Networked embedded sensor systems use the evidence gathered by spatially distributed heterogeneous sensor nodes possessing partial and different scopes of expertise, to make inferences on the scenario under observatio...
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ISBN:
(纸本)3540327940
Networked embedded sensor systems use the evidence gathered by spatially distributed heterogeneous sensor nodes possessing partial and different scopes of expertise, to make inferences on the scenario under observation. For such system to make an accurate collective decision, the partial and incomplete evidence provided by nodes must be processed in a simple and straightforward manner during the information exchange and fusion process. To achieve these objectives, we present a novel, unified approach named "non-recursive evidence filtering" based on the Dempster-Shafer (DS) formalism for evidence representation. It is capable of selectively fusing partial evidence in such a network to directly infer on events of interest such as threats occurring with a certain temporal distribution, while accommodating the varying reliability and accuracy of information sources. Certain restrictions on the coefficients impose several challenges in the design of such evidence filters. We show that the gain of these evidence filters at frequency zero is always equal to one and all coefficients must be non-negative. This suggests that arbitrary frequency shaping is not possible and a pure bandpass evidence filter is not realizable. A method to design a simple FIR evidence filter to detect periodic events of interest is presented. Multi-dimensional spatio-temporal evidence filters are discussed as a direct extension to the above, along with a low signature threat detection example that clearly illustrates the effectiveness of the evidence filtering concept in distributed networked embedded systems.
The network embedded control lab, neclab, is a software environment designed to allow easy deployment of networked embedded control systems, in particular wireless networked embedded control systems (wnecs). A wnecs i...
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ISBN:
(纸本)3540327940
The network embedded control lab, neclab, is a software environment designed to allow easy deployment of networked embedded control systems, in particular wireless networked embedded control systems (wnecs). A wnecs is a collection of interconnected plant sensors, digital controllers, and plant actuators which communicate with each other over wireless channels. In this paper neclab is introduced and explained using a simple ball and beam control application. We focus on wnecs which use the MICA2 Motes.
This paper presents a simulation framework for distributed control using wireless sensor networks. The proposed framework is an extension of the Georgia Tech Sensor Network Simulator (GTSNetS). The new features includ...
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The performance of a class of Model-Based Networked control System (MB-NCS) is considered in this paper. A MB-NCS uses an explicit model of the plant to reduce the network bandwidth requirements. In particular, an Out...
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ISBN:
(纸本)3540327940
The performance of a class of Model-Based Networked control System (MB-NCS) is considered in this paper. A MB-NCS uses an explicit model of the plant to reduce the network bandwidth requirements. In particular, an Output Feedback MB-NCS is studied. After reviewing the stability results for this system and some lifting techniques basics, two performance measures related to the traditional H2 performance measure for LTI systems are computed. The first H2 like performance measurement is called the Extended H2 norm of the system and is based on the norm of the impulse response of the MB-NCS at time zero. The second performance measure is called the Generalized H2 norm and it basically replaces the traditional trace norm by the Hilbert-Schmidt norm that is more appropriate for infinite dimensional operators. The Generalized H2 norm also represents the average norm of the impulse response of the MB-NCS for impulse inputs applied at different times. Examples show how both norms converge to the traditional H2 norm for continuous H2 systems. Finally, with the help of an alternate way of representing lifted parameters, the relationship between the optimal sampler and hold of a sampled data system and the structure of the Output Feedback MB-NCS is shown.
Tagged systems provide a denotational semantics for embedded systems. A heterogeneous network of embedded systems can be modeled mathematically by a network of tagged systems. Taking the heterogeneous composition of t...
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ISBN:
(纸本)3540327940
Tagged systems provide a denotational semantics for embedded systems. A heterogeneous network of embedded systems can be modeled mathematically by a network of tagged systems. Taking the heterogeneous composition of this network results in a single, homogeneous, tagged system. The question this paper addresses is: when is semantics (behavior) preserved by composition? To answer this question, we use the framework of category theory to reason about heterogeneous system composition and derive results that are as general as possible. In particular, we define the category of tagged systems, demonstrate that a network of tagged systems corresponds to a diagram in this category and prove that taking the composition of a network of tagged systems is equivalent to taking the limit of this diagram-thus composition is endowed with a universal property. Using this universality, we are able to derive verifiable necessary and sufficient conditions on when composition preserves semantics.
This paper concerns the problem of controlling mobile nodes in a network in such away that the resulting graph-encoding of the inter-node information flow exhibits certain desirable properties. As a sequence of such t...
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ISBN:
(纸本)3540327940
This paper concerns the problem of controlling mobile nodes in a network in such away that the resulting graph-encoding of the inter-node information flow exhibits certain desirable properties. As a sequence of such transitions between different graphs occurs, the result is a graph process. In this paper, we not only characterize the reachability properties of these graph processes, but also put them to use in a number of applications, ranging from multi-agent formation control, to optimal collaborative beamforming in sensor networks.
The problem of distributed Kalman filtering (DKF) for sensor networks is one of the most fundamental distributed estimation problems for scalable sensor fusion. This paper addresses the DKF problem by reducing it to t...
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ISBN:
(纸本)3540327940
The problem of distributed Kalman filtering (DKF) for sensor networks is one of the most fundamental distributed estimation problems for scalable sensor fusion. This paper addresses the DKF problem by reducing it to two separate dynamic consensus problems in terms of weighted measurements and inverse-covariance matrices. These to data fusion problems are solved is a distributed way using low-pass and band-pass consensus filters. Consensus filters are distributed algorithms that allow calculation of average-consensus of time-varying signals. The stability properties of consensus filters is discussed in a companion CDC '05 paper [OSS05b]. We show that a central Kalman filter for sensor networks can be decomposed into n micro-Kalman filters with inputs that are provided by two types of consensus filters. This network of micro-Kalman filters collectively are capable to provide an estimate of the state of the process (under observation) that is identical to the estimate obtained by a central Kalman filter given that all nodes agree on two central sums. Later, we demonstrate that our consensus filters can approximate these sums and that gives an approximate distributed Kalman filtering algorithm. A detailed account of the computational and communication architecture of the algorithm is provided. Simulation results are presented for a sensor network with 200 nodes and more than 1000 links.
In human walking, the swing leg moves backward just prior to ground contact, i.e. the relative angle between the thighs is decreasing. We hypothesize that this swing leg retraction may have a positive effect on gait s...
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ISBN:
(纸本)3540361189
In human walking, the swing leg moves backward just prior to ground contact, i.e. the relative angle between the thighs is decreasing. We hypothesize that this swing leg retraction may have a positive effect on gait stability, because similar effects have been reported in passive dynamic walking models, in running models, and in robot juggling. For this study, we use a simple inverted pendulum model for the stance leg. The swing leg is assumed to accurately follow a time-based trajectory. The model walks down a shallow slope for energy input which is balanced by the impact losses at heel strike. With this model we show that a mild retraction speed indeed improves stability, while gaits without a retraction phase (the swing leg keeps moving forward) are consistently unstable. By walking with shorter steps or on a steeper slope, the range of stable retraction speeds increases, suggesting a better robustness. An optimization of the swing leg trajectory of a more realistic model also consistently comes up with a retraction phase, and indeed our prototype demonstrates a retraction phase as well. The conclusions of this paper are twofold, (1) use a mild swing leg retraction speed for better stability, and (2) walking faster is easier.
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