Exact,almost and optimal input decoupled (delayed) observers

The core of this paper deals with the construction of input-decoupled observers which seek asymptotic estimation of a desired output variable (a linear combination of state and input) of a time-invariant either continuous- or discrete-time system driven by unknown inputs and disturbances. Exact, almost, optimal (suboptimal) and constrained optimal estimation or filtering problems are formulated and studied. All the problems defined and studied here are inherently interconnected, and have a strong common thread of estimation and filtering in the face of the unknown input and external disturbance signals. They are interconnected from a variety of angles, e.g. they are motivated by one another, methods of obtaining the solvability conditions and their methods of solution rely on one another, etc. Thus, a hierarchy of problems and their solutions is built on top of one another. Some of the problems studied here are known in the literature but not in as general a form as is given here, while a majority of the problems studied here are new. A classical variation of all the above problems is also studied here by introducing an l-step delay in estimating the desired output from the measured output. The underlying philosophy throughout this work has been to study most if not all of the facets of estimation and filtering in one stretch under a single folder. Our study of all the above problems has been guided by three important perspectives: (1) obtaining the solvability conditions, both necessary and sufficient; (2) obtaining optimal performance whenever it applies; and (3) developing sound methodologies to design and construct appropriate observers or filters.     

Verhalten austenitischer Manganstähle in Meerwasser

Auslagerungsversuche mit verschiedenen geschweißten und verspannten Proben aus den chromhaltigen austenitischen Manganstählen X 40 MnCrN 19 und X 12 MnCr 18 12 sowie dem chromfreien Stahl X 50 Mn 20 in Meerwasser der Nord- und Ostsee. Makroskopische und mikroskopische Beurteilung der Proben nach sechs Wochen, einem halben Jahr, einem Jahr und zwei Jahren hinsichtlich Beständigkeit gegen unterschiedliche Korrosionserscheinungen, besonders hinsichtlich transkristalliner Spannungsrißkorrosion.     

Is the analysis of molecular electronic structure of corrosion inhibitors sufficient to predict the trend of their inhibition performance

The often used approach in the corrosion inhibition studies employing quantum chemical calculations that relies on the correlation between molecular electronic structure parameters and inhibition effectiveness is critically examined. It is shown that the inhibition performance of three selected triazole-based corrosion inhibitors for copper - 3-amino-1,2,4-triazole (ATA), benzotriazole (BTAH), and 1-hydroxybenzotriazole (BTAOH) - cannot be explained on this basis in a sound manner. As the effectiveness of inhibitors is due to several phenomena, the outcome depends on the interplay between them and although molecular electronic parameters may provide many necessary elements, the involved effects can be estimated only approximately which may not always suffice. This supports the proposition that in general molecular electronic properties cannot be directly related to inhibition effectiveness - the actual relation is more involved - thus emphasizing the importance of a rigorous modeling of the inhibitor-surface interaction in the corrosion inhibition studies.     

An Adaptive Estimator of the Autocorrelation Coefficient in Regression Models with Autoregressive Errors

In this paper an adaptive estimator of the autocorrelation coefficient is constructed in regression models whose error variables follow a stationary autoregressive process of order 1. Examples of nonparametric, additive and semiparametric regression models are discussed.     

Robust method to provide exponential convergence of model parameters solving linear time-invariant plant identification problem

The scope of this research is a problem of parameters identification of a linear time-invariant plant, which (1) input signal is not frequency-rich, (2) is subjected to initial conditions and external disturbances. The memory regressor extension (MRE) scheme, in which a specially derived differential equation is used as a filter, is applied to solve the above-stated problem. Such a filter allows us to obtain a bounded regressor value, for which a condition of the initial excitation (IE) is met. Using the MRE scheme, the recursive least-squares method with the forgetting factor is used to derive an adaptation law. The following properties have been proved for the proposed approach. If the IE condition is met, then: (1) the parameter error of identification is bounded and converges to zero exponentially (if there are no external disturbances) or to a set (in the case of them) with an adjustable rate, (2) the parameters adaptation rate is a finite value. The above-mentioned properties are mathematically proved and demonstrated via simulation experiments.     

Impact of platinum contamination on ferroelectric memories

Abstract

The impact of platinum contamination on the breakdown properties of gate oxide is reported. Wafers were intentionally contaminated with 1×10¹³ to 4×10¹⁴ at/cm² Pt after a 7.5 nm gate oxide growth, 300 nm poly-silicon deposition and subsequent phosphorus doping. Breakdown characteristics were evaluated using a voltage ramp method. The current-voltage curves of MOS capacitors show very few low field breakdown events, and the main field breakdown occurs at 12 MV/cm. If compared to clean wafers, platinum does not increase the defect density seriously. It is found from the E-Ramp results that platinum contamination up to 4×10¹⁴ at/cm² does not have a pronounced effect on the gate oxide integrity if the contamination occurs after front-end-of-line processing of device fabrication.     

Unknown piecewise constant parameters identification with exponential rate of convergence

The scope of this research is the identification of unknown piecewise constant parameters of linear regression equation under the finite excitation condition. Compared to the known methods, to make the computational burden lower, only one model to identify all switching states of the regression is used in the developed procedure with the following two-fold contribution. First of all, we propose a new truly online estimation algorithm based on a well-known DREM approach to detect switching time and preserve time alertness with adjustable detection delay. Second, despite the fact that a switching signal function is unknown, the adaptive law is derived that provides global exponential convergence of the regression parameters estimates to their true values in case the regressor is finitely exciting somewhere inside the time interval between two consecutive parameters switches. The robustness of the proposed identification procedure to the influence of external disturbances is analytically proved. Its effectiveness is demonstrated via numerical experiments, in which both abstract regressions and a second-order plant model are used.     

Interface reactions between rutile coatings and molten aluminium or AlSi7Mg0.6 alloy

Rutile coatings deposited on corundum substrates are considered as promising functional elements improving the efficiency of the filtration of oxide inclusions out of aluminium melts. This contribution describes the reactions between rutile and two kinds of the aluminium melts and discusses the consequences of these reactions for the filtration process. It was found that the contact of rutile coatings with molten aluminium leads to the formation of a corundum layer at the solid/liquid interface. The exposure of the rutile coatings to molten AlSi7Mg0.6 alloy produces an interface layer of MgTiO₃. The interface layers possess defined orientation relationship to rutile which is characteristic for locally heteroepitaxial growth. The density functional theory calculations revealed that the TiO₂/α-Al₂O₃ and TiO₂/MgTiO₃ interfaces with the orientation relationships observed experimentally have low interface energies. The mechanisms of the interface layer formation and the impact of these layers on the degradation of the rutile coatings are discussed.     

Reduced graphene oxide-ZnO hybrid composites as photocatalysts: The role of nature of the molecular target in catalytic performance

Spurred by controversial literature findings, we enwrapped reduced graphene oxide (rGO) in ZnO hierarchical microstructures (rGO loadings spanning from 0.01 to 2 wt%) using an in situ synthetic procedure. The obtained hybrid composites were carefully characterized, aiming at shining light on the possible role of rGO on the claimed increased performance as photocatalysts. Several characterization tools were exploited to unveil the effect exerted by rGO, including steady state and time resolved photoluminescence, electron microscopies and electrochemical techniques, in order to evaluate the physical, optical and electrical features involved in determining the catalytic degradation of rhodamine B and phenol in water.Several properties of native ZnO structures were found changed upon the rGO enwrapping (including optical absorbance, concentration of native defects in the ZnO matrix and double-layer capacitance), which are all involved in determining the photocatalytic performance of the hybrid composites. The findings discussed in the present work highlight the high complexity of the field of application of graphene-derivatives as supporters of semiconducting metal oxides functionality, which has to be analyzed through a multi-parametric approach.