Robust Nonlinear Output Regulation by Identification Tools

The present thesis focuses on the problem of robust output regulation for minimum phase nonlinear systems by means of identification techniques. Given a controlled plant and an exosystem (an autonomous system that generates eventual references or disturbances), the control goal is to design a proper regulator able to process the only measure available, i.e the error/output variable, in order to make it asymptotically vanishing. In this context, such a regulator can be designed following the well known “internal model principle” that states how it is possible to achieve the regulation objective by embedding a replica of the exosystem model in the controller structure. The main problem shows up when the exosystem model is affected by parametric or structural uncertainties, in this case, it is not possible to reproduce the exact behavior of the exogenous system in the regulator and then, it is not possible to achieve the control goal. In this work, the idea is to find a solution to the problem trying to develop a general framework in which coexist both a standard regulator and an estimator able to guarantee (when possible) the best estimate of all uncertainties present in the exosystem in order to give “robustness” to the overall control loop.

Bioremediation of PCB-contaminated marine sediments: From identification of indigenous dehalorespirers to enhancement of microbial reductive dechlorination

Marine sediments are the main accumulation reservoir of organic recalcitrant pollutants such as polychlorinated biphenyls (PCBs). In the anoxic conditions typical of these sediments, anaerobic bacteria of the phylum Chloroflexi are able to attack these compounds in a process called microbial reductive dechlorination. Such activity and members of this phylum were detected in PCB-impacted sediments of the Venice Lagoon. The aim of this work was to investigate microbial reductive dechlorination and design bioremediation approaches for marine sediments of the area. Three out of six sediment cultures from different sampling areas exhibited dechlorination activities in the same conditions of the site and two phylotypes (VLD-1 and VLD-2) were detected and correlated to this metabolism. Biostimulation was tested on enriched dechlorinating sediment cultures from the same site using five different electron donors, of which lactate was the best biostimulating agent; complementation of microbial and chemical dechlorination catalyzed by biogenic zerovalent Pd nanoparticles was not effective due to sulfide poisoning of the catalyst. A new biosurfactant-producing strain of Shewanella frigidimarina was concomitantly obtained from hydrocarbon-degrading marine cultures and selected because of the low toxicity of its product. All these findings were then exploited to develop bioremediation lab-scale tests in shaken reactors and static microcosms on real sediments and water of the Venice lagoon, testing i) a bioaugmentation approach, with a selected enriched sediment culture from the same area, ii) a biostimulation approach with lactate as electron donor, iii) a bioavailability enhancement with the supplementation of the newly-discovered biosurfactant, and iv) all possible combinations of the afore-mentioned approaches. The best bioremediation approach resulted to be a combination of bioaugmentation and bioremediation and it could be a starting point to design bioremediation process for actual marine sediments of the Venice Lagoon area.

Boundary condition identification of a bridge pier using experimental data and FEM modal updating

Over the past twenty years, new technologies have required an increasing use of mathematical models in order to understand better the structural behavior: finite element method is the one mostly used. However, the reliability of this method applied to different situations has to be tried each time. Since it is not possible to completely model the reality, different hypothesis must be done: these are the main problems of FE modeling. The following work deals with this problem and tries to figure out a way to identify some of the unknown main parameters of a structure. This main research focuses on a particular path of study and development, but the same concepts can be applied to other objects of research. The main purpose of this work is the identification of unknown boundary conditions of a bridge pier using the data acquired experimentally with field tests and a FEM modal updating process. This work doesn’t want to be new, neither innovative. A lot of work has been done during the past years on this main problem and many solutions have been shown and published. This thesis just want to rework some of the main aspects of the structural optimization process, using a real structure as fitting model.

Identification of novel rhoptry proteins in Neospora caninum by LC/MS-MS analysis of subcellular fractions

Apicomplexan parasites possess an apical complex that is composed of two secretory organelles recognized as micronemes and rhoptries. Rhoptry contents are secreted into the parasitophorous vacuole during the host cell invasion process. Several rhoptry proteins have been identified in Toxoplasma gondii and seem to be involved in host-pathogen interactions and some of them are considered to be important virulence factors. Only one rhoptry protein, NcROP2, has been identified and extensively characterized in the closely related parasite Neospora caninum, and this has showed immunoprotective properties. Thus, with the aim of increasing knowledge of the rhoptry protein repertoire in N. caninum, a subcellular fractionation of tachyzoites was performed to obtain fractions enriched for this secretory organelle. 2-D SDS-PAGE followed by MS and LC/MS-MS were applied for fraction analysis and 8 potential novel rhoptry components (NcROP1, 5, 8, 30 and NcRON2, 3, 4, 8) and several kinases, proteases and phosphatases proteins were identified with a high homology to those previously found in T. gondii. Their existence in N. caninum tachyzoites suggests their involvement in similar events or pathways that occur in T. gondii. These novel proteins may be considered as targets that could be useful in the future development of immunoprophylactic measures.

Teacher resistance to school-based consultation with the school psychologist: An analysis according to school level and model of identification for special education services

Consultation is promoted throughout school psychology literature as a best practice in service delivery. This method has numerous benefits including being able to work with more students at one time, providing practitioners with preventative rather than strictly reactive strategies, and helping school professionals meet state and federal education mandates and initiatives. Despite the benefits of consultation, teachers are sometimes resistant to this process.This research studies variables hypothesized to lead to resistance (Gonzalez, Nelson, Gutkin, & Shwery, 2004) and attempts to distinguish differences between school level (elementary, middle and high school) with respect to the role played by these variables and to determine if the model used to identify students for special education services has an influence on resistance factors. Twenty-sixteachers in elementary and middle schools responded to a demographicquestionnaire and a survey developed by Gonzalez, et al. (2004). This survey measures eight variables related to resistance to consultation. No high school teachers responded to the request to participate. Results of analysis of variance indicated a significant difference in the teaching efficacy subscale with elementary teachers reporting more efficacy in teaching than middle school teachers. Results also indicate a significant difference in classroom managementefficacy with teachers who work in schools that identify students according to a Response to Intervention model reporting higher classroom management efficacy than teachers who work in schools that identify students according to a combined method of refer-test-place/RtI combination model. Implications, limitations and directions for future research are discussed.

Use of multislice computed tomography in disaster victim identification--advantages and limitations

After a mass fatality incident (MFI), all victims have to be rapidly and accurately identified for juridical reasons as well as for the relatives' sake. Since MFIs are often international in scope, Interpol has proposed standard disaster victim identification (DVI) procedures, which have been widely adopted by authorities and forensic experts. This study investigates how postmortem multislice computed tomography (MSCT) can contribute to the DVI process as proposed by Interpol. The Interpol postmortem (PM) form has been analyzed, and a number of items in sections D and E thereof have been postulated to be suitable for documentation by CT data. CT scans have then been performed on forensic cases. Interpretation of the reconstructed images showed that indeed much of the postmortem information required for identification can be gathered from CT data. Further advantages of the proposed approach concern the observer independent documentation, the possibility to reconstruct a variety of images a long time after the event, the possibility to distribute the work by transmitting CT data digitally, and the reduction of time and specialists needed at the disaster site. We conclude that MSCT may be used as a valuable screening tool in DVI in the future.

Parameter identification of a copper-zeolite SCR catalyst model using reactor data

The selective catalytic reduction system is a well established technology for NOx emissions control in diesel engines. A one dimensional, single channel selective catalytic reduction (SCR) model was previously developed using Oak Ridge National Laboratory (ORNL) generated reactor data for an iron-zeolite catalyst system. Calibration of this model to fit the experimental reactor data collected at ORNL for a copper-zeolite SCR catalyst is presented. Initially a test protocol was developed in order to investigate the different phenomena responsible for the SCR system response. A SCR model with two distinct types of storage sites was used. The calibration process was started with storage capacity calculations for the catalyst sample. Then the chemical kinetics occurring at each segment of the protocol was investigated. The reactions included in this model were adsorption, desorption, standard SCR, fast SCR, slow SCR, NH3 Oxidation, NO oxidation and N2O formation. The reaction rates were identified for each temperature using a time domain optimization approach. Assuming an Arrhenius form of the reaction rates, activation energies and pre-exponential parameters were fit to the reaction rates. The results indicate that the Arrhenius form is appropriate and the reaction scheme used allows the model to fit to the experimental data and also for use in real world engine studies.

MODEL UPDATING AND STRUCTURAL HEALTH MONITORING OF HORIZONTAL AXIS WIND TURBINES VIA ADVANCED SPINNING FINITE ELEMENTS AND STOCHASTIC SUBSPACE IDENTIFICATION METHODS

Wind energy has been one of the most growing sectors of the nation’s renewable energy portfolio for the past decade, and the same tendency is being projected for the upcoming years given the aggressive governmental policies for the reduction of fossil fuel dependency. Great technological expectation and outstanding commercial penetration has shown the so called Horizontal Axis Wind Turbines (HAWT) technologies. Given its great acceptance, size evolution of wind turbines over time has increased exponentially. However, safety and economical concerns have emerged as a result of the newly design tendencies for massive scale wind turbine structures presenting high slenderness ratios and complex shapes, typically located in remote areas (e.g. offshore wind farms). In this regard, safety operation requires not only having first-hand information regarding actual structural dynamic conditions under aerodynamic action, but also a deep understanding of the environmental factors in which these multibody rotating structures operate. Given the cyclo-stochastic patterns of the wind loading exerting pressure on a HAWT, a probabilistic framework is appropriate to characterize the risk of failure in terms of resistance and serviceability conditions, at any given time. Furthermore, sources of uncertainty such as material imperfections, buffeting and flutter, aeroelastic damping, gyroscopic effects, turbulence, among others, have pleaded for the use of a more sophisticated mathematical framework that could properly handle all these sources of indetermination. The attainable modeling complexity that arises as a result of these characterizations demands a data-driven experimental validation methodology to calibrate and corroborate the model. For this aim, System Identification (SI) techniques offer a spectrum of well-established numerical methods appropriated for stationary, deterministic, and data-driven numerical schemes, capable of predicting actual dynamic states (eigenrealizations) of traditional time-invariant dynamic systems. As a consequence, it is proposed a modified data-driven SI metric based on the so called Subspace Realization Theory, now adapted for stochastic non-stationary and timevarying systems, as is the case of HAWT’s complex aerodynamics. Simultaneously, this investigation explores the characterization of the turbine loading and response envelopes for critical failure modes of the structural components the wind turbine is made of. In the long run, both aerodynamic framework (theoretical model) and system identification (experimental model) will be merged in a numerical engine formulated as a search algorithm for model updating, also known as Adaptive Simulated Annealing (ASA) process. This iterative engine is based on a set of function minimizations computed by a metric called Modal Assurance Criterion (MAC). In summary, the Thesis is composed of four major parts: (1) development of an analytical aerodynamic framework that predicts interacted wind-structure stochastic loads on wind turbine components; (2) development of a novel tapered-swept-corved Spinning Finite Element (SFE) that includes dampedgyroscopic effects and axial-flexural-torsional coupling; (3) a novel data-driven structural health monitoring (SHM) algorithm via stochastic subspace identification methods; and (4) a numerical search (optimization) engine based on ASA and MAC capable of updating the SFE aerodynamic model.

RFID Transponders : Link between information and material flows. How reliable are identification procedures?

Along with the growing complexity of logistic chains the demand for transparency of informations has increased. The use of intelligent RFID-Technology offers the possibility to optimize and control all capacities in use, since it enables the identification and tracking of goods alongside the entire supply chain. Every single product can be located at any given time and a multitude of current and historical data can be transferred. The interaction of the flow of material and the flow of information between the various process steps can be optimized by using RFID-Technology since it guarantees that all required data is available at the right time and at the right place. The local accessibility and convertibility of data allows a flexible, decentralised control of logistic systems. As additional advantages of RFID-Components can be considered that they are individually writable and that their identification can be achieved over considerable distances even if there is no intervisibility between tag and reader. The use of RFID-Transponder opens up new potentials regarding process security, reduction of logistic costs or availability of products. These advantages depend on reliability of the identification processes. The undisputed potentials that are made accessible by the use of RFID-Elements can only be beneficial when the informations that are decentralised and attached to goods and loading equipment can be reliably retrieved at the required points. The communication between tag and reader can be influenced by different materials such as metal, that can disturbed or complicate the radio contact. The communications reliability is subject of various tests and experiments that analyse the effects of different filling materials as well as different alignments of tags on the loading equipment.

Proteomic identification of in vivo substrates for matrix metalloproteinases 2 and 9 reveals a mechanism for resolution of inflammation.

Clearance of allergic inflammatory cells from the lung through matrix metalloproteinases (MMPs) is necessary to prevent lethal asphyxiation, but mechanistic insight into this essential homeostatic process is lacking. In this study, we have used a proteomics approach to determine how MMPs promote egression of lung inflammatory cells through the airway. MMP2- and MMP9-dependent cleavage of individual Th2 chemokines modulated their chemotactic activity; however, the net effect of complementing bronchoalveolar lavage fluid of allergen-challenged MMP2(-/-)/MMP9(-/-) mice with active MMP2 and MMP9 was to markedly enhance its overall chemotactic activity. In the bronchoalveolar fluid of MMP2(-/-)/MMP9(-/-) allergic mice, we identified several chemotactic molecules that possessed putative MMP2 and MMP9 cleavage sites and were present as higher molecular mass species. In vitro cleavage assays and mass spectroscopy confirmed that three of the identified proteins, Ym1, S100A8, and S100A9, were substrates of MMP2, MMP9, or both. Function-blocking Abs to S100 proteins significantly altered allergic inflammatory cell migration into the alveolar space. Thus, an important effect of MMPs is to differentially modify chemotactic bioactivity through proteolytic processing of proteins present in the airway. These findings provide a molecular mechanism to explain the enhanced clearance of lung inflammatory cells through the airway and reveal a novel approach to target new therapies for asthma.

Fast parallel kriging-based stepwise uncertainty reduction with application to the identification of an excursion set

Stepwise uncertainty reduction (SUR) strategies aim at constructing a sequence of points for evaluating a function  f in such a way that the residual uncertainty about a quantity of interest progressively decreases to zero. Using such strategies in the framework of Gaussian process modeling has been shown to be efficient for estimating the volume of excursion of f above a fixed threshold. However, SUR strategies remain cumbersome to use in practice because of their high computational complexity, and the fact that they deliver a single point at each iteration. In this article we introduce several multipoint sampling criteria, allowing the selection of batches of points at which f can be evaluated in parallel. Such criteria are of particular interest when f is costly to evaluate and several CPUs are simultaneously available. We also manage to drastically reduce the computational cost of these strategies through the use of closed form formulas. We illustrate their performances in various numerical experiments, including a nuclear safety test case. Basic notions about kriging, auxiliary problems, complexity calculations, R code, and data are available online as supplementary materials.

Graphical Model-Based Vertebra Identification from X-Ray Image(s)

Automated identification of vertebrae from X-ray image(s) is an important step for various medical image computing tasks such as 2D/3D rigid and non-rigid registration. In this chapter we present a graphical model-based solution for automated vertebra identification from X-ray image(s). Our solution does not ask for a training process using training data and has the capability to automatically determine the number of vertebrae visible in the image(s). This is achieved by combining a graphical model-based maximum a posterior probability (MAP) estimate with a mean-shift based clustering. Experiments conducted on simulated X-ray images as well as on a low-dose low quality X-ray spinal image of a scoliotic patient verified its performance.

Guidelines for WB3 Part I: Desertification and land degradation: Identification of existing and potential prevention and mitigation strategies

These guidelines are a working instrument for conducting and moderating stakeholder workshops with a participatory approach to initiate a mutual learning process among local and external stakeholders. The overall aim of the workshop is to identify promising (existing and potential) strategies for land and water conservation for the selected study site. DESIRE (Desertification Mitigation and Remediation of Land) is a European Integrated Project. The DESIRE WB 3 methodology was developed by CDE and is based on experiences from Learning for Sustainability (LforS) and WOCAT.

The Quiet Eye and Information Processing: Facilitation of Stimulus Identification and Response Selection

Background: A prerequisite for high performance in motor tasks is the acquisition of egocentric sensory information that must be translated into motor actions. A phenomenon that supports this process is the Quiet Eye (QE) defined as long final fixation before movement initiation. It is assumed that the QE facilitates information processing, particularly regarding movement parameterization. Aims: The question remains whether this facilitation also holds for the information-processing stage of response selection and – related to perception crucial – stage of stimulus identification. Method: In two experiments with sport science students, performance-enhancing effects of experimentally manipulated QE durations were tested as a function of target position predictability and target visibility, thereby selectively manipulating response selection and stimulus identification demands, respectively. Results: The results support the hypothesis of facilitated information processing through long QE durations since in both experiments performance-enhancing effects of long QE durations were found under increased processing demands only. In Experiment 1, QE duration affected performance only if the target position was not predictable and positional information had to be processed over the QE period. In Experiment 2, in a full vs. no target visibility comparison with saccades to the upcoming target position induced by flicker cues, the functionality of a long QE duration depended on the visual stimulus identification period as soon as the interval falls below a certain threshold. Conclusions: The results corroborate earlier findings that QE efficiency depends on demands put on the visuomotor system, thereby furthering the assumption that the phenomenon supports the processes of sensorimotor integration.

Cerebellar Pathology Does Not Impair Performance on Identification or Categorization Tasks

In comparison to the basal ganglia, prefrontal cortex, and medial temporal lobes, the cerebellum has been absent from recent research on the neural substrates of categorization and identification, two prominent tasks in the learning and memory literature. To investigate the contribution of the cerebellum to these tasks, we tested patients with cerebellar pathology (seven with bilateral degeneration, six with unilateral lesions, and two with midline damage) on rule-based and information-integration categorization tasks and an identification task. In rule-based tasks, it is assumed that participants learn the categories through an explicit reasoning process. In information-integration tasks, optimal performance requires the integration of information from multiple stimulus dimensions, and participants are typically unaware of the decision strategy. The identification task, in contrast, required participants to learn arbitrary, color-word associations. The cerebellar patients performed similar to matched controls on all three tasks and performance did not vary with the extent of cerebellar pathology. Although the interpretation of these null results requires caution, these data contribute to the current debate on cerebellar contributions to cognition by providing boundary conditions on understanding the neural substrates of categorization and identification, and help define the functional domain of the cerebellum in learning and memory.