This paper presents a novel algorithm for the integration of wind generation with conventional power system for reliability studies. The algorithm is based on dividing the wind turbine generator (WTG) output power int...
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This paper presents a new interface framework which has been added to Easy Java Simualtions' environment in order to improve its graphical features for 3D modeling. These new 3D capabilities provide users a set of...
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ISBN:
(纸本)9783902661562
This paper presents a new interface framework which has been added to Easy Java Simualtions' environment in order to improve its graphical features for 3D modeling. These new 3D capabilities provide users a set of new view elements which can be used to develop models with a high degree of reality. In this way, Easy Java Simulations becomes a powerful tool to easily and quickly create 3D realistic simulations.
Errors-in-Variables systems have been extensively studied in the literature. We study the impact of sampling on a continuous-time errors-in-variables problem. In particular, we study some approximations of a two dimen...
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The high performance mobile robots nowadays should operate themselves in many applications. One attractive task is to build the map, meanwhile estimate their poses for the locomotion in real time. The simultaneous loc...
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The high performance mobile robots nowadays should operate themselves in many applications. One attractive task is to build the map, meanwhile estimate their poses for the locomotion in real time. The simultaneous localization and mapping (SLAM) technique is once technique which can solve this demand. The selecting sensors are essential factors for generation the high accuracy output. This paper present, the applying a new 3D sensor namely the photonic mixer devices (PMD) provides a real-time capturing of surrounding volume. However the output of PMD is very excellent depth metric, to recognize the complex objects is still faultily because of the low resolution output (64 × 48 pixels). The 2D high resolution camera inspires to compensate the PMD camera's drawback. The high resolution image output is registered on the 3D volume. The visual input from the 2D camera does not delivers only high resolution texture data on 3D volume but it is also used for object recognition. Finally, the iterative closest point (ICP) algorithm is used for the image registration in order to yield the real time 3D data frames registration.
The simulation of congestion control algorithms of TCP networks is discussed in this paper. Simulation is a widespread procedure for testing and understanding how real systems evolve. Internet has a great impact in ou...
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ISBN:
(纸本)9781424448692
The simulation of congestion control algorithms of TCP networks is discussed in this paper. Simulation is a widespread procedure for testing and understanding how real systems evolve. Internet has a great impact in our society. Everyone wants fast and reliable links, but sometimes congestion happens because the network delay and the number of users fluctuate from one moment to the next. There are different approaches for dealing with congestion: classical (such as drop tail or RED) or process control techniques (PID, predictive control or fuzzy). Future engineers need to learn about this topic. So it seems logical to use simulation, but which tools should we use? This paper presents a comparison using three different simulation programs: Matlab, EcosimPro and ns-2. Results show that, depending on what we want, we should choose different tools.
Abstract In this paper Principal Components Analysis (PCA) is used for detecting faults in a simulated wastewater treatment plant (WWTP). Diagnosis tasks are treated using Fisher discriminant analysis (FDA). Both tech...
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Abstract In this paper Principal Components Analysis (PCA) is used for detecting faults in a simulated wastewater treatment plant (WWTP). Diagnosis tasks are treated using Fisher discriminant analysis (FDA). Both techniques are multivariate statistical techniques used in multivariate statistical process control (MSPC) and fault detection and isolation (FDI) perspectives. PCA reduces the dimensionality of the original historical data by projecting it onto a lower dimensionality space. It obtains the principal causes of variability in a process. If some of these causes change, it can be due to a fault in the process. FDA provides an optimal lower dimensional representation in terms of a discriminant between classes of data, where, in this context of fault diagnosis, each class corresponds to data collected during a specific and known fault. A discriminant function is applied to diagnose faults using data collected from the plant.
Network reconstruction, i.e., obtaining network structure from data, is a central theme in systems biology,economics, and engineering. Previous work introduced dynamical structure functions as a tool for posing and so...
Network reconstruction, i.e., obtaining network structure from data, is a central theme in systems biology,economics, and engineering. Previous work introduced dynamical structure functions as a tool for posing and solving the problem of network reconstruction between measured *** recovering the network structure between hidden states is not possible since they are not measured, in many situations it is important to estimate the number of hidden states in order to understand the complexity of the network under investigation and help identify potential targets for measurements. Estimating the number of hidden states is also crucial to obtain the simplest state-space model that captures the network structure and is coherent with the measured data. This paper characterises minimal order state-space realisations that are consistent with a given dynamical structure function by exploring properties of dynamical structure functions and developing algorithms to explicitly obtain a minimal reconstruction.
In order to introduce cognition, i.e. perception and autonomously reconfigured control, into manufacturing systems for increasing the flexibility and adaptivity this paper proposes an architecture of a cognitive safet...
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The selection of the structure of a controller in large scale industry processes requires extensive process knowledge. The aim of this paper is to present methods which help designers to comprehend a process by repres...
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The selection of the structure of a controller in large scale industry processes requires extensive process knowledge. The aim of this paper is to present methods which help designers to comprehend a process by representing structural and functional relationships from actuators and process disturbances to measured or estimated variables. This paper describes similarities between brain connectivity theory and interaction analysis in multivariable processes. Results from both theories are combined to create new methods for the analysis of industry processes. The developed methods are applied to an illustrative example.
This contribution addresses the problem of communication topology changes induced by the movement of a set of mobile agents. The network is modeled as a unit disk graph (UDG) where each unit disk is centered in a node...
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This contribution addresses the problem of communication topology changes induced by the movement of a set of mobile agents. The network is modeled as a unit disk graph (UDG) where each unit disk is centered in a node and where the communication topology is given by the instantaneous agents position. UDG allows for a compact representation of the communication topology as an intersection of unit disks. Fundamental properties of UDG are then used to characterize the feasible communication topologies. Under certain mobility assumptions, we show that all the transitions between the set of induced graphs are possible provided that the cardinality of the corresponding set of edges are different at most by one element.
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