H-infinity control design for time-delay linear systems: a rational transfer function based approach

The aim of this paper is to present new results on H-infinity control synthesis for time-delay linear systems. We extend the use of a finite order LTI system, called comparison system to H-infinity analysis and design. Differently from what can be viewed as a common feature of other control design methods available in the literature to date, the one presented here treats time-delay systems control design with classical numeric routines based on Riccati equations arisen from H-infinity theory. The proposed algorithm is simple, efficient and easy to implement. Some examples illustrating state and output feedback design are solved and discussed in order to put in evidence the most relevant characteristic of the theoretical results. Moreover, a practical application involving a 3-DOF networked control system is presented.

Robotic Sensing and Manipulation of Deformable Linear Objects with Learning-based methods

Nowadays robotic applications are widespread and most of the manipulation tasks are efficiently solved. However, Deformable-Objects (DOs) still represent a huge limitation for robots. The main difficulty in DOs manipulation is dealing with the shape and dynamics uncertainties, which prevents the use of model-based approaches (since they are excessively computationally complex) and makes sensory data difficult to interpret. This thesis reports the research activities aimed to address some applications in robotic manipulation and sensing of Deformable-Linear-Objects (DLOs), with particular focus to electric wires. In all the works, a significant effort was made in the study of an effective strategy for analyzing sensory signals with various machine learning algorithms. In the former part of the document, the main focus concerns the wire terminals, i.e. detection, grasping, and insertion. First, a pipeline that integrates vision and tactile sensing is developed, then further improvements are proposed for each module. A novel procedure is proposed to gather and label massive amounts of training images for object detection with minimal human intervention. Together with this strategy, we extend a generic object detector based on Convolutional-Neural-Networks for orientation prediction. The insertion task is also extended by developing a closed-loop control capable to guide the insertion of a longer and curved segment of wire through a hole, where the contact forces are estimated by means of a Recurrent-Neural-Network. In the latter part of the thesis, the interest shifts to the DLO shape. Robotic reshaping of a DLO is addressed by means of a sequence of pick-and-place primitives, while a decision making process driven by visual data learns the optimal grasping locations exploiting Deep Q-learning and finds the best releasing point. The success of the solution leverages on a reliable interpretation of the DLO shape. For this reason, further developments are made on the visual segmentation.

On the effect of confounding in linear regression models: an approach based on the theory of quadratic forms

The main topic of this thesis is confounding in linear regression models. It arises when a relationship between an observed process, the covariate, and an outcome process, the response, is influenced by an unmeasured process, the confounder, associated with both. Consequently, the estimators for the regression coefficients of the measured covariates might be severely biased, less efficient and characterized by misleading interpretations. Confounding is an issue when the primary target of the work is the estimation of the regression parameters. The central point of the dissertation is the evaluation of the sampling properties of parameter estimators. This work aims to extend the spatial confounding framework to general structured settings and to understand the behaviour of confounding as a function of the data generating process structure parameters in several scenarios focusing on the joint covariate-confounder structure. In line with the spatial statistics literature, our purpose is to quantify the sampling properties of the regression coefficient estimators and, in turn, to identify the most prominent quantities depending on the generative mechanism impacting confounding. Once the sampling properties of the estimator conditionally on the covariate process are derived as ratios of dependent quadratic forms in Gaussian random variables, we provide an analytic expression of the marginal sampling properties of the estimator using Carlson’s R function. Additionally, we propose a representative quantity for the magnitude of confounding as a proxy of the bias, its first-order Laplace approximation. To conclude, we work under several frameworks considering spatial and temporal data with specific assumptions regarding the covariance and cross-covariance functions used to generate the processes involved. This study allows us to claim that the variability of the confounder-covariate interaction and of the covariate plays the most relevant role in determining the principal marker of the magnitude of confounding.

Seemingly unrelated linear regression for contaminated data based on Gaussian mixtures

In this thesis, new classes of models for multivariate linear regression defined by finite mixtures of seemingly unrelated contaminated normal regression models and seemingly unrelated contaminated normal cluster-weighted models are illustrated. The main difference between such families is that the covariates are treated as fixed in the former class of models and as random in the latter. Thus, in cluster-weighted models the assignment of the data points to the unknown groups of observations depends also by the covariates. These classes provide an extension to mixture-based regression analysis for modelling multivariate and correlated responses in the presence of mild outliers that allows to specify a different vector of regressors for the prediction of each response. Expectation-conditional maximisation algorithms for the calculation of the maximum likelihood estimate of the model parameters have been derived. As the number of free parameters incresases quadratically with the number of responses and the covariates, analyses based on the proposed models can become unfeasible in practical applications. These problems have been overcome by introducing constraints on the elements of the covariance matrices according to an approach based on the eigen-decomposition of the covariance matrices. The performances of the new models have been studied by simulations and using real datasets in comparison with other models. In order to gain additional flexibility, mixtures of seemingly unrelated contaminated normal regressions models have also been specified so as to allow mixing proportions to be expressed as functions of concomitant covariates. An illustration of the new models with concomitant variables and a study on housing tension in the municipalities of the Emilia-Romagna region based on different types of multivariate linear regression models have been performed.

Ihwg-μnir: A Miniaturised Near-infrared Gas Sensor Based On Substrate-integrated Hollow Waveguides Coupled To A Micro-nir-spectrophotometer.

A miniaturised gas analyser is described and evaluated based on the use of a substrate-integrated hollow waveguide (iHWG) coupled to a microsized near-infrared spectrophotometer comprising a linear variable filter and an array of InGaAs detectors. This gas sensing system was applied to analyse surrogate samples of natural fuel gas containing methane, ethane, propane and butane, quantified by using multivariate regression models based on partial least square (PLS) algorithms and Savitzky-Golay 1(st) derivative data preprocessing. The external validation of the obtained models reveals root mean square errors of prediction of 0.37, 0.36, 0.67 and 0.37% (v/v), for methane, ethane, propane and butane, respectively. The developed sensing system provides particularly rapid response times upon composition changes of the gaseous sample (approximately 2 s) due the minute volume of the iHWG-based measurement cell. The sensing system developed in this study is fully portable with a hand-held sized analyser footprint, and thus ideally suited for field analysis. Last but not least, the obtained results corroborate the potential of NIR-iHWG analysers for monitoring the quality of natural gas and petrochemical gaseous products.

Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.

Correlation between metal-ceramic bond strength and coefficient of linear thermal expansion difference

The purpose of this study was to evaluate the metal-ceramic bond strength (MCBS) of 6 metal-ceramic pairs (2 Ni-Cr alloys and 1 Pd-Ag alloy with 2 dental ceramics) and correlate the MCBS values with the differences between the coefficients of linear thermal expansion (CTEs) of the metals and ceramics. Verabond (VB) Ni-Cr-Be alloy, Verabond II (VB2), Ni-Cr alloy, Pors-on 4 (P), Pd-Ag alloy, and IPS (I) and Duceram (D) ceramics were used for the MCBS test and dilatometric test. Forty-eight ceramic rings were built around metallic rods (3.0 mm in diameter and 70.0 mm in length) made from the evaluated alloys. The rods were subsequently embedded in gypsum cast in order to perform a tensile load test, which enabled calculating the CMBS. Five specimens (2.0 mm in diameter and 12.0 mm in length) of each material were made for the dilatometric test. The chromel-alumel thermocouple required for the test was welded into the metal test specimens and inserted into the ceramics. ANOVA and Tukey's test revealed significant differences (p=0.01) for the MCBS test results (MPa), with PI showing higher MCBS (67.72) than the other pairs, which did not present any significant differences. The CTE (10-6 oC-1) differences were: VBI (0.54), VBD (1.33), VB2I (-0.14), VB2D (0.63), PI (1.84) and PD (2.62). Pearson's correlation test (r=0.17) was performed to evaluate of correlation between MCBS and CTE differences. Within the limitations of this study and based on the obtained results, there was no correlation between MCBS and CTE differences for the evaluated metal-ceramic pairs.

Phase transitions in biodegradable films based on blends of gelatin and poly (vinyl alcohol)

The aim of this work was to study the effect of the hydrolysis degree (HD) and the concentration (C PVA) of two types of poly (vinyl alcohol) (PVA) and the effect of the type and the concentration of plasticizers on the phase properties of biodegradable films based on blends of gelatin and PVA, using a response-surface methodology. The films were made by casting and the studied properties were their glass (Tg) and melting (Tm) transition temperatures, which were determined by diferential scanning calorimetry (DSC). For the data obtained on the first scan, the fitting of the linear model was statistically significant and predictive only for the second melting temperature. In this case, the most important effect on the second Tm of the first scan was due to the HD of the PVA. In relation to the second scan, the linear model could be fit to Tg data with only two statistically significant parameters. Both the PVA and plasticizer concentrations had an important effect on Tg. Concerning the second Tm of the second scan, the linear model was fit to data with two statistically significant parameters, namely the HD and the plasticizer concentration. But, the most important effect was provoked by the HD of the PVA.

A biosensor based on immobilization of lactate oxidase in a PB-CTAB film for FIA determination of lactate in beer samples

An amperometric lactate biosensor with lactate oxidase immobilized into a Prussian Blue (PB) modified electrode was fabricated. The advantage of using cetyltrimethylammonium bromide (CTAB) in the electrodeposition step of PB films onto glassy carbon surfaces was confirmed taking into account both the stability and sensitivity of the measurements. The biosensor was used in the development of a FIA amperometric method for the determination of lactate. Under optimal operating conditions (pH = 6.9, E = -0.1 V), the linear response of the method was extended up to 0.28 µmol L-1 lactate with a limit of detection of 0.84 mmol L-1. The repeatability of the method for injections of a 0.28 mmol L-1 lactate solution was 2.2 % (n = 18). The usefulness of the method was demonstrated by determining lactate in beer samples and the results were in good agreement with those obtained by using a reference spectrophotometric enzyme method.

Phylogenetic relationships in Solanaceae and related species based on cpDNA sequence from plastid trnE-trnT region

Intergenic spacers of chloroplast DNA (cpDNA) are very useful in phylogenetic and population genetic studies of plant species, to study their potential integration in phylogenetic analysis. The non-coding trnE-trnT intergenic spacer of cpDNA was analyzed to assess the nucleotide sequence polymorphism of 16 Solanaceae species and to estimate its ability to contribute to the resolution of phylogenetic studies of this group. Multiple alignments of DNA sequences of trnE-trnT intergenic spacer made the identification of nucleotide variability in this region possible and the phylogeny was estimated by maximum parsimony and rooted with Convolvulaceae Ipomoea batalas, the most closely related family. Besides, this intergenic spacer was tested for the phylogenetic ability to differentiate taxonomic levels. For this purpose, species from four other families were analyzed and compared with Solanaceae species. Results confirmed polymorphism in the trnE-trnT region at different taxonomic levels.

A flow injection procedure based on solenoid micro-pumps for spectrophotometric determination of free glycerol in biodiesel

A flow system designed with solenoid micro-pumps is proposed for fast and greener spectrophotometric determination of free glycerol in biodiesel. Glycerol was extracted from samples without using organic solvents. The determination involves glycerol oxidation by periodate, yielding formaldehyde followed by formation of the colored (3,5-diacetil-1,4-dihidrolutidine) product upon reaction with acetylacetone. The coefficient of variation, sampling rate and detection limit were estimated as 1.5% (20.0 mg L(-1) glycerol, n =10), 34 h(-1), and 1.0 mg L(-1) (99.7% confidence level), respectively. A linear response was observed from 5 to 50 mg L(-1), with reagent consumption estimated as 345 mu g of KIO(4) and 15 mg of acetylacetone per determination. The procedure was successfully applied to the analysis of biodiesel samples and the results agreed with the batch reference method at the 95% confidence level. (C) 2010 Elsevier B.V. All rights reserved.

A greener and highly sensitive flow-based procedure for carbaryl determination exploiting long pathlength spectrophotometry and photochemical waste degradation

An environmentally friendly analytical procedure with high sensitivity for determination of carbaryl pesticide in natural waters was developed. The flow system was designed with solenoid micro-pumps in order to improve mixing conditions and minimize reagent consumption as well as waste generation. A long pathlength (100 cm) flow cell based on a liquid core waveguide (LCW) was employed to increase the sensitivity in detection of the indophenol formed from the reaction between carbaryl and p-aminophenol (PAP). A clean-up step based on cloud-point extraction was explored to remove the interfering organic matter, avoiding the use of toxic organic solvents. A linear response was observed within the range 5-200 mu g L(-1) and the detection limit, coefficient of variation and sampling rate were estimated as 1.7 mu g L(-1) (99.7% confidence level), 0.7% (n=20) and 55 determinations per hour, respectively. The reagents consumption was 1.9 mu g of PAP and 5.7 mu g of potassium metaperiodate, with volume of 2.6 mL of effluent per determination. The proposed procedure was selective for the determination of carbaryl, without interference from other carbamate pesticides. Recoveries within 84% and 104% were estimated for carbaryl spiked to water samples and the results obtained were also in agreement with those found by a batch spectrophotometric procedure at the 95% confidence level. The waste of the analytical procedure was treated with potassium persulphate and ultraviolet irradiation, yielding a colorless residue and a decrease of 94% of total organic carbon. In addition, the residue after treatment was not toxic for Vibrio fischeri bacteria. (c) 2010 Elsevier B.V. All rights reserved.

A flow-based procedure with solenoid micro-pumps for the spectrophotometric determination of uric acid in urine

The determination of uric acid in urine shows clinical importance, once it can be related to human organism dysfunctions, such as gout. An analytical procedure employing a multicommuted flow system was developed for the determination of uric acid in urine samples. Cu(II) ions are reduced by uric acid to Cu(I) that can be quantified by spectrophotometry in the presence of 2,2`-biquinoline 4,4`-dicarboxylic acid (BCA). The analytical response was linear between 10 and 100 mu mol L(-1) uric acid with a detection limit of 3.0 mu mol L(-1) (99.7% confidence level). Coefficient of variation of 1.2% and sampling rate of 150 determinations per hour were achieved. Per determination, 32 mu g of CuSO(4) and 200 mu g of BCA were consumed, generating 2.0 mL of waste. Recoveries from 91 to 112% were estimated and the results for 7 urine samples agreed with those obtained by the commercially available enzymatic kit for determination of uric acid. The procedure required 100-fold dilution of urine samples, minimizing sample consumption and interfering effects. In order to avoid the manual dilution step, on-line sample dilution was achieved by a simple system reconfiguration attaining a sampling rate of 95 h(-1). (C) 2009 Elsevier B.V. All rights reserved.

Green Chemistry-Sensitive Analytical Procedure for Photometric Determination of Orthophosphate in River and Tap Water by Use of a Simple LED-Based Photometer

In the current work a Green Analytical Chemistry (GAC) procedure for photometric determination of orthophosphate in river water at mu g L-1 concentration level is described. The flow system module and the LED-based photometer were assembled together to constitute a compact unit in order to allow that a flow cell with optical path-length of 100mm was coupled to them. The photometric procedure based on the molybdenum blue method was implemented employing the multicommuted flow injection analysis approach, which provided facilities to allow reduction of reagent consumption and as well as waste generation. Aiming to prove the usefulness of the system, orthophosphate in river and tap waters was determined. Accuracy was ascertained by spiking samples with orthophosphate solution yielding recoveries ranging from 96% up to 107%. Other profitable features such as a wide linear response range between 10 to 800 mu g L-1 [image omitted]; a detection limit (3 sigma criterion) of 2.4 mu g L-1 [image omitted]; a relative standard deviation (n=7) of 2% using a typical water sample with concentration of 120 mu g L-1 [image omitted]; reagent consumption of 3.0mg ammonium molybdate, 0.3mg hydrazine sulfate, and 0.03mg stannous chloride per determination; a waste generation of 2.4mL per determination; and a sampling throughput of 20 determination per hours were also achieved.

A critical evaluation of a flow-cell based on a liquid core waveguide for chemiluminescence measurements

Liquid-core waveguides (LCWs), devices that constrain the emitted radiation minimizing losses during the transport, are an alternative to maximize the amount of detected radiation in luminescence. In this work, the performance of a LCW flow-cell was critically evaluated for chemiluminescence measurements, by using as model the oxidation of luminol by hydrogen peroxide or hypochlorite. An analytical procedure for hypochlorite determination was also developed, with linear response in the range 0.2-3.8 mg/L (2.7-51 mu mol/L), a detection limit estimated as 8 mu g/L (0.64 mu mol/L) at the 99.7% confidence level and luminol consumption of 50 mu g/determination. The coefficients of variation were 3.3% and 1.6% for 0.4 and 1.9 mg/L CIO(-), respectively, with a sampling rate of 164 determinations/h. The procedure was applied to the analysis of Dakin`s solution samples, yielding results in agreement with those obtained by iodometric titration at the 95% confidence level. Copyright (c) 2008 John Wiley & Sons, Ltd.