1,721,018 research outputs found
A distributed method for state estimation and false data detection in power networks
No full textThis work presents a distributed method for control centers to monitor the operating condition of a power network. Specifically we consider (static) state estimation problems, in which the state vector consists of the voltage magnitude and angle at all network buses. We consider the state to be linearly related to network measurements, which include power flows, current injections, and voltages phasors at some buses. We admit the presence of several cooperating control centers, and we design two distributed methods for them to compute the minimum variance estimate of the state given the network measurements. The two distributed methods rely on different modes of cooperation among control centers: in the first method an incremental mode of cooperation is assumed, whereas, in the second method, a diffusive interaction is implemented. These estimation methods, which are proved to converge in finite time, are further exploited to develop a distributed algorithm to detect corrupted data among network measurements
Steering a Leader-Follower Team via Linear Consensus
No full textThe paper considers the problem of driving a formation of autonomous mobile agents. Thegroup of mobile devices is represented by a leader-follower network, where the followers updatetheir position using a simple local consensus procedure, while the leaders, whose positionsrepresent the control inputs of the network, are free to move. We characterize the transientbehavior of the network, and we solve the containment problem without relying on auxiliarysensors
Distributed Intrusion Detection for Secure Consensus Computations
No full textThis paper focuses on trustworthy computation systems and proposes a novel intrusion detection scheme for averaging networks with misbehaving nodes. This prototypical control problem is relevant in network security applications. The objective is for each node to detect and isolate the misbehaving nodes using only the information flow adopted by standard averaging protocols. We focus on the single misbehaving node problem. Our technical approach is based on the theory of Unknown Input Observability. First, we give necessary and sufficient conditions for the misbehavior to be observable and for the identity of the faulty node to be detectable. Second, we design a distributed unknown input estimator, and we characterize its convergence rate in the 'equal-neighbor' model and in the general case. Third and finally, we propose a complete detection and isolation scheme and provide some remarks on the filter convergence time. We conclude the paper with the numerical study of a consensus problem and of a robot deployment problem
On the Security of Linear Consensus Networks
No full textThis work considers the problem of reaching consensus in linear networks with misbehaving agents. A solution to this problem is relevant for several tasks in multiagent systems including motion coordination, clock synchronization, and cooperative estimation. By modelling the misbehaving nodes as unknown and unmeasurable inputs affecting the network, we recast the problem into a system theoretic framework. Only relying on their direct measurements, the agents detect and identify uncooperative behaviors using fault detection and isolation techniques. We consider both the cases of Byzantine as well as non-colluding faults, and we express the solvability conditions of the two cases in terms of the observability properties of a linear system associated with the network, and from a graph theoretic perspective. It is shown that generically any node can correctly detect and identify the misbehaving agents, provided that the connectivity of the network is sufficiently high. Precisely, for a linear consensus network to be generically resilient to k concurrent faults, the connectivity of the communication graph needs to be 2k+1, if Byzantine agents are allowed, and k+1, if non-colluding agents are considered
Distributed estimation via iterative projections with application to power network monitoring
No full textThis work presents a distributed method for control centers to monitor the operating condition of a power network, i.e., to estimate the network state, and to ultimately determine the occurrence of threatening situations. State estimation has been recognized to be a fundamental task for network control centers to operate safely and reliably a power grid. We consider (static) state estimation problems, in which the state vector consists of the voltage magnitude and angle at all network buses. We consider the state to be linearly related to network measurements, which include power flows, current injections, and voltage phasors at some buses. We admit the presence of several cooperating control centers, and we design two distributed methods for them to compute the minimum variance estimate of the state, given the network measurements. The two distributed methods rely on different modes of cooperation among control centers: in the first method an incremental mode of cooperation is used, whereas, in the second method, a diffusive interaction is implemented. Our procedures, which require each control center to know only the measurements and the structure of a subpart of the whole network, are computationally efficient and scalable with respect to the network dimension, provided that the number of control centers also increases with the network cardinality. Additionally, a finite-memory approximation of our diffusive algorithm is proposed, and its accuracy is characterized. Finally, our estimation methods are exploited to develop a distributed algorithm to detect corrupted network measurements
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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