Distributed predictive control: A non-cooperative algorithm with neighbor-to-neighbor communication for linear systems

This paper presents a novel Distributed Predictive Control (DPC) algorithm for linear discrete-time systems. This method enjoys the following properties: (i) state and input constraints can be considered; (ii) under mild assumptions, convergence of the closed loop control system is proved; (iii) it is not necessary for each subsystem to know the dynamical models of the other subsystems; (iv) the transmission of information is limited, in that each subsystem only needs the reference trajectories of the state variables of its neighbors. A simulation example is reported to illustrate the main characteristics and performance of the algorithm.     

Thresholds for error probability measures of business process models

The quality of conceptual business process models is highly relevant for the design of corresponding information systems. In particular, a precise measurement of model characteristics can be beneficial from a business perspective, helping to save costs thanks to early error detection. This is just as true from a software engineering point of view. In this latter case, models facilitate stakeholder communication and software system design. Research has investigated several proposals as regards measures for business process models, from a rather correlational perspective. This is helpful for understanding, for example size and complexity as general driving forces of error probability. Yet, design decisions usually have to build on thresholds, which can reliably indicate that a certain counter-action has to be taken. This cannot be achieved only by providing measures; it requires a systematic identification of effective and meaningful thresholds. In this paper, we derive thresholds for a set of structural measures for predicting errors in conceptual process models. To this end, we use a collection of 2000 business process models from practice as a means of determining thresholds, applying an adaptation of the ROC curve method. Furthermore, an extensive validation of the derived thresholds was conducted by using 429 EPC models from an Australian financial institution. Finally, significant thresholds were adapted to refine existing modeling guidelines in a quantitative way.     

Seasonal and temporal study of the northwest African upwelling system

The upwelling index (UI) obtained from sea surface temperature (SST) images for the period 1987–2006 and remote sensing wind stress were used to analyse the features of the coastal upwelling region off northwest Africa. The seasonal distribution shows a persistent upwelling throughout the year from 20° N to 33° N, seasonal behaviour from 12° N to south of 20° N, and an almost total lack of upwelling throughout the year from 5° N to 12° N. The major centres of active upwelling are located around Cape Ghir, Cape Juby and Cape Blanc. The UI shows an intensification of the upwelling system off northwest Africa during the 20-year period while the alongshore wind stress remains almost stable. During this period, upwelled waters off Cape Blanc have increased their offshore spreading.     

Model-based fault detection and isolation for a diesel lean NOx trap aftertreatment system

The lean ${\mathrm{NO}}_x$ trap (LNT) is an aftertreatment device used to reduce nitrogen oxides emissions on Diesel engines. To operate the LNT with high conversion efficiency, an optimized regeneration schedule is required, together with closed-loop control of the air/fuel ratio during regeneration. Furthermore, to comply with emissions regulations, diagnostic schemes are needed to detect and isolate faults, typically related to aging, sulfur poisoning and thermal deactivation.The paper describes a step-by-step methodology for the design and validation of model-based fault diagnosis for a LNT aftertreatment system. The approach is based on a control-oriented model of the LNT validated with experimental data.The proposed diagnostic approach is based on the generation of residuals using system models, through the comparison of the predicted and measured values of selected output variables. The paper focuses on the detection and isolation of sensor faults and LNT parametric faults. Different diagnostic methodologies are presented in relation to the detection of specific faults.Starting from sulfur poisoning detection in a laboratory environment which represents a preliminary validation of the approach, the diagnostic scheme is extended to detect various faults under different plant configurations and operating conditions, with a final application to on-board fault detection and isolation.     

Moving-horizon partition-based state estimation of large-scale systems

This paper presents three novel moving-horizon estimation (MHE) methods for discrete-time partitioned linear systems, i.e., systems decomposed into coupled subsystems with non-overlapping states. The MHE approach is used due to its capability of exploiting physical constraints on states and noise in the estimation process. In the proposed algorithms, each subsystem solves reduced-order MHE problems to estimate its own state and different estimators have different computational complexity, accuracy and transmission requirements among subsystems. In all cases, proper tuning of the design parameters, i.e., the penalties on the states at the beginning of the estimation horizon, guarantees convergence of the estimation error to zero. Numerical simulations demonstrate the viability of the approach.     

Layout design in dynamic environments: Strategies and quantitative indices

The design of a layout is a critical step, which may have a major influence on the success of a plant, particularly when demand is uncertain and variable. In order to counter this variability, one of two strategies is generally adopted, i.e. the identification of either a robust or an agile layout. This study proposes the adoption of indices that will help in identifying the strategy to be preferred. Starting from the case of a single row layout, the results of an experimental campaign are presented and discussed in order to show the efficacy of the indices themselves. Their calculation takes into account the profile of demand over time together with the product route sheets.     

Experimental analysis and simulation of the gas transport in dense Hyflon AD60X membranes: Influence of residual solvent

The present paper discusses the tendency of solution-cast Hyflon^® AD membranes to retain unexpectedly high amounts of solvent, the possible reasons of this phenomenon and its effect on the membrane performance. Dense membranes, prepared by solution-casting and subsequent evaporation, showed large differences in their thermal, mechanical and transport properties, depending on the residual solvent content. Complete solvent removal required heating under vacuum up to well above the glass transition temperature. Analysis of the permeability, diffusion and solubility coefficients of six permanent gases showed that plasticization by the residual solvent reduces the permselectivity and increases the permeability.Data of solution-cast membranes after complete solvent removal compare well with those of a melt-pressed sample. Experimental gas transport parameters were confronted with simulated data, obtained by the Gusev-Suter Transition-State Theory (TST) method and by molecular dynamics (MD) simulations. ¹H High Resolution Magic Angle Spinning Nuclear Magnetic Resonance spectroscopic analysis of the residual solvent in the polymer matrix did not reveal a particular interaction between polymer and solvent, suggesting that the solvent retention is mainly diffusion controlled.     

Large-Scale Assessment of Drought Variability Based on NCEP/NCAR and ERA-40 Re-Analyses

The impacts of different spatial resolutions and different data assimilation schemes of the available re-analysis data sets (NCEP/NCAR and ERA-40) on the assessment of drought variability are analysed. Particular attention has been devoted to the analysis of the possible existence of a linear trend in the climatic signal. The long-term aspects of drought over the globe during the last forty years have been evaluated by computing the Standardized Precipitation Index (SPI) on 24-month time scale. The SPI, in fact, seems to be a useful tool for monitoring dry and wet periods on multiple time scales and comparing climatic conditions of areas governed by different hydrological regimes. To unveil possible discrepancies between the analyses carried out with the two data sets, we studied the leading space-time variability of drought by applying the principal component analysis (PCA) to the SPI time series. Results suggest that on the global scale, the two re-analyses agree in their first principal component score, but not in the associated loading: both re-analyses capture a linear trend, though the areas where this feature should be most likely observed are not uniquely identified by the two data sets. Moreover, while the ERA-40 unveils the presence of a weak net “global” trend towards wet conditions, the NCEP/NCAR re-analysis suggests that the areas in the world characterised by positive/negative trends balance to zero. At large regional scale, a good agreement of the results with those obtained from the observations are found for the United Stated, while for the European sector the two re-analyses show remarkable differences both in the first loading and in representing the timing of the wet and dry periods. Also for these areas a linear trend, superposed on other short-term fluctuations, is detectable in the first principal component of the SPI field.     

Minor compounds in the phenolic fraction of virgin olive oils

The phenolic fraction of 34 virgin olive oils was analysed by gas chromatography–mass spectrometry (GC–MS) with the aim to identify new compounds at low level. Twenty-seven compounds previously described in olive oils were identified; several new minor compounds with phenolic structure were detected in the samples: amongst them, 4-hydroxyphenylacetaldehyde, trans-isoeugenol (trans-2-methoxy-4-(1-propenyl)-phenol), 1,4-dihydroxy-2,6-dimethoxybenzene, 3,4-dihydroxybenzyl alcohol and 3,4-dihydroxyphenylacetic acid were identified by their mass spectra and confirmed using standards. In 34 virgin olive oils (cv. Nocellara del Belice) the mean concentrations for these five substances were always below 0.2 mg kg⁻¹ and only in two samples the level of 3,4-dihydroxyphenylacetic acid reached 1.47 and 1.97 mg kg⁻¹, respectively. These compounds could be used to characterise olive oils; low concentrations of 3,4-dihydroxyphenylacetic acid may show the initial autoxidation processes of olive oils.