A Novel Blended State Estimated Adaptive Controller for Voltage and Current Control of Microgrid against Unknown Noise

© 2013 IEEE. In this study, a novel blended state estimated adaptive controller is designed for voltage and current control of microgrid against unknown noise. The core feature of the microgrid (MG) is its ability to integrate more than one distributed energy resource into the main grid. The state of a microgrid may deteriorate due to many reasons, for example malicious cyber-attacks, disturbances, packet losses, etc. Therefore, it is necessary to achieve the true state of the system to enhance the control requirement and automation of the microgrid. To achieve the true state of a microgrid, this study proposes the use of an algorithm based on the unscented kalman filter (UKF). The proposed state estimator technique is developed using an unscented-transformation and sigma-points measurement technique capable of minimizing the mean and covariance of a nonlinear cost function to estimate the true state of a single-phase, three-phase single-source and three-phase multi-source microgrid system. The advantage of the proposed estimator over using extended kalman filter (EKF) is investigated in simulations. The results demonstrate that the use of the UKF estimator produces a superior estimation of the system compared with the use of the EKF. An adaptive PID controller is also developed and used in system conjunction with the estimator to regulate its voltage and current against the number of loads. Deviation in load parameters hamper the function of the MG system. The performance of the developed controller is also evaluated against number of loads. Results indicate the controller provides a more stable and high-tracking performance with the inclusion of the UKF in the system

Remote Sensing and Geosciences for Archaeology

This book collects more than 20 papers, written by renowned experts and scientists from across the globe, that showcase the state-of-the-art and forefront research in archaeological remote sensing and the use of geoscientific techniques to investigate archaeological records and cultural heritage. Very high resolution satellite images from optical and radar space-borne sensors, airborne multi-spectral images, ground penetrating radar, terrestrial laser scanning, 3D modelling, Geographyc Information Systems (GIS) are among the techniques used in the archaeological studies published in this book. The reader can learn how to use these instruments and sensors, also in combination, to investigate cultural landscapes, discover new sites, reconstruct paleo-landscapes, augment the knowledge of monuments, and assess the condition of heritage at risk. Case studies scattered across Europe, Asia and America are presented: from the World UNESCO World Heritage Site of Lines and Geoglyphs of Nasca and Palpa to heritage under threat in the Middle East and North Africa, from coastal heritage in the intertidal flats of the German North Sea to Early and Neolithic settlements in Thessaly. Beginners will learn robust research methodologies and take inspiration; mature scholars will for sure derive inputs for new research and applications

Micro-RNA family that modulates fibrosis and uses thereof

The present invention relates to the identification of a microRNA family, designated miR-29a-c, that is a key regulator of fibrosis in cardiac tissue. The inventors show that members of the miR-29 family are down-regulated in the heart tissue in response to stress, and are up-regulated in heart tissue of mice that are resistant to both stress and fibrosis. Also provided are methods of modulating expression and activity of the miR-29 family of miRNAs as a treatment for fibrotic disease, including cardiac hypertrophy, skeletal muscle fibrosis other fibrosis related diseases and collagen loss-related disease.Board of Regents, University of Texas Syste

Adjoint-based aerodynamic shape optimization on unstructured meshes

In this paper, the exact discrete adjoint of an unstructured finite-volume formulation of the Euler equations in two dimensions is derived and implemented. The adjoint equations are solved with the same implicit scheme as used for the flow equations. The scheme is modified to efficiently account for multiple functionals simultaneously. An optimization framework, which couples an analytical shape parameterization to the flow/adjoint solver and to algorithms for constrained optimization, is tested on airfoil design cases involving transonic as well as supersonic flows. The effect of some approximations in the discrete adjoint, which aim at reducing the complexity of the implementation, is shown in terms of optimization results rather than only in terms of gradient accuracy. The shape-optimization method appears to be very efficient and robust

Biological reserves Rare Species and the Opportunity Cost of Diversity

The preservation of species diversity generally suggests protection of either the greatest number of species possible or all species. Requiring representation of each species in at least one parcel in the system and seeking the minimum number of parcels in the reserve system to achieve this requirement is termed the Species Set Covering Problem (SSCP). Nonetheless, it is important, as well, to consider the rarest of species, as their populations are the most in need of protection to assure their survival. This paper uses zero-one programming models and an existing data set to study species protection, rarity and the opportunity costs of diversity. We employ for this purpose an integer programming model that uses the SSCP format to require at least one representation of each and every species, but that seeks in addition protection of the rarest species. This is achieved by maximizing redundant coverage of those species designated as rare. Results are then compared to those of the SSCP. Recognizing that resources available for conservation purchases could well be insufficient to represent all species at least once, we structure a model aimed at trading-off first coverage of the greatest number of species against redundant coverage of rare species. We develop a tradeoff curve for this multi-objective problem in order to evaluate the opportunity cost of covering more species as redundant coverage of rare species decreases ­and vice versa. Finally, various possible rarity sets and various budget proxies are considered along with their impacts on conservation policies, Pareto optimality and on the opportunity cost of diversity

Micro-RNAS that control myosin expression and myofiber identity

The present invention relates to the identification of two microRNAs, miR-499 and miR-208b, that repress fast skeletal muscle contractile protein genes. Expression of miR-499 and/or miR-208b can be used to repress fast fiber genes and activate slow fiber genes in the treatment of musculoskeletal disorders. Inhibition of miR-499 and/or miR-208b is proposed as a treatment for cardiac hypertrophy, myocardial infarction, and/or heart failure. Pharmaceutical compositions comprising antagonists and agonists of miR-499 and miR-208b function are also disclosed.Board of Regents, University of Texas Syste

Quantum structural fluxion in superconducting lanthanum polyhydride

The discovery of 250-kelvin superconducting lanthanum polyhydride under high pressure marked a significant advance toward the realization of a room‐temperature superconductor. X-ray diffraction (XRD) studies reveal a nonstoichiometric LaH9.6 or LaH10±δ polyhydride responsible for the superconductivity, which in the literature is commonly treated as LaH10 without accounting for stoichiometric defects. Here, we discover significant nuclear quantum effects (NQE) in this polyhydride, and demonstrate that a minor amount of stoichiometric defects will cause quantum proton diffusion in the otherwise rigid lanthanum lattice in the ground state. The diffusion coefficient reaches ~10−7 cm2/s in LaH9.63 at 150 gigapascals and 240 kelvin, approaching the upper bound value of interstitial hydrides at comparable temperatures. A puzzling phenomenon observed in previous experiments, the positive pressure dependence of the superconducting critical temperature Tc below 150 gigapascals, is explained by a modulation of the electronic structure due to a premature distortion of the hydrogen lattice in this quantum fluxional structure upon decompression, and resulting changes of the electron-phonon coupling. This finding suggests the coexistence of the quantum proton fluxion and hydrogen-induced superconductivity in this lanthanum polyhydride, and leads to an understanding of the structural nature and superconductivity of nonstoichiomectric hydrogen-rich materials.The project is supported by the National Natural Science Foundation of China (Grant No. 11974135, 11874176, 12174170, and 12074138), the Natural Sciences and Engineering Research Council of Canada, the EPSRC through grants EP/P022596/1, and EP/S021981/1, and the startup funds of the office of the Dean of SASN of Rutgers University-Newark. P. T. S. thanks the Department of Materials Science and Metallurgy at the University of Cambridge for generous funding. The work of P. T. S. is further supported through a Trinity Hall research studentship. I. E. acknowledges financial support by the European Research Council (ERC) under the EuropeanUnion’sHorizon 2020 research and innovation program (grant agreement no. 802533)

2014 - The Nineteenth Annual Symposium of Student Scholars

The full program book from the Nineteenth Annual Symposium of Student Scholars, held on April 17, 2014. Includes abstracts from the presentations and posters.https://digitalcommons.kennesaw.edu/sssprograms/1013/thumbnail.jp

Recursive model-based virtual in-cylinder pressure sensing for internal combustion engines

Das Drucksignal im Zylinder ist ein sehr nützlicher Indikator für moderne Hochleistungs-Verbrennungsmotoren. Allerdings sind direkte Messungen des Zylinderdrucks unpraktisch, da die Bedingungen in den Zylindern von Verbrennungsmotoren ungünstig sind sowie die Installation von Zylinderdrucksensoren schwierig ist. Zahlreiche Methoden (z. B. virtuelle Messmethoden) wurden untersucht, um den Druck im Zylinder aus extern gemessenen Signalen zu rekonstruieren, z. B. aus dem Schwingungssignal des Motorblocks und der Winkelgeschwindigkeit der Kurbelwelle. Viele der vorgeschlagenen Methoden haben vielversprechende Ergebnisse erbracht. Allerdings gibt es immer noch einige Nachteile wie z.B. eine schlecht konditionierte Inversion oder die Notwendigkeit einer großen Datenmenge, um ein inverses Modell durch künstliche neuronale Netze abzuleiten. In dieser Arbeit werden unter Berücksichtigung der aktuellen Zylinderdruck-Rekonstruktionsprobleme lineare modellbasierte, nichtlineare modellbasierte und inverse modellbasierte ZylinderdruckRekonstruktionsmethoden vorgeschlagen, die eine Alternative zu den bestehenden ZylinderdruckRekonstruktionsmethoden darstellen. Alle vorgeschlagenen Methoden basieren auf der rekursiven Zustandsrekonstruktion unter Verwendung des Kalman-Filters oder eines Beobachters, so dass eine direkte Inversion vermieden werden kann. Darüber hinaus werden alle vorgeschlagenen Methoden rekursiv im Zeitbereich durchgeführt, so dass sie für Echtzeit-Implementierungen geeignet sind und auch keine Probleme im Frequenzbereich, wie z. B. Leckeffekte, aufweisen. Darüber hinaus handelt es sich bei allen vorgeschlagenen Methoden um modellbasierte Methoden, und die Modelle werden mit Hilfe von Systemidentifikationstechniken unter Ausschluss künstlicher neuronaler Netze identifiziert, so dass keine großen Datenmengen erforderlich sind. Für die Systemidentifikation und die Validierung der vorgeschlagenen Methoden wurden Datensätze eines Vierzylinder-Dieselmotors unter verschiedenen Motorbetriebsbedingungen erfasst. Die erfassten Daten reichen von der Betriebsbedingung 1200 U/min, 60 Nm bis zur Betriebsbedingung 3000 U/min, 180 Nm. Die rekonstruierten Zylinderdruckkurven und die beiden Verbrennungsmetriken Zylinderdruckspitze und Spitzenort wurden zur Validierung der vorgeschlagenen Zylinderdruckrekonstruktionsmethoden verwendet. Die Ergebnisse der Rekonstruktion des Zylinderdrucks, die mit den in dieser Arbeit vorgeschlagenen Methoden erzielt wurden, zeigen, dass alle vorgeschlagenen Methoden sowohl unter stationären als auch unter nicht-stationären Betriebsbedingungen verwendet werden können und dass die Ergebnisse der Rekonstruktion des Zylinderdrucks mit den Ergebnissen der bestehenden Methoden zur Rekonstruktion des Zylinderdrucks vergleichbar sind. Darüber hinaus kann festgestellt werden, dass es mehrere Faktoren gibt, die die Genauigkeit der Druckrekonstruktion beeinflussen, wie z.B. die Qualität der identifizierten Modelle, des Verzögerungsblocks und der momentanen Motordrehzahl.The in-cylinder pressure signal is a very useful indicator for modern high-performance internal combustion engines. Unfortunately, direct measurements of the in-cylinder pressure are impractical because installing cylinder pressure sensors is difficult and conditions in internal combustion engine cylinders are adverse. Numerous methods (such as virtual sensing methods) have been investigated to reconstruct the incylinder pressure from externally measured signals, such as the engine block structural vibration signal and the engine crank angular speed. Many of the proposed methodologies have shown promising results. However, there still exist some drawbacks, such as ill-conditioned inversion and the need of large number of data to derive an inverse model by artificial neural networks. In this thesis, considering current in-cylinder pressure reconstruction problems, linear model-based, nonlinear model-based, and inverse model-based in-cylinder pressure reconstruction methods, which are alternative to existing cylinder pressure reconstruction methods, are proposed. All the proposed methods are based on the recursive state reconstruction by using the Kalman filter or observer such that a direct inversion can be avoided. Moreover, all the proposed methods are recursively conducted in time domain, so they are suitable for real-time implementations and they also do not have frequency-domain problems such as spectral leakage. Additionally, all the proposed methods are model-based methods, and the models are identified by using system identification techniques excluding artificial neural networks, so the need of a large number of data is not necessary. For system identification and the validation of the proposed methods, the datasets under different engine operating conditions were acquired from a four-cylinder diesel engine. Data acquired is from the operating condition 1200 rpm, 60 Nm to the operating condition 3000 rpm, 180 Nm. The reconstructed cylinder pressure curves and two combustion metrics cylinder pressure peak and peak location were used for validating the proposed cylinder pressure reconstruction methods. According to the cylinder pressure reconstruction results obtained based on using the proposed methods in this thesis, it can be found that all the proposed methods can be used under both stationary and non-stationary operating conditions, and the reconstructed cylinder pressure results are comparable among existing cylinder pressure reconstruction methods. Furthermore, it can also be found that there exist several factors affecting the pressure reconstruction accuracy, such as the quality of the identified models, delay block and instantaneous engine cycle frequency