Stability of controllers with on-line computations

The dynamical systems theory developed by Zufiria [1], Zufiria and Guttalu [2, 3], and Guttalu and Zufiria [4] is applied to the stability analysis of control systems in which the feedback control law requires in real time the solution of a set of nonlinear algebraic equations. Since a small sampling period is assumed, the stability and performance of the controlled process can be studied with a continuous-time formulation. A singularly perturbed system is used to model both the dynamics of the system being controlled and a numerical iterative algorithm required to compute the control law. An updating control procedure has been proposed based on the iterative nature of the control algorithm. The results obtained by Zufiria [1] regarding the behavior of a dynamical system that models the numerical algorithms lead to a considerable simplification in the analysis. For the case of a control problem involving inverse kinematics, the numerical algorithm that solves for inverse kinematics can be considered as an observer (or an estimator) of the state-space variables. The study provides an estimate of the required speed of computations to preserve the stability of the controller.Recommended by E .P. Ryan     

Synthesis and characterization of functional gradient copolymers of glycidyl methacrylate and butyl acrylate

Epoxy-functional spontaneous gradient copolymers of glycidyl methacrylate (G) and n-butyl acrylate (B) were synthesized via atom transfer radical polymerization (ATRP). The copolymerization reactions were carried out in toluene solution at 70 °C, using methyl 2-bromopropionate (MBrP) as initiator and copper chloride with N,N,N′,N′′,N′′-pentamethyldiethylenetriamine (PMDETA) as the catalyst system. The kinetic behaviour of the statistical copolymerizations was studied in a wide composition interval with molar fractions of G ranging from 0.10 to 0.75. The synthesized copolymers were characterized by size exclusion chromatography (SEC) and nuclear magnetic resonance (NMR) spectroscopy. ¹H NMR was employed to determine the copolymer composition, demonstrating the gradient character of the copolymers along the main chain in the whole monomer conversion interval. Apart from this, the sequence distribution and stereoregularity were analyzed. These microstructural experimental data agreed well with those calculated from Mayo-Lewis terminal model (MLTM) and a Bernoullian statistic with an isotacticity parameter of σ_G = 0.28 and a coisotacticity parameter of σ = 0.30.     

A p‐version,first order shear deformation,finite element for geometrically non‐linear vibration of curved beams

A p‐version, hierarchical finite element for curved, moderately thick, elastic and isotropic beams is introduced. The convergence properties of the element are analysed and some results are compared with results published elsewhere or calculated using a commercial finite element package. It is verified that, with the proposed element, shear locking does not affect the computation of the natural frequencies and that low dimensional, accurate models are obtainable. Geometrically non‐linear vibrations due to finite deformations, which occur for harmonic excitations with frequencies close to the first three natural frequencies of vibration, are investigated using Newmark's method. The influence of the thickness, longitudinal inertia and curvature radius on the dynamic behaviour of curved beams are studied. Copyright © 2004 John Wiley & Sons, Ltd.     

Structural characterization of the cyanelle peptidoglycan of Cyanophora paradoxa by 252Cf plasma desorption mass spectrometry and fast atom bombardment/tandem mass spectrometry

A strategy for the structural characterization of the four major NaBH4-reduced peptidoglycan monomers derived from muramidase-digested peptidoglycan from the cyanelles of the flagellate Cyanophora paradoxa Korschikoff is described. Initial molecular weight determination of these glycopeptides was performed by positive and negative ion plasma desorption mass spectrometry. Due to the presence of two pairs of disaccharide tripeptide and disaccharide tetrapeptide monomers differing in mass by 112 units, respectively, an as yet unknown peptidoglycan modification either at the carbohydrate or at the peptide moiety was assumed. beta-Elimination of the disaccharide unit from the unreduced peptidoglycan monomers yielded the corresponding (modified) N1-lactyltripeptides and -tetrapeptides, respectively. These peptides, N-terminally blocked with lactic acid, unambiguously showed the modification to be located on the peptide moiety. By positive ion fast atom bombardment/hybrid tandem mass spectrometry of the reduced peptidoglycan monomers as well as of the corresponding deglycosylated monomers (= N1-lactylpeptides) the modification was determined to be linked to the glutamic acid moiety. Based on combined data from plasma desorption mass spectrometry, tandem mass spectrometry, accurate mass measurement and amino acid analysis of the acid hydrolysate after derivatization with o-phthaldialdehyde by high-performance liquid chromatography we could establish the structure of the modification as N-acetylputrescine. Finally, the confirmation of the linkage of the glutamic acid to diaminopimelic acid via the gamma-COOH was based on the presence of a-type peptide backbone fragment ions in the positive ion plasma desorption mass spectra of the modified N1-lactylpeptides.     

Design and implementation of a 5×5 trits multiplier in aquasi-adiabatic ternary CMOS logic

Adiabatic switching is a technique to design low-power digital IC's. Fully adiabatic logics have expensive silicon area requirements. To solve this drawback, a quasi-adiabatic ternary logic is proposed. Its basis is presented, and to validate its performance, a 5×5 ternary digit multiplier is designed and implemented in a 0.7-μm CMOS technology. Results show a satisfactory power saving with respect to conventional and other quasi-adiabatic binary multipliers, and a decrease of the area needed with respect to a fully adiabatic binary one     

Learning Recursive Bayesian Multinets for Data Clustering by Means of Constructive Induction

This paper introduces and evaluates a new class of knowledge model, the recursive Bayesian multinet (RBMN), which encodes the joint probability distribution of a given database. RBMNs extend Bayesian networks (BNs) as well as partitional clustering systems. Briefly, a RBMN is a decision tree with component BNs at the leaves. A RBMN is learnt using a greedy, heuristic approach akin to that used by many supervised decision tree learners, but where BNs are learnt at leaves using constructive induction. A key idea is to treat expected data as real data. This allows us to complete the database and to take advantage of a closed form for the marginal likelihood of the expected complete data that factorizes into separate marginal likelihoods for each family (a node and its parents). Our approach is evaluated on synthetic and real-world databases.     

Theoretical elastoplastic buckling of stringer stiffened cylindrical shells

A linear analysis method is offered to predict the theoretical elastoplastic buckling of stringer stiffened cylindrical shells subjected to longitudinal loading. Welding residual stresses are taken into account in the calculation, but effects of geometrical imperfections and pre-buckling displacements are ignored.The examples analysed show a good correlation between the analytical results and those obtained experimentally with stocky models of moderate geometrical imperfections.