Predictive control of a Boeing 747 aircraft using an FPGA

New embedded predictive control applications call for more eficient ways of solving quadratic programs (QPs) in order to meet demanding real-time, power and cost requirements. A single precision QP-on-a-chip controller is proposed, implemented in afield-programmable gate array (FPGA) with an iterative linear solver at its core. A novel offline scaling procedure is introduced to aid the convergence of the reduced precision solver. The feasibility of the proposed approach is demonstrated with a real-time hardware-in-the-loop (HIL) experimental setup where an ML605 FPGA board controls a nonlinear model of a Boeing 747 aircraft running on a desktop PC through an Ethernet link. Simulations show that the quality of the closed-loop control and accuracy of individual solutions is competitive with a conventional double precision controller solving linear systems using a Riccati recursion. © 2012 IFAC.

A backward-simulation based Rao-Blackwellized particle smoother for conditionally linear Gaussian models

In this article, we develop a new Rao-Blackwellized Monte Carlo smoothing algorithm for conditionally linear Gaussian models. The algorithm is based on the forward-filtering backward-simulation Monte Carlo smoother concept and performs the backward simulation directly in the marginal space of the non-Gaussian state component while treating the linear part analytically. Unlike the previously proposed backward-simulation based Rao-Blackwellized smoothing approaches, it does not require sampling of the Gaussian state component and is also able to overcome certain normalization problems of two-filter smoother based approaches. The performance of the algorithm is illustrated in a simulated application. © 2012 IFAC.

Twisting transition between crystalline and fibrillar phases of aggregated peptides

We study two distinctly ordered condensed phases of polypeptide molecules, amyloid fibrils and amyloidlike microcrystals, and the first-order twisting phase transition between these two states. We derive a single free-energy form which connects both phases. Our model identifies relevant degrees of freedom for describing the collective behavior of supramolecular polypeptide structures, reproduces accurately the results from molecular dynamics simulations as well as from experiments, and sheds light on the uniform nature of the dimensions of different peptide fibrils. © 2012 American Physical Society.

An online expectation-maximisation algorithm for nonnegative matrix factorisation models

In this paper we formulate the nonnegative matrix factorisation (NMF) problem as a maximum likelihood estimation problem for hidden Markov models and propose online expectation-maximisation (EM) algorithms to estimate the NMF and the other unknown static parameters. We also propose a sequential Monte Carlo approximation of our online EM algorithm. We show the performance of the proposed method with two numerical examples. © 2012 IFAC.

A hybrid density functional view of native vacancies in gallium nitride.

We investigated the transition energy levels of the vacancy defects in gallium nitride by means of a hybrid density functional theory approach (DFT). We show that, in contrast to predictions from a recent study on the level of purely local DFT, the inclusion of screened exchange stabilizes the triply positive charge state of the nitrogen vacancy for Fermi energies close to the valence band. On the other hand, the defect levels associated with the negative charge states of the nitrogen vacancy hybridize with the conduction band and turn out to be energetically unfavorable, except for high n-doping. For the gallium vacancy, the increased magnetic splitting between up-spin and down-spin bands due to stronger exchange interactions in sX-LDA pushes the defect levels deeper into the band gap and significantly increases the associated charge transition levels. Based on these results, we propose the ϵ(0| - 1) transition level as an alternative candidate for the yellow luminescence in GaN.

Observing graphene grow: catalyst-graphene interactions during scalable graphene growth on polycrystalline copper.

Complementary in situ X-ray photoelectron spectroscopy (XPS), X-ray diffractometry, and environmental scanning electron microscopy are used to fingerprint the entire graphene chemical vapor deposition process on technologically important polycrystalline Cu catalysts to address the current lack of understanding of the underlying fundamental growth mechanisms and catalyst interactions. Graphene forms directly on metallic Cu during the high-temperature hydrocarbon exposure, whereby an upshift in the binding energies of the corresponding C1s XPS core level signatures is indicative of coupling between the Cu catalyst and the growing graphene. Minor carbon uptake into Cu can under certain conditions manifest itself as carbon precipitation upon cooling. Postgrowth, ambient air exposure even at room temperature decouples the graphene from Cu by (reversible) oxygen intercalation. The importance of these dynamic interactions is discussed for graphene growth, processing, and device integration.

Introducing carbon diffusion barriers for uniform, high-quality graphene growth from solid sources.

Carbon diffusion barriers are introduced as a general and simple method to prevent premature carbon dissolution and thereby to significantly improve graphene formation from the catalytic transformation of solid carbon sources. A thin Al2O3 barrier inserted into an amorphous-C/Ni bilayer stack is demonstrated to enable growth of uniform monolayer graphene at 600 °C with domain sizes exceeding 50 μm, and an average Raman D/G ratio of <0.07. A detailed growth rationale is established via in situ measurements, relevant to solid-state growth of a wide range of layered materials, as well as layer-by-layer control in these systems.

Assessment of the settlement vulnerability of masonry buildings

Excavation works in urban areas require a preliminary risk damage assessment. In historical cities, the prediction of building response to settlements is necessary to reduce the risk of damage of the architectural heritage. The current method used to predict the building damage due to ground deformations is the Limiting Tensile Strain Method (LTSM). In this approach the building is modelled as an elastic beam subjected to imposed Greenfield settlements and the induced tensile strains are compared with a limit value for the material. These assumptions can lead to a non realistic evaluation of the damage. In this paper, the possibility to apply a settlement risk assessment derived from the seismic vulnerability approach is considered. The parameters that influence the structural response to settlements can be defined through numerical analyses which take into account the nonlinear behaviour of masonry and the soil-structure interaction. The effects of factors like material quality, geometry of the structure, amount of openings, type of foundation or the actual state of preservation can be included in a global vulnerability index, which should indicate the building susceptibility to damage by differential settlements of a given magnitude. Vulnerability curves will represent the expected damage of each vulnerability class of building as a function of the settlement.