SpiderCrane: Model and Properties of a Fast Weight-Handling Equipment

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Publications associées (31)

Optimized numerical solutions of SIRDVW multiage model controlling SARS-CoV-2 vaccine roll out: An application to the Italian scenario

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In the context of SARS-CoV-2 pandemic, mathematical modelling has played a funda-mental role for making forecasts, simulating scenarios and evaluating the impact of pre-ventive political, social and pharmaceutical measures. Optimal control theory represent ...

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Increasing the Energy Efficiency of Gas Boosters for Hydrogen Storage and for Refueling Stations

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A new electrically driven gas booster is described as an alternative to the classical air-driven gas boosters known for their poor energetic efficiency. These boosters are used in small scale Hydrogen storage facilities and in refueling stations for Hydrog ...

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Rock-Flow Cell Parameters Evaluation Using Ultrasound Doppler Velocimetry

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This work presents a study of two-phase flow generated inside a rock-flow cell setup. It is characterized by a pipe section filled with fluid (oil in our studies) that is put into oscillation around its mass centre by an electric motor. This type of appara ...

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Achieving Optimal Performance With Data-Driven Frequency-Based Control Synthesis Methods

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Frequency Response Function (FRF)-based control synthesis methods for Linear Time-Invariant (LTI) systems have been widely used in control theory and industry. Recently, there has been renewed interest in these methods, employing numerical optimization too ...

Ieee-Inst Electrical Electronics Engineers Inc2023

Self-sustained dynamics and forced resonant oscillations in flows: cross-junction jets and sloshing liquids

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In engineering, oscillatory instabilities and resonances are often considered undesirable flow features and measures are taken to avoid them. This may include avoiding certain parametric regions or implementing control and mitigation strategies. However, t ...

EPFL2023

Training Efficient Controllers via Analytic Policy Gradient

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Control design for robotic systems is complex and often requires solving an optimization to follow a trajectory accurately. Online optimization approaches like Model Predictive Control (MPC) have been shown to achieve great tracking performance, but requir ...

New York2023

Dynamics analysis for DC transformers integration in hybrid AC‐DC power distribution networks

Drazen Dujic, Max Dupont, Jules Christian Georges Macé, Renan Pillon Barcelos, Andrea Cervone

In AC/DC power distributions networks, power converters are interfacing buses to ensure DC voltage regulation and power distribution. Active front ends are used between AC and DC buses and two typical control schemes that can be implemented are voltage reg ...

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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

Methods for Grid-aware Operation and Planning of Active Distribution Networks

Rahul Kumar Gupta

The thesis presents methods for controlling and planning distributed energy resources (DERs) in active distribution networks (ADNs). It deals with three main challenges: (i) developing and experimentally validating grid-aware real-time control frameworks, ...

EPFL2023

Reinforcement learning approach to control an inverted pendulum: A general framework for educational purposes

Jesus Sanchez Rodriguez

Machine learning is often cited as a new paradigm in control theory, but is also often viewed as empirical and less intuitive for students than classical model-based methods. This is particularly the case for reinforcement learning, an approach that does n ...

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Machine Learning Methods for Robust Uncertainty Quantification and Controller Approximation

Emilio Maddalena

This thesis is situated at the crossroads between machine learning and control engineering. Our contributions are both theoretical, through proposing a new uncertainty quantification methodology in a kernelized context; and experimental, through investigat ...

EPFL2023

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