97 resultados para Non-Ideal Duffing System
Resumo:
The introduction of the Tesla in 2008 has demonstrated to the public of the potential of electric vehicles in terms of reducing fuel consumption and green-house gas from the transport sector. It has brought electric vehicles back into the spotlight worldwide at a moment when fossil fuel prices were reaching unexpected high due to increased demand and strong economic growth. The energy storage capabilities from of fleets of electric vehicles as well as the potentially random discharging and charging offers challenges to the grid in terms of operation and control. Optimal scheduling strategies are key to integrating large numbers of electric vehicles and the smart grid. In this paper, state-of-the-art optimization methods are reviewed on scheduling strategies for the grid integration with electric vehicles. The paper starts with a concise introduction to analytical charging strategies, followed by a review of a number of classical numerical optimization methods, including linear programming, non-linear programming, dynamic programming as well as some other means such as queuing theory. Meta-heuristic techniques are then discussed to deal with the complex, high-dimensional and multi-objective scheduling problem associated with stochastic charging and discharging of electric vehicles. Finally, future research directions are suggested.
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This document describes best practice and evidence based recommendations for the use of FDG-PET/CT for the purposes of radiotherapy target volume delineation (TVD) for curative intent treatment of non-small cell lung cancer (NSCLC). These recommendations have been written by an expert advisory group, convened by the International Atomic Energy Agency (IAEA) to facilitate a Coordinated Research Project (CRP) aiming to improve the applications of PET based radiation treatment planning (RTP) in low and middle income countries. These guidelines can be applied in routine clinical practice of radiotherapy TVD, for NSCLC patients treated with concurrent chemoradiation or radiotherapy alone, where FDG is used, and where a calibrated PET camera system equipped for RTP patient positioning is available. Recommendations are provided for PET and CT image visualization and interpretation, and for tumor delineation using planning CT with and without breathing motion compensation.
Resumo:
Cascade control is one of the routinely used control strategies in industrial processes because it can dramatically improve the performance of single-loop control, reducing both the maximum deviation and the integral error of the disturbance response. Currently, many control performance assessment methods of cascade control loops are developed based on the assumption that all the disturbances are subject to Gaussian distribution. However, in the practical condition, several disturbance sources occur in the manipulated variable or the upstream exhibits nonlinear behaviors. In this paper, a general and effective index of the performance assessment of the cascade control system subjected to the unknown disturbance distribution is proposed. Like the minimum variance control (MVC) design, the output variances of the primary and the secondary loops are decomposed into a cascade-invariant and a cascade-dependent term, but the estimated ARMA model for the cascade control loop based on the minimum entropy, instead of the minimum mean squares error, is developed for non-Gaussian disturbances. Unlike the MVC index, an innovative control performance index is given based on the information theory and the minimum entropy criterion. The index is informative and in agreement with the expected control knowledge. To elucidate wide applicability and effectiveness of the minimum entropy cascade control index, a simulation problem and a cascade control case of an oil refinery are applied. The comparison with MVC based cascade control is also included.
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A novel model-based principal component analysis (PCA) method is proposed in this paper for wide-area power system monitoring, aiming to tackle one of the critical drawbacks of the conventional PCA, i.e. the incapability to handle non-Gaussian distributed variables. It is a significant extension of the original PCA method which has already shown to outperform traditional methods like rate-of-change-of-frequency (ROCOF). The ROCOF method is quick for processing local information, but its threshold is difficult to determine and nuisance tripping may easily occur. The proposed model-based PCA method uses a radial basis function neural network (RBFNN) model to handle the nonlinearity in the data set to solve the no-Gaussian issue, before the PCA method is used for islanding detection. To build an effective RBFNN model, this paper first uses a fast input selection method to remove insignificant neural inputs. Next, a heuristic optimization technique namely Teaching-Learning-Based-Optimization (TLBO) is adopted to tune the nonlinear parameters in the RBF neurons to build the optimized model. The novel RBFNN based PCA monitoring scheme is then employed for wide-area monitoring using the residuals between the model outputs and the real PMU measurements. Experimental results confirm the efficiency and effectiveness of the proposed method in monitoring a suite of process variables with different distribution characteristics, showing that the proposed RBFNN PCA method is a reliable scheme as an effective extension to the linear PCA method.
Resumo:
In Holcus lanatus L. phosphate and arsenate are taken up by the same transport system. Short-term uptake kinetics of the high affinity arsenate transport system were determined in excised roots of arsenate-tolerant and non-tolerant genotypes. In tolerant plants the Vmax of ion uptake in plants grown in phosphate-free media was decreased compared to non-tolerant plants, and the affinity of the uptake system was lower than in the non-tolerant plants. Both the reduction in Vmax and the increase in Km led to reduced arsenate influx into tolerant roots. When the two genotypes were grown in nutrient solution containing high levels of phosphate, there was little change in the uptake kinetics in tolerant plants. In non-tolerant plants, however, there was a marked decrease in the Vmax to the level of the tolerant plants but with little change in the Km. This suggests that the low rate of arsenate uptake over a wide range of differing root phosphate status is due to loss of induction of the synthesis of the arsenate (phosphate) carrier. © 1992 Oxford University Press.
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The Terawatt Apparatus for Relativistic And Non-linear Interdisciplinary Science (TARANIS), installed in the Centre for Plasma Physics at the Queen's University Belfast, supports a wide ranging science program, including laser-driven particle acceleration, X-ray lasers and high energy density physics experiments. We present (1) an overview of the laser facility, (2) results of preliminary investigations on proton acceleration, laser action at 13.9 nm and Kα sources and (3) speculation on future experiments using these extreme sources.
Resumo:
Key challenges for contemporary neorepublicans are identified and explored. Firstly, the attempt to maintain a sharp line between neorepublicanism and the wider family of liberal–egalitarian political theories is questioned. Secondly, in response to challenges from democratic theorists, it is argued that republicanism needs to effect an appropriate rapprochement with the ideal of collective political autonomy, on which it appears to rely. Thirdly, it is argued that freedom as non-domination draws so heavily on the idea of equal respect that it is hard to maintain that freedom is the sole value grounding the theory. Finally, it is suggested that the consequentialist framework of Pettit’s theory imposes significant limitations on republican social justice. How republican political theorists respond to these challenges will determine whether the neorepublican revival will be seen as enriching contemporary debates about democracy and social justice or as a retreat from more ambitious accounts of freedom and justice.