A New Control Architecture for Robust Controllers in Rear Electric Traction Passenger HEVs

It is well known that control systems are the core of electronic differential systems (EDSs) in electric vehicles (EVs)/hybrid HEVs (HEVs). However, conventional closed-loop control architectures do not completely match the needed ability to reject noises/disturbances, especially regarding the input acceleration signal incoming from the driver's commands, which makes the EDS (in this case) ineffective. Due to this, in this paper, a novel EDS control architecture is proposed to offer a new approach for the traction system that can be used with a great variety of controllers (e. g., classic, artificial intelligence (AI)-based, and modern/robust theory). In addition to this, a modified proportional-integral derivative (PID) controller, an AI-based neuro-fuzzy controller, and a robust optimal H-infinity controller were designed and evaluated to observe and evaluate the versatility of the novel architecture. Kinematic and dynamic models of the vehicle are briefly introduced. Then, simulated and experimental results were presented and discussed. A Hybrid Electric Vehicle in Low Scale (HELVIS)-Sim simulation environment was employed to the preliminary analysis of the proposed EDS architecture. Later, the EDS itself was embedded in a dSpace 1103 high-performance interface board so that real-time control of the rear wheels of the HELVIS platform was successfully achieved.

Robust modeling using the generalized epsilon-skew-t distribution

In this paper, an alternative skew Student-t family of distributions is studied. It is obtained as an extension of the generalized Student-t (GS-t) family introduced by McDonald and Newey [10]. The extension that is obtained can be seen as a reparametrization of the skewed GS-t distribution considered by Theodossiou [14]. A key element in the construction of such an extension is that it can be stochastically represented as a mixture of an epsilon-skew-power-exponential distribution [1] and a generalized-gamma distribution. From this representation, we can readily derive theoretical properties and easy-to-implement simulation schemes. Furthermore, we study some of its main properties including stochastic representation, moments and asymmetry and kurtosis coefficients. We also derive the Fisher information matrix, which is shown to be nonsingular for some special cases such as when the asymmetry parameter is null, that is, at the vicinity of symmetry, and discuss maximum-likelihood estimation. Simulation studies for some particular cases and real data analysis are also reported, illustrating the usefulness of the extension considered.

Stable water isotopes of precipitation and firn cores from the northern Antarctic Peninsula region as a proxy for climate reconstruction

In order to investigate the climate variability in the northern Antarctic Peninsula region, this paper focuses on the relationship between stable isotope content of precipitation and firn, and main meteorological variables (air temperature, relative humidity, sea surface temperature, and sea ice extent). Between 2008 and 2010, we collected precipitation samples and retrieved firn cores from several key sites in this region. We conclude that the deuterium excess oscillation represents a robust indicator of the meteorological variability on a seasonal to sub-seasonal scale. Low absolute deuterium excess values and the synchronous variation of both deuterium excess and air temperature imply that the evaporation of moisture occurs in the adjacent Southern Ocean. The delta O-18-air temperature relationship is complicated and significant only at a (multi)seasonal scale. Backward trajectory calculations show that air-parcels arriving at the region during precipitation events predominantly originate at the South Pacific Ocean and Bellingshausen Sea. These investigations will be used as a calibration for ongoing and future research in the area, suggesting that appropriate locations for future ice core research are located above 600 m a.s.l. We selected the Plateau Laclavere, Antarctic Peninsula as the most promising site for a deeper drilling campaign.

Evolution of Precambrian life in the Brazilian geological record

Precambrian rocks comprise nearly one-quarter of the surface of Brazil and range from Paleoarchean (ca. 3.6 Ga) to the latest Ediacaran (0.542 Ga) in age. Except for controversial phosphatized 'embryo-like' microfossils like those from the lower Ediacaran Doushantuo Formation, China and complex rangeomorphs, Brazilian research has revealed all major categories of Precambrian life forms described elsewhere - microbialites, biomarkers, silicified microfossils, palynomorphs, vase-shaped microfossils, macroalgae, metazoans, vendobionts and ichnofossils - but the paleobiological significance of this record has been little explored. At least four occurrences of these fossils offer promise for increased understanding of the following aspects of Precambrian biospheric evolution: (i) the relationship of microbialites in 2.1-2.4 Ga old carbonates of the Minas Supergroup in the Quadrilatero Ferrifero, Minas Gerais (the oldest Brazilian fossils) to the development of the early oxygenic atmosphere and penecontemporaneous global tectonic and climatic events; (ii) the evolutionary and biostratigraphic significance of Mesoproterozoic to Ediacaran organic-walled microfossils in central-western Brazil; (iii) diversity and paleoecological significance of vase-shaped heterotrophic protistan microfossils in the Urucum Formation (Jacadigo Group) and possibly the Bocaina Formation (Corumba Group), of Mato Grosso do Sul; and (iv) insights into the record of skeletogenesis and paleoecology of latest Ediacaran metazoans as represented by the abundant organic carapaces of Corumbella and calcareous shells of the index fossil Cloudina, of the Corumba Group, Mato Grosso do Sul. Analysis of the Brazilian Precambrian fossil record thus holds great potential for augmenting paleobiological knowledge of this crucial period on Earth and for developing more robust hypotheses regarding possible origins and evolutionary pathways of biospheres on other planets. Received 26 February 2012, accepted 17 May 2012, first published online 18 June 2012

G'day Gondwana - the final accretion of a supercontinent: U-Pb ages from the post-orogenic Sao Vicente Granite, northern Paraguay Belt, Brazil

The Paraguay Belt in central South America is part of a larger chain of orogenic belts, including the Araguaia Belt to the northeast and potentially the Pampean Belt to the south, which are believed to mark the suture zone of the Clymene Ocean - interpreted amongst the youngest of the Gondwana amalgamation orogens. The post-orogenic Sao Vicente Granite crops out in the northern Paraguay Belt and cuts the basal unit of the deformed and metamorphosed Cuiaba Group. The age of this granite therefore provides a long sort after minimum age for orogenesis within the belt. Dating crystallisation of this important intrusion is challenging due to the presence of considerable common-Pb. However, based on LA-ICPMS dating of more than 100 zircons from three separate samples we interpret a robust crystallisation age for the Sao Vicente batholith at 518 +/- 4 Ma. This age constrains the termination of deformation within the Paraguay Belt and the final accretion of the supercontinent Gondwana. (C) 2011 International Association for Gondwana Research. Published by Elsevier B.V. All rights reserved.

Robust and optimal adjustment of Power System Stabilizers through Linear Matrix Inequalities

This work presents the application of Linear Matrix Inequalities to the robust and optimal adjustment of Power System Stabilizers with pre-defined structure. Results of some tests show that gain and zeros adjustments are sufficient to guarantee robust stability and performance with respect to various operating points. Making use of the flexible structure of LMI's, we propose an algorithm that minimizes the norm of the controllers gain matrix while it guarantees the damping factor specified for the closed loop system, always using a controller with flexible structure. The technique used here is the pole placement, whose objective is to place the poles of the closed loop system in a specific region of the complex plane. Results of tests with a nine-machine system are presented and discussed, in order to validate the algorithm proposed. (C) 2012 Elsevier Ltd. All rights reserved.

ACTIVE NETWORKS THAT MAXIMIZE THE AMOUNT OF INFORMATION TRANSMISSION

This work clarifies the relationship between network circuit (topology) and behavior (information transmission and synchronization) in active networks, e. g. neural networks. As an application, we show how to determine a network topology that is optimal for information transmission. By optimal, we mean that the network is able to transmit a large amount of information, it possesses a large number of communication channels, and it is robust under large variations of the network coupling configuration. This theoretical approach is general and does not depend on the particular dynamic of the elements forming the network, since the network topology can be determined by finding a Laplacian matrix (the matrix that describes the connections and the coupling strengths among the elements) whose eigenvalues satisfy some special conditions. To illustrate our ideas and theoretical approaches, we use neural networks of electrically connected chaotic Hindmarsh-Rose neurons.

Robust statistical modeling using the Birnbaum-Saunders-t distribution applied to insurance

In this paper, we carry out robust modeling and influence diagnostics in Birnbaum-Saunders (BS) regression models. Specifically, we present some aspects related to BS and log-BS distributions and their generalizations from the Student-t distribution, and develop BS-t regression models, including maximum likelihood estimation based on the EM algorithm and diagnostic tools. In addition, we apply the obtained results to real data from insurance, which shows the uses of the proposed model. Copyright (c) 2011 John Wiley & Sons, Ltd.

New Optimization Algorithms for Structural Reliability Analysis

Solution of structural reliability problems by the First Order method require optimization algorithms to find the smallest distance between a limit state function and the origin of standard Gaussian space. The Hassofer-Lind-Rackwitz-Fiessler (HLRF) algorithm, developed specifically for this purpose, has been shown to be efficient but not robust, as it fails to converge for a significant number of problems. On the other hand, recent developments in general (augmented Lagrangian) optimization techniques have not been tested in aplication to structural reliability problems. In the present article, three new optimization algorithms for structural reliability analysis are presented. One algorithm is based on the HLRF, but uses a new differentiable merit function with Wolfe conditions to select step length in linear search. It is shown in the article that, under certain assumptions, the proposed algorithm generates a sequence that converges to the local minimizer of the problem. Two new augmented Lagrangian methods are also presented, which use quadratic penalties to solve nonlinear problems with equality constraints. Performance and robustness of the new algorithms is compared to the classic augmented Lagrangian method, to HLRF and to the improved HLRF (iHLRF) algorithms, in the solution of 25 benchmark problems from the literature. The new proposed HLRF algorithm is shown to be more robust than HLRF or iHLRF, and as efficient as the iHLRF algorithm. The two augmented Lagrangian methods proposed herein are shown to be more robust and more efficient than the classical augmented Lagrangian method.

A Robust Structural PGN Model for Control of Cell-Cycle Progression Stabilized by Negative Feedbacks

The cell division cycle comprises a sequence of phenomena controlled by a stable and robust genetic network. We applied a probabilistic genetic network (PGN) to construct a hypothetical model with a dynamical behavior displaying the degree of robustness typical of the biological cell cycle. The structure of our PGN model was inspired in well-established biological facts such as the existence of integrator subsystems, negative and positive feedback loops, and redundant signaling pathways. Our model represents genes interactions as stochastic processes and presents strong robustness in the presence of moderate noise and parameters fluctuations. A recently published deterministic yeast cell-cycle model does not perform as well as our PGN model, even upon moderate noise conditions. In addition, self stimulatory mechanisms can give our PGN model the possibility of having a pacemaker activity similar to the observed in the oscillatory embryonic cell cycle.

Minimally invasive esthetic therapy: a case report describing the advantages of a multidisciplinary approach

The decision-making process for the treatment of esthetic areas is based on the achievement of a healthy, harmonious, and pleasant smile. These conditions are directly associated with a solid knowledge of tooth anatomy and proportions, as well as the smile line, soft tissue morphology, and osseous architecture. To achieve these objectives, a multidisciplinary approach may be necessary to create long-term harmony between the final restoration and the adjacent teeth, and the health of the surrounding soft and hard tissues. This case report describes the application of a minimally invasive therapy on a 33-year-old woman seeking esthetic treatment. Minimally invasive periodontal plastic surgery associated with porcelain laminate veneers yielded satisfactory esthetics and minimal trauma to dental and periodontal tissues. Such a combined approach may be considered a viable option for the improvement of "white" and "red" esthetics.

Calculation of parameter ranges for robust gain tuning of power system controllers

This work proposes a computational tool to assist power system engineers in the field tuning of power system stabilizers (PSSs) and Automatic Voltage Regulators (AVRs). The outcome of this tool is a range of gain values for theses controllers within which there is a theoretical guarantee of stability for the closed-loop system. This range is given as a set of limit values for the static gains of the controllers of interest, in such a way that the engineer responsible for the field tuning of PSSs and/or AVRs can be confident with respect to system stability when adjusting the corresponding static gains within this range. This feature of the proposed tool is highly desirable from a practical viewpoint, since the PSS and AVR commissioning stage always involve some readjustment of the controller gains to account for the differences between the nominal model and the actual behavior of the system. By capturing these differences as uncertainties in the model, this computational tool is able to guarantee stability for the whole uncertain model using an approach based on linear matrix inequalities. It is also important to remark that the tool proposed in this paper can also be applied to other types of parameters of either PSSs or Power Oscillation Dampers, as well as other types of controllers (such as speed governors, for example). To show its effectiveness, applications of the proposed tool to two benchmarks for small signal stability studies are presented at the end of this paper.