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Publications associées (72)

Scalable sparse covariance estimation via self-concordance

Volkan Cevher, Quoc Tran Dinh, Anastasios Kyrillidis, Rabeeh Karimi Mahabadi

We consider the class of convex minimization problems, composed of a self-concordant function, such as the logdet metric, a convex data fidelity term h and, a regularizing -- possibly non-smooth -- function g. This type of problems have recently attracted ...

2014

A Hardware-in-the-Loop Test Platform for the Real-Time State Estimation of Active Distribution Networks using Phasor Measurement Units

Mario Paolone, Paolo Romano, Marco Pignati, Lorenzo Zanni, Styliani Sarri

The paper describes the development and the performance assessment of a Hardware-in-the-Loop (HIL) test platform built as a proof-of-concept of a sub-second State Estimator (SE) of Active Distribution Networks (ADNs). The SE relies on the availability of d ...

Cigré - Conseil International des Grands Réseaux Électriques2013

Distributed bounded-error state estimation for partitioned systems based on practical robust positive invariance

Giancarlo Ferrari Trecate

We propose a partition-based state estimator for linear discrete-time systems composed by coupled subsystems affected by bounded disturbances. The architecture is distributed in the sense that each subsystem is equipped with a local state estimator that ex ...

2013

State Estimation for Legged Robots on Unstable and Slippery Terrain

Roland Siegwart, Marco Hutter

This paper presents a state estimation approach for legged robots based on stochastic filtering. The key idea is to extract information from the kinematic constraints given through the intermittent contacts with the ground and to fuse this information with ...

2013

Distributed bounded-error state estimation for partitioned systems based on practical robust positive invariance

Giancarlo Ferrari Trecate

In this paper we propose a novel partition-based state estimator for linear discrete-time systems composed of physically coupled subsystems affected by bounded disturbances. The proposed scheme is distributed in the sense that each local state estimator ex ...

2013

A Quotient Method for Designing Nonlinear Controllers

Dominique Bonvin, Philippe Müllhaupt

An algorithmic method is proposed to design stabilizing control laws for a class of nonlinear systems that comprises single-input feedback-linearizable systems and a particular set of single-input non feedback-linearizable systems. The method proceeds iter ...

Wiley-Blackwell2013

Design Of Steerable Filters For The Detection Of Micro-Particles

Michaël Unser, Cédric René Jean Vonesch, Frédéric Stauber

This paper presents two contributions. We first introduce a continuous-domain version of Principal-Component Analysis (PCA) for designing steerable filters so that they best approximate a given set of image templates. We exploit the fact that steerability ...

IEEE2013

State Estimation of Active Distribution Networks: Comparison Between WLS and Iterated Kalman-Filter Algorithm Integrating PMUs

Mario Paolone, Carlo Alberto Nucci, Styliani Sarri

One of the challenging tasks related to the realtime control of Active Distribution Networks (ADNs) is represented by the development of fast (i.e. sub-second) state estimation (SE) processes. As known, the problem of SE of power networks links the measure ...

IEEE Power Engineering Society and Technische Universität Berlin, Germany2012

Distributed moving horizon estimation for nonlinear constrained systems

Giancarlo Ferrari Trecate, Marcello Farina

In this paper we consider a nonlinear constrained system observed by a sensor network and propose a distributed state estimation scheme based on moving horizon estimation (MHE). In order to embrace the case where the whole system state cannot be reconstruc ...

2012

State Estimation for Legged Robots - Consistent Fusion of Leg Kinematics and IMU

Roland Siegwart, Marco Hutter

This paper introduces a state estimation framework for legged robots that allows estimating the full pose of the robot without making any assumptions about the geometrical structure of its environment. This is achieved by means of an Observability Constrai ...

2012

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