Redundancy and Observability Analysis of Conventional and PMU Measurements

This letter shows that the matrix can be used for redundancy and observability analysis of metering systems composed of PMU measurements and conventional measurements (power and voltage magnitude measurements). The matrix is obtained via triangular factorization of the Jacobian matrix. Observability analysis and restoration is carried out during the triangular factorization of the Jacobian matrix, and the redundancy analysis is made exploring the matrix structure. As a consequence, the matrix can be used for metering system planning considering conventional and PMU measurements. These features of the matrix will be outlined and illustrated by numerical examples.

On the use of Gram matrix in observability analysis

This letter presents some notes on the use of the Gram matrix in observability analysis. This matrix is constructed considering the rows of the measurement Jacobian matrix as vectors, and it can be employed in observability analysis and restoration methods. The determination of nonredundant pseudo-measurements (normally injections pseudo-measurements) for merging observable islands into an observable (single) system is carried out analyzing the pivots of the Gram matrix. The Gram matrix can also be used to verify local redundancy, which is important in measurement system planning. Some numerical examples` are used to illustrate these features. Others features of the Gram matrix are under study.

Observability of nonlinear fractional dynamical systems

We study the observability of linear and nonlinear fractional differential systems of order 0 < α < 1 by using the Mittag-Leffler matrix function and the application of Banach’s contraction mapping theorem. Several examples illustrate the concepts.

Observability and overcoming coordination failure in organizations

Many organizations suffer poor performance because its members fail to coordinate on efficient patterns of behavior. In previous research, we have shown that financial incentives can be used to find a way out of such performance traps. Here we examine the sensitivity of this result to the ability of people to observe others' choices. Our experiments are set in a corporate environment where subjects' payoffs depend on coordinating at high effort levels; the underlying game being played repeatedly by the employees of an experimental firm is a weak-link game. Treatments vary along two dimensions. First, subjects either start with low financial incentives for coordination, which typically leads to coordination failure, and then are switched to higher incentives or start with high incentives, which typically yield effective coordination, and are switched to low incentives. Second, as the key treatment variable, subjects either observe the effort levels chosen by all employees in their experimenta

Planning under partial observability by classical replanning: theory and experiments

Planning with partial observability can be formulated as a non-deterministic search problem in belief space. The problem is harder than classical planning as keeping track of beliefs is harder than keeping track of states, and searching for action policies is harder than searching for action sequences. In this work, we develop a framework for partial observability that avoids these limitations and leads to a planner that scales up to larger problems. For this, the class of problems is restricted to those in which 1) the non-unary clauses representing the uncertainty about the initial situation are nvariant, and 2) variables that are hidden in the initial situation do not appear in the body of conditional effects, which are all assumed to be deterministic. We show that such problems can be translated in linear time into equivalent fully observable non-deterministic planning problems, and that an slight extension of this translation renders the problem solvable by means of classical planners. The whole approach is sound and complete provided that in addition, the state-space is connected. Experiments are also reported.

Duality, observability, and controllability for linear time-varying descriptor systems

A characterization of observability for linear time-varying descriptor systemsE(t)x(t)+F(t)x(t)=B(t)u(t), y(t)=C(t)x(t) was recently developed. NeitherE norC were required to have constant rank. This paper defines a dual system, and a type of controllability so that observability of the original system is equivalent to controllability of the dual system. Criteria for observability and controllability are given in terms of arrays of derivatives of the original coefficients. In addition, the duality results of this paper lead to an improvement on a previous fundamental structure result for solvable systems of the formE(t)x(t)+F(t)x(t)=f(tt).

On the observability of turbulent transport rates by Argo: supporting evidence from an inversion experiment

Although estimation of turbulent transport parameters using inverse methods is not new, there is little evaluation of the method in the literature. Here, it is shown that extended observation of the broad scale hydrography by Argo provides a path to improved estimates of regional turbulent transport rates. Results from a 20 year ocean state estimate produced with the ECCO v4 non-linear inverse modeling framework provide supporting evidence. Turbulent transport parameter maps are estimated under the constraints of fitting the extensive collection of Argo profiles collected through 2011. The adjusted parameters dramatically reduce misfits to in situ profiles as compared with earlier ECCO solutions. They also yield a clear reduction in the model drift away from observations over multi-century long simulations, both for assimilated variables (temperature and salinity) and independent variables (bio-geochemical tracers). Despite the minimal constraints imposed specifically on the estimated parameters, their geography is physically plausible and exhibits close connections with the upper ocean ocean stratification as observed by Argo. The estimated parameter adjustments furthermore have first order impacts on upper-ocean stratification and mixed layer depths over 20 years. These results identify the constraint of fitting Argo profiles as an effective observational basis for regional turbulent transport rates. Uncertainties and further improvements of the method are discussed.

JVM-based Techniques for Improving Java Observability

Observability measures the support of computer systems to accurately capture, analyze, and present (collectively observe) the internal information about the systems. Observability frameworks play important roles for program understanding, troubleshooting, performance diagnosis, and optimizations. However, traditional solutions are either expensive or coarse-grained, consequently compromising their utility in accommodating today’s increasingly complex software systems. New solutions are emerging for VM-based languages due to the full control language VMs have over program executions. Existing such solutions, nonetheless, still lack flexibility, have high overhead, or provide limited context information for developing powerful dynamic analyses. In this thesis, we present a VM-based infrastructure, called marker tracing framework (MTF), to address the deficiencies in the existing solutions for providing better observability for VM-based languages. MTF serves as a solid foundation for implementing fine-grained low-overhead program instrumentation. Specifically, MTF allows analysis clients to: 1) define custom events with rich semantics ; 2) specify precisely the program locations where the events should trigger; and 3) adaptively enable/disable the instrumentation at runtime. In addition, MTF-based analysis clients are more powerful by having access to all information available to the VM. To demonstrate the utility and effectiveness of MTF, we present two analysis clients: 1) dynamic typestate analysis with adaptive online program analysis (AOPA); and 2) selective probabilistic calling context analysis (SPCC). In addition, we evaluate the runtime performance of MTF and the typestate client with the DaCapo benchmarks. The results show that: 1) MTF has acceptable runtime overhead when tracing moderate numbers of marker events; and 2) AOPA is highly effective in reducing the event frequency for the dynamic typestate analysis; and 3) language VMs can be exploited to offer greater observability.

Observability of high density tracing molecular lines in lensed galaxies with the Atacama large millimeter array

Lo scopo di questo lavoro di tesi è indagare le capacità di ALMA di osservare il continuo e le righe molecolari di emissione di HCN, HCO+ e HNC, in galassie lensate ad alto z, nelle prime fasi della loro formazione. Per farlo vengono utilizzate osservazioni ALMA di righe di emissione molecolare, relative a dati pubblici di Ciclo 0. Queste osservazioni vengono utilizzate per simulare in modo realistico l’emissione da parte di galassie ad alto z e la risposta osservativa del telescopio, assumendo diverse possibili geometrie di lensing. Inoltre le recenti osservazioni ALMA sono state utilizzate per aggiornare le relazioni già esistenti tra la luminosità FIR e la luminosità delle righe molecolari. Queste recenti osservazioni con maggiore sensibilità e risoluzione angolare, sembrano essere in buon accordo con le precedenti osservazioni. Per realizzare questo progetto di tesi, sono stati scaricati dall’archivio ALMA i dati non calibrati relativi a due sorgenti ben studiate: NGC1614, rappresentativa delle galassie di tipo starburst ed IRAS 20551-4250, un AGN oscurato. Il processo di calibrazione è stato ripetuto per esaminare le proprietà dei cubi di dati utilizzando il pacchetto Common Astronomy Software Applications (CASA). Le righe spettrali osservate e l’emissione del continuo sono state successivamente estrapolate ad alto z riscalando adeguatamente le distanze, le dimensioni delle sorgenti e le frequenze di emissione. In seguito è stato applicato un modello di lensing gravitazionale basato su quello di Lapi et al. (2012). Sono state considerate diverse configurazioni tra lente e sorgente per ottenere diverse geometrie delle immagini e diversi fattori di amplificazione. Infine stato utilizzato il software CASA per simulare le osservazioni ALMA in modo da verificare le capacità osservative del telescopio al variare della geometria del sistema. Per ogni riga molecolare e per l’emissione del continuo sono state determinate la sensibilit e la risoluzione che possono essere raggiunte con le osservazioni ALMA e sono state analizzate alcune strategie osservative per effettuare survey di righe spettrali in oggetti lensati. Inoltre stata analizzata la possibilit di caratterizzare oggetti starburst ed AGN dai rapporti tra le righe di emissione delle molecole traccianti di alta densit. Le prestazioni di ALMA consentiranno di distinguere e stimare i contributi relativi di SB ed AGN in galassie lensate a z > 2.5, quindi vicine alla loro presunta epoca di formazione (Lapi et al. 2010), in meno di 5 minuti di osservazione per qualsiasi fattore di magnificazione. Nel presente lavoro sono state inoltre discusse alcune strategie osservative per condurre survey o followup per osservare le righe di HCN(4-3), HCO+(4-3) e HNC(4-3) in galassie lensate a redshift 2.5 < z < 3, dimostrando che sono possibili per campioni statisticamente significativi in tempi relativamente brevi.

A combined algorithm for analyzing structural controllability and observability of complex networks

In this paper a combined algorithm for analyzing structural controllability and observability of complex networks is presented. The algorithm addresses the two fundamental properties to guarantee structural controllability of a system: the absence of dilations and the accessibility of all nodes. The first problem is reformulated as a Maximum Matching search and it is addressed via the Hopcroft- Karp algorithm; the second problem is solved via a new wiring algorithm. Both algorithms can be combined to efficiently determine the number of required controllers and observers as well as the new required connections in order to guarantee controllability and observability in real complex networks. An application to a Twitter social network with over 100,000 nodes illustrates the proposed algorithms.

Mathematical foundations for efficient structural controllability and observability analysis of complex systems

The relationship between structural controllability and observability of complex systems is studied. Algebraic and graph theoretic tools are combined to prove the extent of some controller/observer duality results. Two types of control design problems are addressed and some fundamental theoretical results are provided. In addition new algorithms are presented to compute optimal solutions for monitoring large scale real networks.

Innovation concept for measurement gross error detection and identification in power system state estimation

In this study, the innovation approach is used to estimate the measurement total error associated with power system state estimation. This is required because the power system equations are very much correlated with each other and as a consequence part of the measurements errors is masked. For that purpose an index, innovation index (II), which provides the quantity of new information a measurement contains is proposed. A critical measurement is the limit case of a measurement with low II, it has a zero II index and its error is totally masked. In other words, that measurement does not bring any innovation for the gross error test. Using the II of a measurement, the masked gross error by the state estimation is recovered; then the total gross error of that measurement is composed. Instead of the classical normalised measurement residual amplitude, the corresponding normalised composed measurement residual amplitude is used in the gross error detection and identification test, but with m degrees of freedom. The gross error processing turns out to be very simple to implement, requiring only few adaptations to the existing state estimation software. The IEEE-14 bus system is used to validate the proposed gross error detection and identification test.

Optimization of modal filters based on arrays of piezoelectric sensors

Modal filters may be obtained by a properly designed weighted sum of the output signals of an array of sensors distributed on the host structure. Although several research groups have been interested in techniques for designing and implementing modal filters based on a given array of sensors, the effect of the array topology on the effectiveness of the modal filter has received much less attention. In particular, it is known that some parameters, such as size, shape and location of a sensor, are very important in determining the observability of a vibration mode. Hence, this paper presents a methodology for the topological optimization of an array of sensors in order to maximize the effectiveness of a set of selected modal filters. This is done using a genetic algorithm optimization technique for the selection of 12 piezoceramic sensors from an array of 36 piezoceramic sensors regularly distributed on an aluminum plate, which maximize the filtering performance, over a given frequency range, of a set of modal filters, each one aiming to isolate one of the first vibration modes. The vectors of the weighting coefficients for each modal filter are evaluated using QR decomposition of the complex frequency response function matrix. Results show that the array topology is not very important for lower frequencies but it greatly affects the filter effectiveness for higher frequencies. Therefore, it is possible to improve the effectiveness and frequency range of a set of modal filters by optimizing the topology of an array of sensors. Indeed, using 12 properly located piezoceramic sensors bonded on an aluminum plate it is shown that the frequency range of a set of modal filters may be enlarged by 25-50%.

Robust model-order reduction of complex biological processes

This paper addresses robust model-order reduction of a high dimensional nonlinear partial differential equation (PDE) model of a complex biological process. Based on a nonlinear, distributed parameter model of the same process which was validated against experimental data of an existing, pilot-scale BNR activated sludge plant, we developed a state-space model with 154 state variables in this work. A general algorithm for robustly reducing the nonlinear PDE model is presented and based on an investigation of five state-of-the-art model-order reduction techniques, we are able to reduce the original model to a model with only 30 states without incurring pronounced modelling errors. The Singular perturbation approximation balanced truncating technique is found to give the lowest modelling errors in low frequency ranges and hence is deemed most suitable for controller design and other real-time applications. (C) 2002 Elsevier Science Ltd. All rights reserved.