CLF based designs with robustness to dynamic input uncertainties

The problem of robust stabilization of nonlinear systems in the presence of input uncertainties is of great importance in practical implementation. Stabilizing control laws may not be robust to this type of uncertainty, especially if cancellation of nonlinearities is used in the design. By exploiting a connection between robustness and optimality, "domination redesign" of the control Lyapunov function (CLF) based Sontag's formula has been shown to possess robustness to static and dynamic input uncertainties. In this paper we provide a sufficient condition for the domination redesign to apply. This condition relies on properties of local homogeneous approximations of the system and of the CLF. We show that an inverse optimal control law may not exist when these conditions are violated and illustrate how these conditions may guide the choice of a CLF which is suitable for domination redesign. © 1999 Elsevier Science B.V. All rights reserved.

Hybrid deterministic-statistical modelling of built-up structures

When used correctly, Statistical Energy Analysis (SEA) can provide good predictions of high frequency vibration levels in built-up structures. Unfortunately, the assumptions that underlie SEA break down as the frequency of excitation is reduced, and the method does not yield accurate predictions at "medium" frequencies (and neither does the Finite Element Method, which is limited to low frequencies). A basic problem is that parts of the system have a short wavelength of deformation and meet the requirements of SEA, while other parts of the system do not - this is often referred to as the "mid-frequency" problem, and there is a broad class of mid-frequency vibration problems that are of great concern to industry. In this paper, a coupled deterministic-statistical approach referred to as the Hybrid Method (Shorter & Langley, 2004) is briefly described, and some results that demonstrate how the method overcomes the aforementioned difficulties are presented.

Efficient statistical electromagnetic analysis in reverberant environments

This paper presents a statistical approach to the electromagnetic analysis of a system that lies within a reverberant cavity that has random or uncertain properties. The need to solve Maxwell's equations within the cavity is avoided by employing a relation known as the diffuse field reciprocity principle, which leads directly to the ensemble mean squared response of the system; all that is required is the impedance matrix of the system associated with radiation into infinite space. The general theoretical approach is presented, and the analysis is then applied to a five-cable bundle in a reverberation room © 2013 EMC Europe Foundation.

Systematic misregistration and the statistical analysis of surface data.

Spatial normalisation is a key element of statistical parametric mapping and related techniques for analysing cohort statistics on voxel arrays and surfaces. The normalisation process involves aligning each individual specimen to a template using some sort of registration algorithm. Any misregistration will result in data being mapped onto the template at the wrong location. At best, this will introduce spatial imprecision into the subsequent statistical analysis. At worst, when the misregistration varies systematically with a covariate of interest, it may lead to false statistical inference. Since misregistration generally depends on the specimen's shape, we investigate here the effect of allowing for shape as a confound in the statistical analysis, with shape represented by the dominant modes of variation observed in the cohort. In a series of experiments on synthetic surface data, we demonstrate how allowing for shape can reveal true effects that were previously masked by systematic misregistration, and also guard against misinterpreting systematic misregistration as a true effect. We introduce some heuristics for disentangling misregistration effects from true effects, and demonstrate the approach's practical utility in a case study of the cortical bone distribution in 268 human femurs.

Efficient parametric uncertainty analysis within the hybrid Finite Element/Statistical Energy Analysis method

This paper is concerned with the development of efficient algorithms for propagating parametric uncertainty within the context of the hybrid Finite Element/Statistical Energy Analysis (FE/SEA) approach to the analysis of complex vibro-acoustic systems. This approach models the system as a combination of SEA subsystems and FE components; it is assumed that the FE components have fully deterministic properties, while the SEA subsystems have a high degree of randomness. The method has been recently generalised by allowing the FE components to possess parametric uncertainty, leading to two ensembles of uncertainty: a non-parametric one (SEA subsystems) and a parametric one (FE components). The SEA subsystems ensemble is dealt with analytically, while the effect of the additional FE components ensemble can be dealt with by Monte Carlo Simulations. However, this approach can be computationally intensive when applied to complex engineering systems having many uncertain parameters. Two different strategies are proposed: (i) the combination of the hybrid FE/SEA method with the First Order Reliability Method which allows the probability of the non-parametric ensemble average of a response variable exceeding a barrier to be calculated and (ii) the combination of the hybrid FE/SEA method with Laplace's method which allows the evaluation of the probability of a response variable exceeding a limit value. The proposed approaches are illustrated using two built-up plate systems with uncertain properties and the results are validated against direct integration, Monte Carlo simulations of the FE and of the hybrid FE/SEA models. © 2013 Elsevier Ltd.

Statistical study of a novel launch scheme for highperformance electronic-equalized multimode-fiber links

A novel launch scheme is proposed for multimode-fiber (MMF) links. Enhanced performance in 10 Gb/s MMF links using electronic equalization is demonstrated by statistical analysis of installed-base fiber and an experimental investigation. © 2007 Optical Society of America.

Comprehensive statistical investigation of SCM-based transmission over 300 m of FDDI-grade multimode fiber

Rigorous statistical analysis is applied for the first time to identify optimal launch conditions and carrier frequencies for SCM transmission over worst-case MMF. The feasibility of multichannel schemes for 10 Gb/s over 300 m is demonstrated. © 2005 Optical Society of America.

Comprehensive statistical investigation of SCM-based transmission over 300 m of FDDI-grade multimode fiber

Rigorous statistical analysis is applied for the first time to identify optimal launch conditions and carrier frequencies for SCM transmission over worst-case MMF. The feasibility of multichannel schemes for 10 Gb/s over 300 m is demonstrated. © 2005 Optical Society of America.

Statistical investigation on morphology development of gallium nitride in initial growth stage

Morphology of Gallium Nitride (GaN) in initial growth stage was observed with atomic force microscopy (AFM) and scanning electron microscopy (SEM), It was found that the epilayer developed from islands to coalesced film. Statistics based on AFM observation was carried out to investigate the morphology characteristics. It was found that the evolution of height distribution could be used to describe morphology development. Statistics also clearly revealed variation of top-face growth rate among islands. Indium-doping effect on morphology development was also statistically studied. The roughening and smoothing behavior in morphology development was explained. (C) 2002 Elsevier Science B.V. All rights reserved.

A Structured Prediction Approach for Statistical Machine Translation

We propose a new formally syntax-based method for statistical machine translation. Transductions between parsing trees are transformed into a problem of sequence tagging, which is then tackled by a search- based structured prediction method. This allows us to automatically acquire transla- tion knowledge from a parallel corpus without the need of complex linguistic parsing. This method can achieve compa- rable results with phrase-based method (like Pharaoh), however, only about ten percent number of translation table is used. Experiments show that the structured pre- diction approach for SMT is promising for its strong ability at combining words.

Investigation of Interfacial Tensions for Carbon Dioxide Aqueous Solutions by Perturbed-Chain Statistical Associating Fluid Theory Combined with Density-Gradient Theory

The perturbed-chain statistical associating fluid theory and density-gradient theory are used to construct an equation of state (EOS) applicable for the phase behaviors of carbon dioxide aqueous solutions. With the molecular parameters and influence parameters respectively regressed from bulk properties and surface tensions of pure fluids as input, both the bulk and interfacial properties of carbon dioxide aqueous solutions are satisfactorily correlated by adjusting the binary interaction parameter (k(ij)). Our results show that the constructed EOS is able to describe the interfacial properties of carbon dioxide aqueous solutions in a wide temperature range, and illustrate the influences of temperature, pressure, and densities in each phase on the interfacial properties.