Publications related to State observer

Regularization for distributionally robust state estimation and prediction

Giancarlo Ferrari Trecate, Jean-Sébastien Hubert Brouillon, 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 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

Robust Localization for Multi-robot Formations: An Experimental Evaluation of an Extended GM-PHD Filter

Alcherio Martinoli, Alicja Barbara Roelofsen, Michiaki Hirayama

This paper presents a thorough experimental evaluation of an extended Gaussian Mixture Probability Hypothesis Density filter which is able to provide state estimates for the maintenance of a multirobot formation, even when the communication fails and the t ...

Springer Nature2021

A Sensor Fusion Approach to the Estimation of Instantaneous Velocity Using Single Wearable Sensor During Sprint

Kamiar Aminian, Frédéric Meyer, Salil Apte, Farzin Dadashi, Vincent Gremeaux

Power-Force-Velocity profile obtained during a sprint test is crucial for designing personalized training and evaluating injury risks. Estimation of instantaneous velocity is requisite for developing these profiles and the predominant method for this estim ...

2020

Model-based Identification, Estimation, and Control for Large-scale Urban Road Networks

Nikolaos Geroliminis, Isik Ilber Sirmatel

Network-level road traffic control remains a challenging problem. Macroscopic fundamental diagram (MFD) based dynamical models of large-scale urban networks enable development of model predictive perimeter control methods, which represent an efficient cong ...

IEEE2020

Moving Horizon Demand and State Estimation for Model Predictive Perimeter Control of Large-scale Urban Networks

Nikolaos Geroliminis, Isik Ilber Sirmatel

Perimeter control schemes proposed to alleviate congestion in large-scale urban networks usually assume perfect knowledge of the accumulation state and inflow demands, both requiring information about the origins and destinations of drivers. Such assumptio ...

IEEE2019

Real-Time State Estimation and Voltage Stability Assessment of Power Grids: From Theoretical Foundations to Practical Applications

Andreas Martin Kettner

The operators of power distribution systems strive to lower their operational costs and improve the quality of the power service provided to their customers. Furthermore, they are faced with the challenge of accommodating large numbers of Distributed Energ ...

EPFL2019

Nonlinear Moving Horizon Estimation for Large-Scale Urban Road Networks

Nikolaos Geroliminis, Isik Ilber Sirmatel

Perimeter control schemes proposed to alleviate congestion in large-scale urban networks usually assume perfect knowledge of the accumulation state together with current and future inflow demands, requiring information about the origins and destinations (O ...

IEEE Institute of Electrical and Electronics Engineers2020

Optimal Stochastic Sensor Error Modeling based on Actual Impact on Quality of GNSS-INS Integrated Navigation

Jan Skaloud, Stéphane Guerrier, Mehran Khaghani

Proper modeling of stochastic errors in inertial sensors plays a crucial role in the achievable quality of GNSS-INS integration especially with low-cost inertial sensors. Generalized Method of Wavelet Moments (GMWM) can model the underlying process for suc ...

2019

Distributed Fault Detection for Interconnected Large-Scale Systems: A Scalable Plug & Play Approach

Giancarlo Ferrari Trecate, Marcello Farina

In this paper, we propose a novel distributed fault detection method to monitor the state of a-possibly large scale-linear system, partitioned into interconnected subsystems. The approach hinges on the definition of a partition-based distributed Luenberger ...

2019

The Foldable Drone: A Morphing Quadrotor That Can Squeeze and Fly

Dario Floreano, Stefano Mintchev, Davide Scaramuzza

The recent advances in state estimation, perception, and navigation algorithms have significantly contributed to the ubiquitous use of quadrotors for inspection, mapping, and aerial imaging. To further increase the versatility of quadrotors, recent works i ...

2019

Distributed State Estimation and Cooperative Path-Following Under Communication Constraints

Francisco Fernandes Castro Rego

The main topics of this thesis are distributed estimation and cooperative path-following in the presence of communication constraints, with applications to autonomous marine vehicles. To this end, we study algorithms that take explicitly into account the c ...

EPFL2018

Design and Experimental Validation of an LTE-Based Synchrophasor Network in a Medium Voltage Distribution Grid

Mario Paolone, Asja Derviskadic, Paolo Romano, Marco Pignati, Lorenzo Zanni

We present and experimentally validate in a real-scale medium voltage (MV) grid a synchrophasor network that exploits the availability of a public 4G LTE communication infrastructure. An 18 buses, 10 kV feeder located in Huissen, The Netherlands, has been ...

Power Systems Computation Conference2018

Sequential Discrete Kalman Filter for Real-Time State Estimation in Power Distribution Systems: Theory and Implementation

Mario Paolone, Andreas Martin Kettner

This paper demonstrates the feasibility of implementing real-time state estimators for active distribution networks in field-programmable gate arrays (FPGAs) by presenting an operational prototype. The prototype is based on a linear state estimator that us ...

Institute of Electrical and Electronics Engineers2017

A Robust Relative Positioning System for Multi-Robot Formations Leveraging an Extended GM-PHD Filter

Alcherio Martinoli, Alicja Barbara Roelofsen

We propose a multi-robot tracking method to provide state estimates that allow a group of robots to maintain a formation even when the communication fails. We extend a Gaussian Mixture Probability Hypothesis Density filter to incorporate, firstly, absolute ...

2017

A Solution for the Partitioning Problem in Partition-Based Moving-Horizon Estimation

René Uwe Schneider

In addition to being observable, systems composed of interconnected subsystems must typically exhibit a particular subsystem structure, if their state is to be estimated successfully by a partition-based moving horizon estimator (PMHE). Suitable subsystem ...

Ieee-Inst Electrical Electronics Engineers Inc2017

Local-polynomial-approximation-based phase unwrapping using state space analysis

Pramod Rastogi, Rishikesh Dilip Kulkarni

A new method of phase unwrapping is proposed for the absolute phase estimation based on the first-order polynomial phase approximation within a symmetric window generated around each pixel. The accurate estimation of polynomial coefficients is performed by ...

2017

Linear Parameter-Varying Kalman Filter for angular velocity estimation of a reaction sphere actuator for satellite attitude control

Alireza Karimi, Leopoldo Rossini, Guzmán Borque Gallego

This paper presents a novel angular velocity estimation strategy of a Reaction Sphere (RS) for satellite attitude control based on a Linear Parameter-Varying (LPV) Kalman Filter. The reaction sphere is a permanent magnet synchronous spherical actuator whos ...

IEEE2017

On the use of shape constraints for state estimation in reaction systems

Dominique Bonvin, Julien Léo Billeter, Sriniketh Srinivasan

State estimation techniques are used for improving the quality of measured signals and for reconstructing unmeasured quantities. In chemical reaction systems, nonlinear estimators are often used to improve the quality of estimated concentrations. These non ...

Elsevier Science Bv2016

Performance Assessment of Linear State Estimators Using Synchrophasor Measurements

Jean-Yves Le Boudec, Mario Paolone, Lorenzo Zanni, Styliani Sarri, Miroslav Popovic

This paper aims to assess the performance of linear state estimation (SE) processes of power systems relying on synchrophasor measurements. The performance assessment is conducted with respect to two different families of SE algorithms, i.e., static ones r ...

Institute of Electrical and Electronics Engineers2016