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Stochastic Model Predictive Control for Building Climate Control

Related publications (28)

Optimal Linear Controller for Minimizing DC Voltage Oscillations in MMC-Based Offshore Multiterminal HVDC Grids

The paper aims at minimizing DC voltage oscillations in offshore multiterminal high-voltage direct current (HVDC) grids based on modular multilevel converters (MMCs). The DC voltage stability is a crucial factor in multiterminal HVDC networks since it is a ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Pretraining boosts out-of-domain robustness for pose estimation

Mackenzie Mathis, Alexander Mathis, Steffen Schneider, Thomas Ray Biasi, Mert Yüksekgönül, Matthias Bethge

Neural networks are highly effective tools for pose estimation. However, as in other computer vision tasks, robustness to out-of-domain data remains a challenge, especially for small training sets that are common for real-world applications. Here, we probe ...

IEEE COMPUTER SOC2021

Whole Body Model Predictive Control with a Memory of Motion: Experiments on a Torque-Controlled Talos

Sylvain Calinon, Rohan Budhiraja, Teguh Santoso Lembono

This paper presents the first successful experiment implementing whole-body model predictive control with state feedback on a torque-control humanoid robot. We demonstrate that our control scheme is able to do whole-body target tracking, control the balanc ...

IEEE2021

Review of control strategies for lower-limb exoskeletons to assist gait

Mohamed Bouri, Auke Ijspeert, Romain Pierre François Baud, Ali Reza Manzoori

Background Many lower-limb exoskeletons have been developed to assist gait, exhibiting a large range of control methods. The goal of this paper is to review and classify these control strategies, that determine how these devices interact with the user. Met ...

BioMed Central2021

Data-driven methods for building control - A review and promising future directions

Colin Neil Jones, Yingzhao Lian, Emilio Maddalena

A review of the heating, ventilation and air-conditioning control problem for buildings is presented with particular emphasis on its distinguishing features. Next, we not only examine how data-driven algorithms have been exploited to tackle the main challe ...

2020

Actor neural networks for the robust control of partially measured nonlinear systems showcased for image propagation through diffuse media

Navid Borhani, Demetri Psaltis, Christophe Moser, Damien Claude-Marie Loterie, Babak Rahmani, Eirini Kakkava, Ugur Tegin

The output of physical systems, such as the scrambled pattern formed by shining the spot of a laser pointer through fog, is often easily accessible by direct measurements. However, selection of the input of such a system to obtain a desired output is diffi ...

SPRINGERNATURE2020

Data driven model free adaptive iterative learning perimeter control for large-scale urban road networks

Nikolaos Geroliminis, Isik Ilber Sirmatel, Ye Ren

Most perimeter control methods in literature are the model-based schemes designing the controller based on the available accurate macroscopic fundamental diagram (MFD) function with well known techniques of modern control methods. However, accurate modelin ...

2020

From human action understanding to robot action execution: how the physical properties of handled objects modulate non-verbal cues

Aude Billard, José Santos-Victor, Konstantinos Chatzilygeroudis, Nuno Ricardo Ferreira Duarte

Humans manage to communicate action intentions in a non-verbal way, through body posture and movement. We start from this observation to investigate how a robot can decode a human's non-verbal cues during the manipulation of an object, with specific physic ...

IEEE2020