Backpropagation), which uses well-established Machine Learning tools for discrete-time linear multi-step-ahead state-space System Identification (SI).
no code implementations • 9 Nov 2023 • Paul Scharnhorst, Baptiste Schubnel, Rafael E. Carrillo, Pierre-Jean Alet, Colin N. Jones
Residential and commercial buildings, equipped with systems such as heat pumps, hot water tanks, or stationary energy storage, have a large potential to offer their consumption flexibility as grid services.
1 code implementation • 6 Nov 2023 • Loris Di Natale, Muhammad Zakwan, Bratislav Svetozarevic, Philipp Heer, Giancarlo Ferrari-Trecate, Colin N. Jones
Machine Learning (ML) and linear System Identification (SI) have been historically developed independently.
no code implementations • 2 Oct 2023 • Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic, Colin N. Jones
Additionally, the algorithm guarantees an $\mathcal{O}(N\sqrt{T})$ bound on the cumulative violation for the known affine constraints, where $N$ is the number of agents.
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.
no code implementations • 8 Sep 2023 • Kristína Fedorová, Yuning Jiang, Juraj Oravec, Colin N. Jones, Michal Kvasnica
Most of the real-time implementations of the stabilizing optimal control actions suffer from the necessity to provide high computational effort.
no code implementations • 25 Aug 2023 • Xinliang Dai, Junyi Zhai, Yuning Jiang, Yi Guo, Colin N. Jones, Veit Hagenmeyer
This paper introduces a distributed operational solution for coordinating integrated transmission-distribution (ITD) systems regarding data privacy.
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.
no code implementations • 8 Jun 2023 • Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic, Colin N. Jones
We consider the problem of optimizing a grey-box objective function, i. e., nested function composed of both black-box and white-box functions.
no code implementations • 1 May 2023 • Manuel Koch, Colin N. Jones
Data-enabled predictive control (DeePC) is a recently established form of Model Predictive Control (MPC), based on behavioral systems theory.
1 code implementation • 12 Apr 2023 • Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic, Colin N. Jones
This paper studies the problem of online performance optimization of constrained closed-loop control systems, where both the objective and the constraints are unknown black-box functions affected by exogenous time-varying contextual disturbances.
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.
no code implementations • 30 Nov 2022 • Loris Di Natale, Bratislav Svetozarevic, Philipp Heer, Colin N. Jones
Model-free Reinforcement Learning (RL) generally suffers from poor sample complexity, mostly due to the need to exhaustively explore the state-action space to find well-performing policies.
no code implementations • 21 Nov 2022 • Wenjie Xu, Yuning Jiang, Bratislav Svetozarevic, Colin N. Jones
In this paper, the CONFIG algorithm, a simple and provably efficient constrained global optimization algorithm, is applied to optimize the closed-loop control performance of an unknown system with unmodeled constraints.
no code implementations • 11 Nov 2022 • Muhammad Zakwan, Loris Di Natale, Bratislav Svetozarevic, Philipp Heer, Colin N. Jones, Giancarlo Ferrari Trecate
Since IPHS models are consistent with the first and second principles of thermodynamics by design, so are the proposed Physically Consistent NODEs (PC-NODEs).
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 • 7 Oct 2022 • Paul Scharnhorst, Baptiste Schubnel, Rafael E. Carrillo, Pierre-Jean Alet, Colin N. Jones
Buildings are a promising source of flexibility for the application of demand response.
no code implementations • 20 Sep 2022 • Wenjie Xu, Yuning Jiang, Emilio T. Maddalena, Colin N. Jones
In this paper, we study the worst-case complexity of the efficient global optimization problem and, in contrast to existing kernel-specific results, we derive a unified lower bound for the complexity of efficient global optimization in terms of the metric entropy of a ball in its corresponding reproducing kernel Hilbert space~(RKHS).
1 code implementation • 27 Jun 2022 • Roland Schwan, Colin N. Jones, Daniel Kuhn
We provide sufficient conditions for the closed-loop stability of the candidate policy in terms of the worst-case approximation error with respect to the baseline policy, and we show that these conditions can be checked by solving a Mixed-Integer Quadratic Program (MIQP).
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 • 29 Mar 2022 • Peng Yang, Yuning Jiang, Ting Wang, Yong Zhou, Yuanming Shi, Colin N. Jones
To address this issue, in this paper, we instead propose a novel over-the-air second-order federated optimization algorithm to simultaneously reduce the communication rounds and enable low-latency global model aggregation.
1 code implementation • 10 Mar 2022 • Loris Di Natale, Bratislav Svetozarevic, Philipp Heer, Colin N. Jones
Replacing poorly performing existing controllers with smarter solutions will decrease the energy intensity of the building sector.
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.
1 code implementation • 24 Jan 2022 • Wenzhi Fang, Ziyi Yu, Yuning Jiang, Yuanming Shi, Colin N. Jones, Yong Zhou
Under non-convex settings, we derive the convergence performance of the FedZO algorithm on non-independent and identically distributed data and characterize the impact of the numbers of local iterates and participating edge devices on the convergence.
no code implementations • 14 Dec 2021 • Emilio T. Maddalena, Silvio A. Muller, Rafael M. dos Santos, Christophe Salzmann, Colin N. Jones
Herein we report a multi-zone, heating, ventilation and air-conditioning (HVAC) control case study of an industrial plant responsible for cooling a hospital surgery center.
1 code implementation • 6 Dec 2021 • Loris Di Natale, Bratislav Svetozarevic, Philipp Heer, Colin N. Jones
To counter this known generalization issue, physics-informed NNs have recently been introduced, where researchers introduce prior knowledge in the structure of NNs to ground them in known underlying physical laws and avoid classical NN generalization issues.
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.
1 code implementation • 19 Apr 2021 • Paul Scharnhorst, Emilio T. Maddalena, Yuning Jiang, Colin N. Jones
The problem of establishing out-of-sample bounds for the values of an unkonwn ground-truth function is considered.
no code implementations • 12 Feb 2021 • Yinghao Lian, Colin N. Jones
Inspired by this observation, a robust closed-loop data-enabled predictive control scheme is proposed for stochastic LTI systems.
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.
1 code implementation • 10 Aug 2020 • Emilio T. Maddalena, Paul Scharnhorst, Colin N. Jones
We consider the problem of reconstructing a function from a finite set of noise-corrupted samples.
no code implementations • 8 Jun 2020 • Prabhat K. Mishra, Sanket S. Diwale, Colin N. Jones, Debasish Chatterjee
A stochastic model predictive control framework over unreliable Bernoulli communication channels, in the presence of unbounded process noise and under bounded control inputs, is presented for tracking a reference signal.
Optimization and Control