Robust stabilization of singular-impulsive-delayed systems with nonlinear perturbations

Many dynamic systems in physics, chemistry, biology, engineering, and information science have impulsive dynamical behaviors due to abrupt jumps at certain instants during the dynamical process, and these complex dynamic behaviors can be modeled by singular impulsive differential systems. This paper formulates and studies a model for singular impulsive delayed systems with uncertainty from nonlinear perturbations. Several fundamental issues such as global exponential robust stabilization of such systems are established. A simple approach to the design of a robust impulsive controller is then presented. A numerical example is given for illustration of the theoretical results. Meanwhile, some new results and refined properties associated with the M-matrices and time-delay dynamic systems are derived and discussed.published_or_final_versio

Novel critical point drying (CPD) based preparation and transmission electron microscopy (TEM) imaging of protein specific molecularly imprinted polymers (HydroMIPs)

We report the transmission electron microscopy (TEM) imaging of a hydrogel-based molecularly imprinted polymer (HydroMIP) specific to the template molecule bovine haemoglobin (BHb). A novel critical point drying based sample preparation technique was employed to prepare the molecularly imprinted polymer (MIP) samples in a manner that would facilitate the use of TEM to image the imprinted cavities, and provide an appropriate degree of both magnification and resolution to image polymer architecture in the <10 nm range. For the first time, polymer structure has been detailed that clearly displays molecularly imprinted cavities, ranging from 5-50 nm in size, that correlate (in terms of size) with the protein molecule employed as the imprinting template. The modified critical point drying sample preparation technique used may potentially play a key role in the imaging of all molecularly imprinted polymers, particularly those prepared in the aqueous phase

Current-induced magnetization dynamics in Co/Cu/Co nanopillars

Author name used in this publication: S. Q. Shi2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Micromagnetic simulations of current-induced magnetization switching in Co/Cu/Co nanopillars

Author name used in this publication: S. Q. Shi2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

On the design of experiments to study extreme field limits

We propose experiments on the collision of high intensity electromagnetic pulses with electron bunches and on the collision of multiple electromagnetic pulses for studying extreme field limits in the nonlinear interaction of electromagnetic waves. The effects of nonlinear QED will be revealed in these laser plasma experiments.Comment: 7 pages, 3 figures, 1 table; 15th Advanced Accelerator Concepts Workshop (AAC 2012), Austin, Texas, 10-15 June, 201

Facile Synthesis of High Quality Graphene Nanoribbons

Graphene nanoribbons have attracted attention for their novel electronic and spin transport properties1-6, and because nanoribbons less than 10 nm wide have a band gap that can be used to make field effect transistors. However, producing nanoribbons of very high quality, or in high volumes, remains a challenge. Here, we show that pristine few-layer nanoribbons can be produced by unzipping mildly gas-phase oxidized multiwalled carbon nanotube using mechanical sonication in an organic solvent. The nanoribbons exhibit very high quality, with smooth edges (as seen by high-resolution transmission electron microscopy), low ratios of disorder to graphitic Raman bands, and the highest electrical conductance and mobility reported to date (up to 5e2/h and 1500 cm2/Vs for ribbons 10-20 nm in width). Further, at low temperature, the nanoribbons exhibit phase coherent transport and Fabry-Perot interference, suggesting minimal defects and edge roughness. The yield of nanoribbons was ~2% of the starting raw nanotube soot material, which was significantly higher than previous methods capable of producing high quality narrow nanoribbons1. The relatively high yield synthesis of pristine graphene nanoribbons will make these materials easily accessible for a wide range of fundamental and practical applications.Comment: Nature Nanotechnology in pres

The wavelet-NARMAX representation : a hybrid model structure combining polynomial models with multiresolution wavelet decompositions

A new hybrid model structure combing polynomial models with multiresolution wavelet decompositions is introduced for nonlinear system identification. Polynomial models play an important role in approximation theory, and have been extensively used in linear and nonlinear system identification. Wavelet decompositions, in which the basis functions have the property of localization in both time and frequency, outperform many other approximation schemes and offer a flexible solution for approximating arbitrary functions. Although wavelet representations can approximate even severe nonlinearities in a given signal very well, the advantage of these representations can be lost when wavelets are used to capture linear or low-order nonlinear behaviour in a signal. In order to sufficiently utilise the global property of polynomials and the local property of wavelet representations simultaneously, in this study polynomial models and wavelet decompositions are combined together in a parallel structure to represent nonlinear input-output systems. As a special form of the NARMAX model, this hybrid model structure will be referred to as the WAvelet-NARMAX model, or simply WANARMAX. Generally, such a WANARMAX representation for an input-output system might involve a large number of basis functions and therefore a great number of model terms. Experience reveals that only a small number of these model terms are significant to the system output. A new fast orthogonal least squares algorithm, called the matching pursuit orthogonal least squares (MPOLS) algorithm, is also introduced in this study to determine which terms should be included in the final model

A unified wavelet-based modelling framework for non-linear system identification: the WANARX model structure

A new unified modelling framework based on the superposition of additive submodels, functional components, and wavelet decompositions is proposed for non-linear system identification. A non-linear model, which is often represented using a multivariate non-linear function, is initially decomposed into a number of functional components via the wellknown analysis of variance (ANOVA) expression, which can be viewed as a special form of the NARX (non-linear autoregressive with exogenous inputs) model for representing dynamic input–output systems. By expanding each functional component using wavelet decompositions including the regular lattice frame decomposition, wavelet series and multiresolution wavelet decompositions, the multivariate non-linear model can then be converted into a linear-in-theparameters problem, which can be solved using least-squares type methods. An efficient model structure determination approach based upon a forward orthogonal least squares (OLS) algorithm, which involves a stepwise orthogonalization of the regressors and a forward selection of the relevant model terms based on the error reduction ratio (ERR), is employed to solve the linear-in-the-parameters problem in the present study. The new modelling structure is referred to as a wavelet-based ANOVA decomposition of the NARX model or simply WANARX model, and can be applied to represent high-order and high dimensional non-linear systems