Design of experiments for nonlinear system identification: A set membership approach

Design of Experiments (DoE) is an important step in system identification. Regardless of the chosen model structure and identification method, the DoE quality determines an upper bound on the accuracy of the identified models. One of the greatest challenges in this context is to design an experiment which gives the maximum information about the dynamics of the system of interest. In this paper, a novel DoE algorithm for input-constrained MISO nonlinear systems, based on set membership identification, is proposed. The DoE algorithm is aimed to minimize the so-called radius of information, a quantity giving the worst-case model error. Two numerical examples are presented, showing the effectiveness of the approach and its potential in view of real-world applications

Effect of morphology and defectiveness of graphene-related materials on the electrical and thermal conductivity of their polymer nanocomposites

In this work, electrically and thermally conductive poly (butylene terephthalate) nanocomposites were prepared by in-situ ring-opening polymerization of cyclic butylene terephthalate (CBT) in presence of a tin-based catalyst. One type of graphite nanoplatelets (GNP) and two different grades of reduced graphene oxide (rGO) were used. Furthermore, high temperature annealing treatment under vacuum at 1700{\deg}C was carried out on both RGO to reduce their defectiveness and study the correlation between the electrical/thermal properties of the nanocomposites and the nanoflakes structure/defectiveness. The morphology and quality of the nanomaterials were investigated by means of electron microscopy, x-ray photoelectron spectroscopy, thermogravimetry and Raman spectroscopy. Thermal, mechanical and electrical properties of the nanocomposites were investigated by means of rheology, dynamic mechanical thermal analysis, volumetric resistivity and thermal conductivity measurements. Physical properties of nanocomposites were correlated with the structure and defectiveness of nanoflakes, evidencing a strong dependence of properties on nanoflakes structure and defectiveness. In particular, a significant enhancement of both thermal and electrical conductivities was demonstrated upon the reduction of nanoflakes defectiveness

Data-Driven Disturbance Estimation and Control with Application to Blood Glucose Regulation

A data-driven control approach for nonlinear systems is proposed, called data-driven estimation and control (D2EC), which combines a disturbance estimator and a nonlinear control algorithm. The estimator provides a signal representing the unknown disturbances affecting the plant to control. This signal is used by the control algorithm to improve its performance. A real-data study is presented, concerned with the regulation of blood glucose concentration in type 1 diabetic patients. Preliminary tests of the D2EC approach are also carried out using a diabetic patient simulator, obtained from a revised version of the well-known University of Virginia/Padova model. Both the real-data and the simulator-based studies indicate that the proposed approach has the potential to become an effective tool in the context of diabetes treatment and, more in general, in the biomedical field, where accurate first-principle models can seldom be found and relevant disturbances are present

Effect of processing conditions on the thermal and electrical conductivity of poly (butylene terephthalate) nanocomposites prepared via ring-opening polymerization

Successful preparation of polymer nanocomposites, exploiting graphene-related materials, via melt mixing technology requires precise design, optimization and control of processing. In the present work, the effect of different processing parameters during the preparation of poly (butylene terephthalate) nanocomposites, through ring-opening polymerization of cyclic butylene terephthalate in presence of graphite nanoplatelets (GNP), was thoroughly addressed. Processing temperature (240{\deg}C or 260{\deg}C), extrusion time (5 or 10 minutes) and shear rate (50 or 100 rpm) were varied by means of a full factorial design of experiment approach, leading to the preparation of polybutylene terephthalate/GNP nanocomposite in 8 different processing conditions. Morphology and quality of GNP were investigated by means of electron microscopy, X-ray photoelectron spectroscopy, thermogravimetry and Raman spectroscopy. Molecular weight of the polymer matrix in nanocomposites and nanoflake dispersion were experimentally determined as a function of the different processing conditions. The effect of transformation parameters on electrical and thermal properties was studied by means of electrical and thermal conductivity measurement. Heat and charge transport performance evidenced a clear correlation with the dispersion and fragmentation of the GNP nanoflakes; in particular, gentle processing conditions (low shear rate, short mixing time) turned out to be the most favourable condition to obtain high conductivity values

Linaceae

Hierbas, raro arbustos. Hojas alternas, enteras, con o sin estípulas. Inflorescencias cimosas, raro flores solitarias. Flores cíclicas, actinomorfas, perfectas. Cáliz con (4-) 5 sépalos soldados o libres, persistentes hasta la dehiscencia del fruto. Corola con 5 pétalos libres, raro unidos en la base, caedizos. Estambres 5 oposipétalos; filamentos unidos en la base formando un anillo, pueden presentar 5 estaminodios, alternos a los estambres. Ovario súpero con 2-5 carpelos soldados y 4-10 lóculos formados por falsos tabiques, óvulos 1-2 por lóculo; estilos 2-5. Fruto generalmente cápsula septici da, en algunas especies drupáceo; semillas aplanadas con o sin endosperm

New trends in teacher\u2019s education. Educational placement of the adopted child

In Italy, the number of adopted school-age children is increasing. According to the Commission of Intercountry Adoption (2013), 3106 children were adopted, 47.5% of them are between 5 and 9 years old. The present action-research aims at exploring the spread of good approaches in schools in terms of welcoming of adopted children. For this purpose, 268 teachers of primary schools were involved in analyzing the social representation about adopted children and their family. The results show a simplified vision of the adoptive family, which is described as heroic family or, on the contrary, as a family with difficulty

“Is This Enough?” Digitizing Liz Lerman Dance Exchange Archives Media

Special Collections in Performing Arts (SCPA) at University of Maryland Libraries collects performing arts materials that preserve performance practice, instruction, and scholarship, including the full scope of audiovisual (AV) formats. The Liz Lerman Dance Exchange Archives at SCPA contains, among common print archival materials, a significant number of AV materials. This collection is examplar of the numerous challenges facing AV digitization and preservation projects in university libraries and archives, including determining metadata standards and best practices, describing at the appropriate level, handling technical and personnel issues, and working with vendors. In this article we outline the decisions made for this project, our ultimate workflow, lessons learned, and future plans

Subspace Identification of a Glucose-Insulin model Using Meal Tracer Protocol Measurements

In this study, the problem of identifying a low complexity state space model describing glucose and insulin dynamics from low sample meal tracer experiments is investigated. Triple tracer meal protocol measurements (sampled as low as 15 samples per meal) together with continuous glucose monitoring measurements, measured concurrently at a rate of 5 minutes per sample, are used. A new formulation to estimate the missing input and output measurements at such low sample rates is developed. Nuclear norm minimization is used to exploit low rankness of the stacked input and output matrix, while the {ell1} norm is used to exploit an available sparse basis for the glucose flux profiles. Simulation results, using the UVa Padova simulator, show that the technique outperforms previous methods and also demonstrate the possibility of identifying state space models from triple tracer measurements with good prediction performance under non-ideal conditions