Set-Point Tracking MPC with Avoidance Features

This work proposes a finite-horizon optimal control strategy to solve the tracking problem while providing avoidance features to the closed-loop system. Inspired by the set-point tracking model predictive control (MPC) framework, the central idea of including artificial variables into the optimal control problem is considered. This approach allows us to add avoidance features into the set-point tracking MPC strategy without losing the properties of an enlarged domain of attraction and feasibility insurances in the face of any changing reference. Besides, the artificial variables are considered together with an avoidance cost functional to establish the basis of the strategy, maintaining the recursive feasibility property in the presence of a previously unknown number of regions to be avoided. It is shown that the closed-loop system is recursively feasible and input-to-state-stable under the mild assumption that the avoidance cost is uniformly bounded over time. Finally, two numerical examples illustrate the controller behavior

Fresh-Cut Vegetables Processing: Environmental Sustainability and Food Safety Issues in a Comprehensive Perspective

The fresh-cut industry supplies the food market with healthy fresh fruit and vegetables and, in that way, may contribute to improve the nutritional status of the general population. On the other hand, over the last few years increasing concerns have been raised regarding the environmental impact of the fresh-cut industry, human health risks from exposure to disinfection by-products found in fresh-cut products and chlorine-based disinfection treatments during produce processing. This review provides a comprehensive view of the main interlinked aspects related to food safety and environmental impact of processing of fresh-cut vegetables. Advantages and downsides of the mainstream disinfection strategy, based on the use of chlorine-related disinfecting agents, along with some alternative treatments close to a wide commercial application, are discussed. Limitation in the application of these strategies to processing of organic fresh-cut produce are also highlighted, examining the specific environmental and food safety problems in the organic sector. Areas where lack of available information hinders at present a clear understanding of priorities of research and action are pointed out. Innovative conceptual tools are proposed to address these multiple and interlinking issues and to overcome limitations of currently available technologies. A comprehensive and multidisciplinary approach is suggested to move toward a more safe and environmentally sustainable production of fresh-cut products

Nonlinear Model Predictive Path Following Controller with Obstacle Avoidance

In the control systems community, path-following refers to the problem of tracking an output reference curve. This work presents a novel model predictive path-following control formulation for nonlinear systems with constraints, extended with an obstacle avoidance strategy. The method proposed in this work simultaneously provides an optimizing solution for both, path-following and obstacle avoidance tasks in a single optimization problem, using Nonlinear Model Predictive Control (NMPC). The main idea consists in extending the existing NMPC controllers by the introduction of an additional auxiliary trajectory that maintains the feasibility of the successive optimization problems even when the reference curve is unfeasible, possibly discontinuous, relaxing assumptions required in previous works. The obstacle avoidance is fulfilled by introducing additional terms in the value functional, rather than imposing state space constraints, with the aim of maintaining the convexity of the state and output spaces. Simulations results considering an autonomous vehicle subject to input and state constraints are carried out to illustrate the performance of the proposed control strategy.Fil: Sánchez, Ignacio Julián Rodolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Matemática Aplicada del Litoral. Universidad Nacional del Litoral. Instituto de Matemática Aplicada del Litoral; ArgentinaFil: D'jorge, Agustina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Raffo, Guilherme V.. Universidade Federal de Minas Gerais; BrasilFil: González, Alejandro Hernán. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Ferramosca, Antonio. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

Measurement uncertainty propagation in transistor model parameters via polynomial chaos expansion

We present an analysis of the propagation of measurement uncertainty in microwave transistor nonlinear models. As a case study, we focus on residual calibration uncertainty and its effect on modeled nonlinear capacitances extracted from small-signal microwave measurements. We evaluate the uncertainty by means of the polynomial chaos expansion (PCE) method and compare the results with the NIST Microwave Uncertainty Framework, which enables both sensitivity and Monte Carlo (MC) analyses for uncertainty quantification in microwave measurements. We demonstrate that, for the considered application, PCE provides results in agreement with classical MC simulations but with a significant reduction of the computational effort

Accurate pHEMT nonlinear modeling in the presence of low-frequency dispersive effects

Low-frequency (LF) dispersive phenomena due to device self-heating and/or the presence of "traps" (i.e., surface state densities and bulk spurious energy levels) must be taken into account in the large-signal dynamic modeling of III-V field-effect transistors when accurate performance predictions are pursued, since these effects cause important deviations between direct current (dc) and dynamic drain current characteristics. In this paper, a new model for the accurate characterization of these phenomena above their cutoff frequencies is presented, which is able to fully exploit, in the identification phase, large-signal current-voltage (I-V) measurements carried out under quasi-sinusoidal regime using a recently proposed setup. Detailed experimental results for model validation under LF small- and large-signal operating conditions are provided. Furthermore, the I-V model proposed has been embedded into a microwave large-signal pseudomorphic high electron-mobility transistor (pHEMT) model in order to point out the strong influence of LF modeling on the degree of accuracy achievable under millimeter-wave nonlinear operation. Large-signal experimental validation at microwave frequencies is provided for the model proposed, by showing the excellent intermodulation distortion (IMD) predictions obtained with different loads despite the very low power level of IMD products involved. Details on the millimeter-wave IMD measurement setup are also provided. Finally, IMD measurements and simulations on a Ka-band highly linear power amplifier, designed by Ericsson using the Triquint GaAs 0.25-/spl mu/m pHEMT process, are shown for further model validation

Dual-Layer Single-Varactor Driven Reflectarray Cell for Broad-Band Beam-Steering and Frequency Tunable Applications

A dual-layer active reflectarray configuration is proposed for broad-band beam-steering and/or frequency-tunable applications. A unit cell composed by two stacked fixed-size rectangular patches, properly loaded with a single varactor diode, is designed to realize the dynamic phase tuning mechanism. The proposed approach offers wider bandwidths, with respect to the existing varactor-based reflectarray cells, and quite good frequency reconfigurability features, as demanded by several radar or satellite communication applications. An X-band reflectarray cell is fabricated and tested, to prove the effectiveness of the proposed approach, achieving a 318° phase agility within a measured frequency range of about 14.6% with respect to the central design frequency (i.e., 11 GHz). Wideband beam-steering reflectarray designs are demonstrated, showing 1-dB gain bandwidths equal to 9-10%

Chemical composition and biological activities of essential oils from Origanum vulgare genotypes belonging to the carvacrol and thymol chemotypes

The remarkable biological activities of oregano essential oils (EOs) have recently prompted a host of studies aimed at exploring their potential innovative applications in the food and pharmaceutical industries. The chemical composition and biological activities of EOs from two Origanum vulgare genotypes, widely cultivated in Sicily and not previously studied for their biological properties, were characterized. Plants of the two genotypes, belonging to the carvacrol (CAR) and thymol (THY) chemotypes and grown in different cultivation environments, were considered for this study. The chemical profiles, including the determination of enantiomeric distribution, of the EOs, obtained by hydrodistillation from dried leaves and flowers, were investigated by GC-MS. Biological activity was evaluated as antimicrobial properties against different pathogen indicator strains, while intestinal barrier integrity, reduction in pathogen adhesion and anti-inflammatory actions were assayed in the intestinal Caco-2 cell line. The chemical profile of the CAR genotype was less complex and characterized by higher levels of the most active compound, i.e., carvacrol, when compared to the THY genotype. The enantiomeric distribution of chiral constituents did not vary across genotypes, while being markedly different from that observed in Origanum vulgare genotypes from other geographical origins. In general, all EOs showed high antimicrobial activity, both in vitro and in a food matrix challenge test. Representative EOs from the two genotypes resulted not altering epithelial monolayer sealing only for concentrations lower than 0.02%, were able to reduce the adhesion of selected pathogens, but did not exert relevant anti-inflammatory effects. These results suggest their potential use as control agents against a wide spectrum of foodborne pathogens

Impact of different temperature abuse scenarios on sensory quality and off-odour formation in ready-to-eat salad leaves

Packages of ready-to-eat (RTE) wild rocket and lettuce baby leaves were subjected during 8 days of cold storage to a chronic temperature abuse (CTA) at sub-optimal storage temperature (10 °C) or to a shortterm (6 h) abuse at ambient temperature (STA) to evaluate the impact of two temperature abuse scenarios on gas composition within the packages, leaf sensory quality and volatile organic compounds (VOCs). In both species, the CTA scenario had a markedly higher impact on gas composition, sensory quality and off-odour formation than the STA, and the limit of sensory acceptability was reached in the CTA scenario 4 days or more earlier than in the STA. Sulphur compounds were the main responsible for offodour perception in both leafy salads. Results from the present study may be useful in the assessment of critical points in the cold chain of RTE fresh produce and in prioritising actions towards improved coldchain management