Publications associées à Distributed state estimation for discrete-time linear time invariant systems: A survey

Frequency domain data-driven robust and optimal control

The goal of this thesis is to propose pragmatic solutions to real challenges faced in the industry. The scope of this thesis encompasses two subjects: frequency-based structured controller synthesis for linear time-invariant (LTI) systems on one side, and ...

EPFL2024

Data-Driven Control Synthesis using Koopman Operator: A Robust Approach

Alireza Karimi, Mert Eyuboglu, Nathan Russell Powell

This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...

2024

Regularization for distributionally robust state estimation and prediction

Jean-Sébastien Hubert Brouillon, Giancarlo Ferrari Trecate, Florian Dörfler

The increasing availability of sensing techniques provides a great opportunity for engineers to design state estimation methods, which are optimal for the system under observation and the observed noise patterns. However, these patterns often do not fulfil ...

2023

Data-driven IQC-Based Robust Control Design for Hybrid Micro-disturbance Isolation Platform

Alireza Karimi, Elias Sebastian Klauser, Vaibhav Gupta

A novel approach for robust controller synthesis, which models uncertainty as an elliptical set, is proposed in the paper. Given a set of frequency response functions of linear time-invariant (LTI) multiple-input multiple-output (MIMO) systems, the approac ...

IEEE2023

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

Alireza Karimi, Philippe Louis Schuchert

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

Regularization for distributionally robust state estimation and prediction

Jean-Sébastien Hubert Brouillon

Simulation script for the paper "Regularization for distributionally robust state estimation and prediction". Run tests/test_cdc.py to reproduce results. Extended versions can be found at https://github.com/DecodEPFL/. ...

Zenodo2023

Self-powered transformer intelligent wireless temperature monitoring system based on an ultra-low acceleration piezoelectric vibration energy harvester

Xin Chen

The wireless sensor nodes used for monitoring the condition of grid equipment always be powered by disposable batteries. However, it introduces disadvantages, such as inconvenient replacement, short lifespan, and envi-ronmental pollution, significantly imp ...

Elsevier2023

Detecting whether a stochastic process is finitely expressed in a basis

Victor Panaretos, Neda Mohammadi Jouzdani

Is it possible to detect if the sample paths of a stochastic process almost surely admit a finite expansion with respect to some/any basis? The determination is to be made on the basis of a finite collection of discretely/noisily observed sample paths. We ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2023

Experimental Validation of a Unified and Linear State Estimation Method for Hybrid AC/DC Microgrids

Mario Paolone, Willem Lambrichts

This paper presents the experimental validation of a linear recursive state estimation (SE) process for hybrid AC/DC microgrids proposed in the authors' previous work. The SE uses a unified and linear measurement model that relies on the use of synchronize ...

IEEE2023

Data-Driven Unknown-Input Observers and State Estimation

Giancarlo Ferrari Trecate, Mustafa Sahin Turan

Unknown-input observers (UIOs) allow for estimation of the states of an LTI system without knowledge of all inputs. In this letter, we provide a novel data-driven UIO based on behavioral system theory and the result known as Fundamental Lemma proposed by J ...

2022

Neural System Level Synthesis: Learning over All Stabilizing Policies for Nonlinear Systems

Giancarlo Ferrari Trecate, Clara Lucía Galimberti, Luca Furieri

We address the problem of designing stabilizing control policies for nonlinear systems in discrete-time, while minimizing an arbitrary cost function. When the system is linear and the cost is convex, the System Level Synthesis (SLS) approach offers an effe ...

IEEE2022

Strategies, Techniques and Systems for powering low-maintenance and battery-free devices through Energy Harvesting and Wireless Power Transfer

Roberto La Rosa

The purpose of this research has a background in the market for Internet of Things (IoT)devices and wireless sensor networks. The Market Forecast predicts the connection of a trillion"things" by 2025. The global smart sensor market size trend grows from US ...

EPFL2022

A Distributed Luenberger Observer for Linear State Feedback Systems With Quantized and Rate-Limited Communications

Colin Neil Jones, Andrea Alessandretti, Ye Pu, Francisco Fernandes Castro Rego

This article addresses the problem of simultaneous distributed state estimation, and control of linear systems with linear state feedback, subjected to process, and measurement noise, under the constraints of quantized, and rate-limited network data transm ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Shortest-support multi-spline bases for generalized sampling

Michaël Unser, Shayan Aziznejad, Alireza Naderi, Alexis Marie Frederic Goujon

Generalized sampling consists in the recovery of a function f, from the samples of the responses of a collection of linear shift-invariant systems to the input f . The reconstructed function is typically a member of a finitely generated integer-shift invar ...

2021

Aerosol formation and growth rates from chamber experiments using Kalman smoothing

Lubna Dada

Bayesian state estimation in the form of Kalman smoothing was applied to differential mobility analyser train (DMA-train) measurements of aerosol size distribution dynamics. Four experiments were analysed in order to estimate the aerosol size distribution, ...

Copernicus Publications2021

Efficient Learning of a Linear Dynamical System with Stability Guarantees

Daniel Kuhn, Tobias Sutter, Wouter Jongeneel

We propose a principled method for projecting an arbitrary square matrix to the non- convex set of asymptotically stable matrices. Leveraging ideas from large deviations theory, we show that this projection is optimal in an information-theoretic sense and ...

2023

An Energy-Autonomous Wireless Sensor With Simultaneous Energy Harvesting and Ambient Light Sensing

Catherine Dehollain, Andreas Peter Burg, Roberto La Rosa

Wireless sensor nodes (WSNs) are generally powered by batteries, which results in a substantial limitation to the places where the nodes can be installed, to the maximum number of deployable devices, and to the node lifetime. To meet the demand for Interne ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Advanced methods for Brillouin based distributed optical fiber sensors

Simon Adrien Zaslawski

After more than thirty years of continuous research and development, the performances of conventional Brillouin based distributed optical fiber sensors (DOFS) are now peaking, as they are facing fundamental barriers that restrict the power of the light inj ...

EPFL2021

Model order reduction based on functional rational approximants for parametric PDEs with meromorphic structure

Davide Pradovera

Many engineering fields rely on frequency-domain dynamical systems for the mathematical modeling of physical (electrical/mechanical/etc.) structures. With the growing need for more accurate and reliable results, the computational burden incurred by frequen ...

EPFL2021

A Note on BIBO Stability

Michaël Unser

The statements on the BIBO stability of continuoustime convolution systems found in engineering textbooks are often either too vague (because of lack of hypotheses) or mathematically incorrect. What is more troubling is that they usually exclude the identi ...

2020