Distributing the Kalman Filter for Large-Scale Systems

This paper derives a \emph{distributed} Kalman filter to estimate a sparsely connected, large-scale, $n-$dimensional, dynamical system monitored by a network of $N$ sensors. Local Kalman filters are implemented on the ($n_l-$dimensional, where $n_l\ll n$) sub-systems that are obtained after spatially decomposing the large-scale system. The resulting sub-systems overlap, which along with an assimilation procedure on the local Kalman filters, preserve an $L$th order Gauss-Markovian structure of the centralized error processes. The information loss due to the $L$th order Gauss-Markovian approximation is controllable as it can be characterized by a divergence that decreases as $L\uparrow$. The order of the approximation, $L$, leads to a lower bound on the dimension of the sub-systems, hence, providing a criterion for sub-system selection. The assimilation procedure is carried out on the local error covariances with a distributed iterate collapse inversion (DICI) algorithm that we introduce. The DICI algorithm computes the (approximated) centralized Riccati and Lyapunov equations iteratively with only local communication and low-order computation. We fuse the observations that are common among the local Kalman filters using bipartite fusion graphs and consensus averaging algorithms. The proposed algorithm achieves full distribution of the Kalman filter that is coherent with the centralized Kalman filter with an $L$th order Gaussian-Markovian structure on the centralized error processes. Nowhere storage, communication, or computation of $n-$dimensional vectors and matrices is needed; only $n_l \ll n$ dimensional vectors and matrices are communicated or used in the computation at the sensors

DILAND: An Algorithm for Distributed Sensor Localization with Noisy Distance Measurements

In this correspondence, we present an algorithm for distributed sensor localization with noisy distance measurements (DILAND) that extends and makes the DLRE more robust. DLRE is a distributed sensor localization algorithm in $\mathbb{R}^m$ $(m\geq1)$ introduced in \cite{usman_loctsp:08}. DILAND operates when (i) the communication among the sensors is noisy; (ii) the communication links in the network may fail with a non-zero probability; and (iii) the measurements performed to compute distances among the sensors are corrupted with noise. The sensors (which do not know their locations) lie in the convex hull of at least $m+1$ anchors (nodes that know their own locations.) Under minimal assumptions on the connectivity and triangulation of each sensor in the network, this correspondence shows that, under the broad random phenomena described above, DILAND converges almost surely (a.s.) to the exact sensor locations.Comment: Submitted to the IEEE Transactions on Signal Processing. Initial submission on May 2009. 12 page

Finite element analysis of the ECT test on mode III interlaminar fracture of carbon-epoxy composite laminates

In this work a parametric study of the Edge Crack Torsion (ECT) specimen was performed in order to maximize the mode III component (GIII) of the strain energy release rate for carbon-epoxy laminates. A three-dimensional finite element analysis of the ECT test was conducted considering a [90/0/(+45/-45)2/(-45/+45)2/0/90]S lay-up. The main objective was to define an adequate geometry to obtain an almost pure mode III at crack front. The geometrical parameters studied were specimen dimensions, distance between pins and size of the initial crack. The numerical results demonstrated that the ratio between the specimen length and the initial crack length had a significant effect on the strain energy release rate distributions. In almost all of the tested configurations, a mode II component occurred near the edges but it did not interfere significantly with the dominant mode III state.FCT - POCTI/EME/45573/200

A new data reduction scheme to obtain the mode II fracture properties of Pinus Pinaster wood

In this work a numerical study of the End Notched Flexure (ENF) specimen was performed in order to obtain the mode II critical strain energy released rate (GIIc) of a Pinus pinaster wood in the RL crack propagation system. The analysis included interface finite elements and a progressive damage model based on indirect use of Fracture Mechanics. The difficulties in monitoring the crack length during an experimental ENF test and the inconvenience of performing separate tests in order to obtain the elastic properties are well known. To avoid these problems, a new data reduction scheme based on the equivalent crack concept was proposed and validated. This new data reduction scheme, the Compliance-Based Beam Method (CBBM), does not require crack measurements during ENF tests and additional tests to obtain elastic properties.FCT - POCTI/EME/45573/200