932 resultados para Systems fuzzy


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There is an increasing demand for highly dynamic realtime systems where several independently developed applications with different timing requirements can coexist. This paper proposes a protocol to integrate shared resources and precedence constraints among tasks in such systems assuming no precise information on critical sections and computation times is available. The concept of bandwidth inheritance is combined with a capacity sharing and stealing mechanism to efficiently exchange bandwidth among needed tasks, minimising the cost of blocking.

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A brief introduction to the fractional continuous-time linear systems is presented. It will be done without needing a deep study of the fractional derivatives. We will show that the computation of the impulse and step responses is very similar to the classic. The main difference lies in the substitution of the exponential by the Mittag-Leffler function. We will present also the main formulae defining the fractional derivatives.

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In this paper, we focus on large-scale and dense Cyber- Physical Systems, and discuss methods that tightly integrate communication and computing with the underlying physical environment. We present Physical Dynamic Priority Dominance ((PD)2) protocol that exemplifies a key mechanism to devise low time-complexity communication protocols for large-scale networked sensor systems. We show that using this mechanism, one can compute aggregate quantities such as the maximum or minimum of sensor readings in a time-complexity that is equivalent to essentially one message exchange. We also illustrate the use of this mechanism in a more complex task of computing the interpolation of smooth as well as non-smooth sensor data in very low timecomplexity.

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A new algorithm is proposed for scheduling preemptible arbitrary-deadline sporadic task systems upon multiprocessor platforms, with interprocessor migration permitted. This algorithm is based on a task-splitting approach - while most tasks are entirely assigned to specific processors, a few tasks (fewer than the number of processors) may be split across two processors. This algorithm can be used for two distinct purposes: for actually scheduling specific sporadic task systems, and for feasibility analysis. Simulation- based evaluation indicates that this algorithm offers a significant improvement on the ability to schedule arbitrary- deadline sporadic task systems as compared to the contemporary state-of-art. With regard to feasibility analysis, the new algorithm is proved to offer superior performance guarantees in comparison to prior feasibility tests.

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Due to the growing complexity and dynamism of many embedded application domains (including consumer electronics, robotics, automotive and telecommunications), it is increasingly difficult to react to load variations and adapt the system's performance in a controlled fashion within an useful and bounded time. This is particularly noticeable when intending to benefit from the full potential of an open distributed cooperating environment, where service characteristics are not known beforehand and tasks may exhibit unrestricted QoS inter-dependencies. This paper proposes a novel anytime adaptive QoS control policy in which the online search for the best set of QoS levels is combined with each user's personal preferences on their services' adaptation behaviour. Extensive simulations demonstrate that the proposed anytime algorithms are able to quickly find a good initial solution and effectively optimise the rate at which the quality of the current solution improves as the algorithms are given more time to run, with a minimum overhead when compared against their traditional versions.

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Due to the growing complexity and adaptability requirements of real-time embedded systems, which often exhibit unrestricted inter-dependencies among supported services and user-imposed quality constraints, it is increasingly difficult to optimise the level of service of a dynamic task set within an useful and bounded time. This is even more difficult when intending to benefit from the full potential of an open distributed cooperating environment, where service characteristics are not known beforehand. This paper proposes an iterative refinement approach for a service’s QoS configuration taking into account services’ inter-dependencies and quality constraints, and trading off the achieved solution’s quality for the cost of computation. Extensive simulations demonstrate that the proposed anytime algorithm is able to quickly find a good initial solution and effectively optimises the rate at which the quality of the current solution improves as the algorithm is given more time to run. The added benefits of the proposed approach clearly surpass its reducedoverhead.

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We use the term Cyber-Physical Systems to refer to large-scale distributed sensor systems. Locating the geographic coordinates of objects of interest is an important problemin such systems. We present a new distributed approach to localize objects and events of interest in time complexity independent of number of nodes.

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OBJECTIVE To analyze the effectiveness of the Chilean System of Childhood Welfare in transferring benefits to socially vulnerable families. METHODS A cross-sectional study with a sample of 132 families from the Metropolitan Region, Chile, stratified according to degree of social vulnerability, between September 2011 and January 2012. Semi-structured interviews were conducted with mothers of the studied families in public health facilities or their households. The variables studied were family structure, psychosocial risk in the family context and integrated benefits from the welfare system in families that fulfill the necessary requirements for transfer of benefits. Descriptive statistics to measure location and dispersion were calculated. A binary logistic regression, which accounts for the sample size of the study, was carried out. RESULTS The groups were homogenous regarding family size, the presence of biological father in the household, the number of relatives living in the same dwelling, income generation capacity and the rate of dependency and psychosocial risk (p ≥ 0.05). The transfer of benefits was low in all three groups of the sample (≤ 23.0%). The benefit with the best coverage in the system was the Single Family Subsidy, whose transfer was associated with the size of the family, the presence of relatives in the dwelling, the absence of the father in the household, a high rate of dependency and a high income generation capacity (p ≤ 0.10). CONCLUSIONS The effectiveness of benefit transfer was poor, especially in families that were extremely socially vulnerable. Further explanatory studies of benefit transfers to the vulnerable population, of differing intensity and duration, are required in order to reduce health disparities and inequalities.

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A MATLAB/SIMULINK-based simulator was employed for studies concerning the control of baker’s yeast fed-batch fermentation. Four control algorithms were implemented and compared: the classical PID control, two discrete versions- modified velocity and position algorithms, and a fuzzy law. The simulation package was seen to be an efficient tool for the simulation and tests of control strategies of the nonlinear process.

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Most of today’s embedded systems are required to work in dynamic environments, where the characteristics of the computational load cannot always be predicted in advance. Furthermore, resource needs are usually data dependent and vary over time. Resource constrained devices may need to cooperate with neighbour nodes in order to fulfil those requirements and handle stringent non-functional constraints. This paper describes a framework that facilitates the distribution of resource intensive services across a community of nodes, forming temporary coalitions for a cooperative QoSaware execution. The increasing need to tailor provided service to each application’s specific needs determines the dynamic selection of peers to form such a coalition. The system is able to react to load variations, degrading its performance in a controlled fashion if needed. Isolation between different services is achieved by guaranteeing a minimal service quality to accepted services and by an efficient overload control that considers the challenges and opportunities of dynamic distributed embedded systems.

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Penalty and Barrier methods are normally used to solve Nonlinear Optimization Problems constrained problems. The problems appear in areas such as engineering and are often characterised by the fact that involved functions (objective and constraints) are non-smooth and/or their derivatives are not know. This means that optimization methods based on derivatives cannot net used. A Java based API was implemented, including only derivative-free optimizationmethods, to solve both constrained and unconstrained problems, which includes Penalty and Barriers methods. In this work a new penalty function, based on Fuzzy Logic, is presented. This function imposes a progressive penalization to solutions that violate the constraints. This means that the function imposes a low penalization when the violation of the constraints is low and a heavy penalisation when the violation is high. The value of the penalization is not known in beforehand, it is the outcome of a fuzzy inference engine. Numerical results comparing the proposed function with two of the classic penalty/barrier functions are presented. Regarding the presented results one can conclude that the prosed penalty function besides being very robust also exhibits a very good performance.

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Different heating systems have been used in pultrusion, where the most widely used heaters are planar resistances. The primary objective of this study was to develop an improved heating system and compare its performance with that of a system with planar resistances. In this study, thermography was used to better understand the temperature profile along the die. Finite element analysis was performed to determine the amount of energy consumed by the heating systems. Improvements were made to the die to test the new heating system, and it was found that the new system reduced the setup time and energy consumption by approximately 57%.

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In this paper an algorithm for the calculation of the root locus of fractional linear systems is presented. The proposed algorithm takes advantage of present day computational resources and processes directly the characteristic equation, avoiding the limitations revealed by standard methods. The results demonstrate the good performance for different types of expressions.

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This paper focus on a demand response model analysis in a smart grid context considering a contingency scenario. A fuzzy clustering technique is applied on the developed demand response model and an analysis is performed for the contingency scenario. Model considerations and architecture are described. The demand response developed model aims to support consumers decisions regarding their consumption needs and possible economic benefits.

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This paper presents a comparison between proportional integral control approaches for variable speed wind turbines. Integer and fractional-order controllers are designed using linearized wind turbine model whilst fuzzy controller also takes into account system nonlinearities. These controllers operate in the full load region and the main objective is to extract maximum power from the wind turbine while ensuring the performance and reliability required to be integrated into an electric grid. The main contribution focuses on the use of fractional-order proportional integral (FOPI) controller which benefits from the introduction of one more tuning parameter, the integral fractional-order, taking advantage over integer order proportional integral (PI) controller. A comparison between proposed control approaches for the variable speed wind turbines is presented using a wind turbine benchmark model in the Matlab/Simulink environment. Results show that FOPI has improved system performance when compared with classical PI and fuzzy PI controller outperforms the integer and fractional-order control due to its capability to deal with system nonlinearities and uncertainties. © 2014 IEEE.