Robust tracking control design for uncertain robotic systems with persistent bounded disturbances

In this study, a robust nonlinear L_∞‐gain tracking control design for uncertain robotic systems is proposed under persistent bounded disturbances. The design objective is that the peak of the tracking error in time domain must be as small as possible under persistent bounded disturbances. Since the nonlinear L_∞ ‐gain optimal tracking control cannot be solved directly, the nonlinear L_∞ ‐gain optimal tracking problem is transformed into a nonlinear L_∞ ‐gain tracking problem by given a prescribed disturbance attenuation level for the L_∞ ‐gain tracking performance. To guarantee that the L_∞ ‐gain tracking performance can be achieved for the uncertain robotic systems, a sliding‐mode scheme is introduced to eliminate the effect of the parameter uncertainties. By virtue of the skew‐symmetric property of the robotic systems, sufficient conditions are developed for solving the robust L_∞ ‐gain tracking control problems in terms of an algebraic equation instead of a differential equation. The proposed method is simple and the algebraic equation can be solved analytically. Therefore, the proposed robust L_∞ ‐gain tracking control scheme is suitable for practical control design of uncertain robotic systems. Copyright © 2008 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Parameter determination of support vector machine and feature selection using simulated annealing approach

Support vector machine (SVM) is a novel pattern classification method that is valuable in many applications. Kernel parameter setting in the SVM training process, along with the feature selection, significantly affects classification accuracy. The objective of this study is to obtain the better parameter values while also finding a subset of features that does not degrade the SVM classification accuracy. This study develops a simulated annealing (SA) approach for parameter determination and feature selection in the SVM, termed SA-SVM.To measure the proposed SA-SVM approach, several datasets in UCI machine learning repository are adopted to calculate the classification accuracy rate. The proposed approach was compared with grid search which is a conventional method of performing parameter setting, and various other methods. Experimental results indicate that the classification accuracy rates of the proposed approach exceed those of grid search and other approaches. The SA-SVM is thus useful for parameter determination and feature selection in the SVM.     

Synthesis of bio-functionalized copolymer particles bearing carboxyl groups via a microfluidic device

Monodisperse copolymer particles carrying surface carboxyl groups in the range of 50–200 μm were prepared by in situ UV polymerization of ethyleneglycol dimethacrylate (EGDMA) with acrylic acid (AA) via a microfluidic flow-focusing device (MFFD). The design of the coaxial orifices in the MFFD enables the confinement of the comonomer liquid thread to the central axis of the microchannel, which can avoid the wetting problem of comonomer liquid with the microchannel and can successfully produce monodisperse copolymer microspheres with coefficient of variance below 5%. The effects of concentration of EGDMA and AA on droplet diameters and the distribution of carboxyl group on particle surfaces were examined. It has been found that, increasing the concentration of AA would decrease particle sizes, but increase the distribution of carboxyl group on particle surfaces. Bioconjugation of the carboxylated copolymer particles with the anti-rabbit IgG–Cy3 conjugates was successfully demonstrated. By increasing the concentration of AA accompanied with decreasing the particle sizes, high efficiency of bioconjugation on carboxylated copolymer particles was achieved. The rapid continuous synthesis of carboxylated copolymer particles via a microfluidic device provides a reliable control of particle sizes and composition for massive production in biotechnological applications.     

Exploiting Network Locality for CC-NUMA Multiprocessors

The Journal of Supercomputing - Rapid advances in interconnection networks in multiprocessors are closing the gap between computation and communication. Given this trend, how can we utilize fast...     

Large-scale protein identification of human urine proteome by multi-dimensional LC and MS/MS

Urine is a human specimen that is easily obtained non-invasively for clinical diagnosis. We attempted to enhance the resolution of current human urine proteomes and construct a comprehensive reference database for advanced studies, such as the discovery of biomarkers for renal diseases. Multi-dimensional LC-MS/MS was coupled with de novo sequencing and database matching. The proposed approach improved the identification of not only the proteins, but also the post-translational sites of urinary proteins. We identified 165, 200 and 259 unique gene products in the urine proteomes from males, females and pregnant women, respectively. When all of the results were combined and the redundancies removed, a total of 1095 distinct peptides were identified. Of these, 1016 peptides were associated with 334 unique gene products. In this study, over 100 gene products, including some disease-related proteins, were detected in urine for the first time by proteomic approaches. Various proteins with novel post-translational hydroxylation were identified using the MASCOT program and de novo sequencing. All proteins with peptide information were summarized into a comprehensive urine protein database. We believe that this comprehensive urine proteome database will assist in the identification of urinary proteins/polypeptides whose spectra are difficult to interpret in the discovery of urinary biomarkers.     

Shape optimization using adaptive high-order finite elements

In recent years, the state of the art in shape optimization has advanced due to new approaches proposed by various researchers. A fundamental difficulty in shape optimization is that the original finite element mesh may become invalid during large shape changes. Automatic remeshing and velocity field approaches are most commonly used for conventionalh-type finite element analysis to address this problem.In this paper, we describe a different approach to shape optimization based on the use of high-orderp-type finite elements tightly coupled to a parameterized computational geometry module. The advantages of this approach are as follows.Accurate results can be obtained with much fewer finite elements, so large shape changes are possible without remeshing.Automatic adaptive analysis may be performed so that accurate results are achieved at each step of the optimization process.Since the elements derive their geometric mapping from the underlying geometry, the fundamental equivalent of velocity field element shape updating may be readily achieved.Results are presented for sizing and shape optimization with this approach and contrasted with previous results from the literature.     

Calculation of the wetted area of a planing hull with a chine

Summary The extent to which a low-aspect-ratio flat ship with a chined hull is wetted when planing at infinite Froude number is investigated. A numerical method of solution for the wetted area, which is applicable to more general planing problems, is presented. The results obtained by this method are compared with those found by solving the inverse problem of determining the hull shape which produces a given waterplane shape and are shown to be in excellent agreement. Results are also presented which indicate that a vertical chine may be used to fix the shape of the wetted region.     

Craze intersections in biaxially-stressed polystyrene

Crazes are produced on two orthogonal planes in both thin film and macroscopic samples of polystyrene by sequentially applying two orthogonal tensile strains ₁ and ₂. Although many crazes produced by the second strain ₂ (secondary crazes) are stopped when they meet a primary craze, some intersections occur. The fraction of craze meetings resulting in intersection increases from 20% at ₁= ₂=3% to 55% at ₁= ₂=5%; intersections also occur preferentially in thin regions of primary crazes. The craze fibril structure in the intersection has a much lower fibril volume fraction, v _f, than either of the two crazes from which it formed. The fibril volume fraction in the intersection is approximately given by the product of the fibril volume fractions of the two crazes, in agreement with a prediction based on the surface drawing mechanism of craze thickening. At higher strain levels the v _fs of the intersections are lower, leading to higher fibril stresses and enhanced fibril fracture; an increasing fraction of intersections breaks down to form large voids at these higher strain levels. Fractography of macroscopic samples containing intersecting crazes demonstrates that voids formed at the intersections can act as nuclei for cracks causing premature fracture of the material.     

Noise of He-Cd laser and its suppression

Linear relations have been observed between the reciprocal of the noise ratio and the reciprocal of the output power of the He-Cd laser as well as between the noise ratio and the net gain within the laser cavity. By a feedback method with an acoustooptic modulator in the laser cavity at the Brewster angle for low optical loss, a stable laser with high power output and low noise has been obtained. The noise ratio and the output power are 0.8% and 33 mW, respectively, at 4416 A