This paper revisits the synchronisation problem for second-order multi-agent systems(MASs)under dynamically changing communication *** employing the reference model-based synchronisation algorithm,it is finally shown ...
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This paper revisits the synchronisation problem for second-order multi-agent systems(MASs)under dynamically changing communication *** employing the reference model-based synchronisation algorithm,it is finally shown that synchronisation for both the position and velocity states can be achieved if the union of the communication topologies has a directed spanning tree frequently *** extends the existing results obtained for second-order MASs which exploits mild communication topology condition guaranteeing the synchronisation to a more general *** analysis is successfully performed by exploiting the product properties of row-stochastic matrices,which can also provide us with an estimate the convergence rate towards the synchronisation.
This paper addresses the problem of fully covering an a priori known environment with fixed obstacles by a mobile agent. The blind region (i.e., the region hidden by the obstacles from the viewpoint of the agent) is d...
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This paper addresses the problem of fully covering an a priori known environment with fixed obstacles by a mobile agent. The blind region (i.e., the region hidden by the obstacles from the viewpoint of the agent) is described geometrically via both an exact and an over-approximation procedure. It is shown that the structure of this region depends on the hyperplane arrangement originating from the obstacles. This is further used to provide an mixed integer programming construction which allows to test if the feasible space is (or is not) fully covered by the agent(s). These novel results are examined over illustrative examples.
Accurate covariance matrix estimation has applications in a wide range of disciplines. For many applications the estimated covariance matrix needs to be positive definite and hence invertible. When the number of data ...
Accurate covariance matrix estimation has applications in a wide range of disciplines. For many applications the estimated covariance matrix needs to be positive definite and hence invertible. When the number of data points is insufficient, the estimated sample covariance matrix has two fold disadvantages. Firstly, although it is unbiased, it consists of a large estimation error. Secondly, it is not positive definite. A shrinkage technique has been proposed in the fields of finance and life sciences to estimate the covariance matrix that is invertible and contains relatively a small estimation error variance. In this paper, we introduce the shrinkage covariance matrix concept in the area of multiple target localization in wireless networks with correlated measurements. For localization, we use the low cost received signal strength (RSS) measurements. Unlike most studies, where the links between sensor nodes (SNs) and targets nodes (TNs) are independent, we use a realistic model where these links are correlated. Optimization in location accuracy is achieved by weighting each link via the shrinkage covariance matrix. Simulation results show that using the estimated shrinkage covariance improves the location accuracy of the localization algorithm.
The real-time detection of bacteria and other bio-pollutants in water distribution networks and the real-time control of the water quality is made possible by new biosensors. However, the limited communication capabil...
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The real-time detection of bacteria and other bio-pollutants in water distribution networks and the real-time control of the water quality is made possible by new biosensors. However, the limited communication capabilities of these sensors, which are placed underground, and their limited number, due to their high cost, pose significant challenges in the deployment and the reliable monitoring. This paper presents a preliminary study concerning the problem of the static optimal sensor placement of a wireless biosensor network in a water distribution network for real-time detection of bacterial contamination. An optimal sensor placement strategy is proposed, which maximizes the probability of detection considering a limited number of sensors while ensuring a connected communication topology. A lightweight algorithm that solves the optimal placement problem is developed. The performance of the proposed algorithm is evaluated through simulations, considering different network topologies using a water pipelines emulator. The results indicate that the proposed optimization outperforms more traditional approaches in terms of detection probability. It is concluded that the availability of a dynamic model of the bacterial propagation along with a spatio-temporal correlation of the process could lead to a more advanced real-time control of the water distribution networks.
When paralleled inverters feed a common load, it is required that the load is shared according to their power ratings. In this paper, the robust droop controller (RDC) proposed in the literature for achieving accurate...
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This article proposes a novel real time bug like algorithm for performing a dynamic smooth path planning scheme for an articulated vehicle under limited and sensory reconstructed surrounding static environment. In the...
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Radiation portal monitors (RPMs) are an effective mean of detecting radioactive material inside cargo containers. Polyvinyl toluene (PVT) monitors are the most broadly extended mainly due to their cost. The drawback w...
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ISBN:
(纸本)9781479959020
Radiation portal monitors (RPMs) are an effective mean of detecting radioactive material inside cargo containers. Polyvinyl toluene (PVT) monitors are the most broadly extended mainly due to their cost. The drawback when compared to other detectors is the lower resolution of the measured energy spectra. This low resolution hinders the use of spectrometric analysis to discriminate isotopes and discard nuisance alarms. Every alarm must thus be checked in a second inspection by a handheld detector or a spectroscopy-based radiation portal. The cost of this secondary inspection in terms of throughput can be significant, specially at maritime ports and borders. This paper aim is to assess the ability of neural networks to discriminate radioactive isotopes from the energy spectrum as measured by PVT RPMs. For this purpose, the system proposed preprocesses these energy spectra, dividing them by specific zones and transforming them into information. In a second step, this information is used by the neural network architecture, which allows to classify the radioisotopes in different groups.
Pressure retarded osmosis (PRO) uses the free energy of mixing when fresh river water flow into the sea to generate renewable energy. Many operating parameters affect the proper functioning of a PRO unit. Our analysis...
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Pressure retarded osmosis (PRO) uses the free energy of mixing when fresh river water flow into the sea to generate renewable energy. Many operating parameters affect the proper functioning of a PRO unit. Our analysis reveals the influence that the temperature has on power density and demonstrates that membrane performance is improved if the temperature is taken into account. In particular, the influence of the difference of temperatures between both sides of the membrane is investigated. This study demonstrates that structural parameters and physicochemical parameters are significantly affected by the temperature. Using streams with higher temperatures and reducing the temperature difference between the two streams, the process can achieve higher performance.
In Wireless Networked controlsystems (WNCS) with more than one concurrent control loop accessing the network, we need a control design that incorporates effects from the communication protocol (delays, packet dropout...
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ISBN:
(纸本)9781467360890
In Wireless Networked controlsystems (WNCS) with more than one concurrent control loop accessing the network, we need a control design that incorporates effects from the communication protocol (delays, packet dropouts, jitter) as well as energy and computation restrictions of the network nodes (e.g. bandwidth, node energy, transmission power). In practice, increasing communication frequency leads to a decreasing network lifetime and vice versa. In literature this joint design approach is referred to as control-communication or control-scheduling co-design. In this work, we present a new approach for the synthesis of robust or gain-scheduled controllers in a distributed WNCS, depending only on the sampling period. We use a scheduling policy computed by an iterative optimization algorithm to maximize the network lifetime and guarantee Lyapunov stability of the selected feedback control law with bounded delay and sampling intervals.
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