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Hybrid Quadratic Programming - Pullback Bundle Dynamical Systems Control

Aude Billard, Bernardo Fichera

Dynamical System (DS)-based closed-loop control is a simple and effective way to generate reactive motion policies that well generalize to the robotic workspace, while retaining stability guarantees. Lately the formalism has been expanded in order to handl ...

SPRINGER INTERNATIONAL PUBLISHING AG2023

Integration of feedforward and feedback control in the neuromechanics of vertebrate locomotion: a review of experimental, simulation and robotic studies

Auke Ijspeert

Animal locomotion is the result of complex and multi-layered interactions between the nervous system, the musculo-skeletal system and the environment. Decoding the underlying mechanisms requires an integrative approach. Comparative experimental biology has ...

Company Biologists Ltd2023

DIET Controller: Dynamic Indoor Environment using Deep Reinforcement Learning

Arnab Chatterjee

Heating, Ventilation, and Air Conditioning (HVAC) Systems utilize much energy, accounting for 40% of total building energy use. The temperatures in buildings are commonly held within narrow limits, leading to higher energy use. Measurements from office bui ...

EPFL2023

Third-harmonic generation monitoring of femtosecond-laser-induced in-volume functional modifications

Christian Enz, Yves Bellouard, Assim Boukhayma, Andrea Kraxner, Olivier Bernard

During the last two decades, ultrafast in-volume laser-based processing of transparent materials has emerged as a key 3D-printing method for manufacturing a variety of complex integrated photonic devices and micro-parts. Yet, identifying suitable laser pro ...

2023

Model Predictive Control for Multi-Agent Systems under Limited Communication and Time-Varying Network Topology

Danilo Saccani, Melanie Nicole Zeilinger

In control system networks, reconfiguration of the controller when agents are leaving or joining the network is still an open challenge, in particular when operation constraints that depend on each agent's behavior must be met. Drawing our motivation from ...

IEEE2023

Data-Driven Control and Optimization under Noisy and Uncertain Conditions

Baiwei Guo

Control systems operating in real-world environments often face disturbances arising from measurement noise and model mismatch. These factors can significantly impact the perfor- mance and safety of the system. In this thesis, we aim to leverage data to de ...

EPFL2023

Data-driven Methods for Control: from Linear to Lifting

Yingzhao Lian

The progress towards intelligent systems and digitalization relies heavily on the use of automation technology. However, the growing diversity of control objects presents significant challenges for traditional control approaches, as they are highly depende ...

EPFL2023

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

Colin Neil Jones, Loris Di Natale, Jicheng Shi, Emilio Maddalena, Yingzhao Lian

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 ...

2023

Modeling and analysis of miniaturized magnetorheological valve for fluidic actuation

Sofia Lydia Ntella

Fluidic actuation enables movement in a wide range of mechanical systems, from simple laboratory devices to more complex industrial machinery. Fluids are used to generate motion of mechanical pieces. The term "fluids" encompasses two types of technologies: ...

EPFL2023

Surfactant Treatment for Efficient Gene Detection of Enteric Viruses and Indicators in Surface Water Concentrated by Ultrafiltration

Shotaro Torii

The hollow fiber ultrafiltration (HFUF)-based microbial concentration method is widely applied for monitoring pathogenic viruses and microbial indicators in environmental water samples. However, the HFUF-based method can co-concentrate substances that inte ...

SPRINGER2023

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Integration of feedforward and feedback control in the neuromechanics of vertebrate locomotion: a review of experimental, simulation and robotic studies

Auke Ijspeert

Company Biologists Ltd2023

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

Colin Neil Jones, Loris Di Natale, Jicheng Shi, Emilio Maddalena, Yingzhao Lian

2023

Modeling and analysis of miniaturized magnetorheological valve for fluidic actuation

Sofia Lydia Ntella

EPFL2023

Data-driven Methods for Control: from Linear to Lifting

Yingzhao Lian

EPFL2023

Surfactant Treatment for Efficient Gene Detection of Enteric Viruses and Indicators in Surface Water Concentrated by Ultrafiltration

Shotaro Torii

SPRINGER2023