Implementation of an economic MPC with robustly optimal steady-state behavior

Designing an economic model predictive control (EMPC) algorithm that asymptotically achieves the optimal performance in presence of plant-model mismatch is still an open problem. Starting from previous work, we elaborate an EMPC algorithm using the offset-free formulation from tracking MPC algorithms in combination with modifier-adaptation technique from the real-time optimization (RTO) field. The augmented state used for offset-free design is estimated using a Moving Horizon Estimator formulation, and we also propose a method to estimate the required plant steady-state gradients using a subspace identification algorithm. Then, we show how the proposed formulation behaves on a simple illustrative example

Model predictive control design for multivariable processes in the presence of valve stiction

This paper presents different formulations of Model Predictive Control (MPC) to handle static friction in control valves for industrial processes. A fully unaware formulation, a stiction embedding structure, and a stiction inversion controller are considered. These controllers are applied to multivariable systems, with linear and nonlinear process dynamics. A semiphysical model is used for valve stiction dynamics and the corresponding inverse model is derived and used within the stiction inversion controller. The two-move stiction compensation method is revised and used as warm-start to build a feasible trajectory for the MPC optimal control problem. Some appropriate choices of objective functions and constraints are used with the aim of improving performance in set-points tracking. The different MPC formulations are reviewed, compared, and tested on several simulation examples. Stiction embedding MPC proves to guarantee good performance in set-points tracking and also stiction compensation, at the expense of a lower robustness with respect to other two formulations

A valve stiction tolerant formulation of MPC for industrial processes

This paper presents three different formulations of MPC to face static friction in control valves for industrial processes. A pure linear formulation, a stiction embedding structure, and a stiction inversion controller are designed. The controllers are derived for SISO systems with linear process dynamics, where valve stiction is the only nonlinearity present in the control loop. A novel smoothed stiction model is introduced to improve and fasten the dynamic optimization module of stiction embedding MPC. A stiction compensation method is revised and used as a warm-start to build a suitable trajectory for the predictive controller. The different MPC formulations are tested and compared on some simulation examples

Estimation technique for offset-free economic MPC based on modifier adaptation

Economic model predictive control formulations that combine online optimizing control with offset-free methodologies such as modifier adaptation have been proposed recently. These new algorithms are able to achieve asymptotic optimal performance despite the presence of plant-model mismatch. However, there is a major requirement stemming from the modifier-adaptation part, namely, the necessity to know the static plant gradients at the sought (and therefore still unknown) steady-state operating point. Hence, for implementation purposes, the algorithms need to be enhanced with plant gradient estimation techniques. This work proposes to estimate modifiers directly, based on steady-state perturbations and using Broyden’s approximation. The proposed economic MPC algorithm has been tested in simulation on the Williams-Otto reactor and provides plant optimality upon convergence

Detection and Characterization of Porcine Sapelovirus in Italian Pig Farms

Porcine sapelovirus (PSV) belongs to the genus Sapelovirus of the family Picornaviridae. PSV infects pigs asymptomatically, but it can also cause severe neurologic, enteric, and respiratory symptoms or reproductive failure. Sapelovirus infections have been reported worldwide in pigs. The objective of this study was to investigate the presence and the prevalence of PSV in Italian swine farms in animals of different ages to clarify the occurrence of the infection and the genetic characteristics of circulating strains. In the present study, 92 pools of fecal samples, collected from pigs across three farms, were analyzed by Reverse Transcriptase-polymerase Chain Reaction-PCR (RT-PCR). Fecal pools from young growers (63/64) were found positive for Sapelovirus in all farms while detection in sows (4/28) was observed in only one farm. Phylogenetic analyses of the 19 partial capsid protein nucleotide sequences (VP1) (6\u20137 each farm) enable the classification of the virus sequences into three distinct clades and highlighted the high heterogeneity within one farm. The whole genome sequence obtained from one strain showed the highest correlation with the Italian strain detected in 2015. The study adds novel information about the circulation and heterogeneity of PSV strains in Italy and considering the movement of pigs across Europe would also be informative for other countries

Implementation of an Industry 4.0 system to optimally manage chemical plant operation

The evolution of the process industry in the direction of automation and digitalization is nowadays a consolidated phenomenon. In this direction, Industry 4.0 paradigms are leading many industrial companies to significantly update their facilities. This paper presents a scheduling algorithm that takes the role of a real-time optimization (RTO) element in a larger project framework where the various network components are aimed to be all highly interconnected. The proposed methodology is applied to an Italian chemical industrial site, in order to best manage the production rates of the various products and the sales plan for the different clients. Numerous plants and processes are considered into the model: batch and continuous production lines, saleable and non-storable products. Concepts of linear optimization and batch operation scheduling are used in the algorithm construction. This whole structure lays the foundation for a full integration between different elements of the facility, that is, the control systems and the selling department

The treatment of the organic fraction of municipal solid waste (OFMSW) as a possible source of micro- and nano-plastics and bioplastics in agroecosystems: a review

AbstractPlastics fragmentation into smaller debris, namely, micro- and nano-plastics (MPs and NPs), is a matter of global concern because of their wide distribution in terrestrial and marine environments. The latest research has focused mainly on aquatic ecosystems, and fragmentation of bioplastics into micro- and nano-particles (MBPs and NBPs) is not considered. The distribution, concentration, fate and major source of MPs, NPS, MBPs and NBPs in agroecosystems still need to be understood. The use of composts and sewage sludge from the organic fraction of municipal solid waste (OFMSW) treatment plants as soil amendments is likely to represent a major input of these debris. The present review provides insights into the current evidence of pollution from micro- and nano-particles of both fossil- and bio-origin in the OFMSW treatment, and aims at evaluating if the recycling of organic waste and its application as a soil fertilizer outweigh the risk of pollution in terrestrial environments. Huge unpredictability exists due to the limited numbers of data on their quantification in each source of possible solution. Indeed, the major hurdles arise from the difficult to quantify the micro-, especially the nano-, particles and subsequently assess the concentrations in the environments, as well as bioaccumulation risks, and toxic effects on organisms. Graphical Abstrac

PRNP genetic variability and molecular typing of natural goat scrapie isolates in a high number of infected flocks

One hundred and four scrapie positive and 77 negative goats from 34 Greek mixed flocks were analysed by prion protein gene sequencing and 17 caprine scrapie isolates from 11 flocks were submitted to molecular isolate typing. For the first time, the protective S146 variant was reported in Greece, while the protective K222 variant was detected in negative but also in five scrapie positive goats from heavily infected flocks. By immunoblotting six isolates, including two goat flockmates carrying the K222 variant, showed molecular features slightly different from all other Greek and Italian isolates co-analysed, possibly suggesting the presence of different scrapie strains in Greece

First Pandemic H1N1 Outbreak from a Pig Farm in Italy

The first outbreak of the pandemic H1N1 virus in a swine breeder farm in Italy in November 2009 was reported. Clinical signs observed in sows included fever, depression, anorexia and agalactia, while in piglets diarrhoea and weight loss. The morbidity in sows was approximately 30% and the accumulated mortality rate was similar with those usually reported in piggeries (<10%). Virus was isolated from piglets (A/Sw/It/290271/09) and the sequencing of the whole genome was then performed. Comparison with all (H1N1)v sequences available in GenBank shows A/Sw/It/290271/09 three unique amino-acid (aa) changes in PB2 (S405T), PB1 (K386R) and PA (K256Q), not yet associated to any well characterized phenotype markers of Influenza viruses. All eight aa at positions representing the so-called species specific swine-human signatures, found in both swine and in the pandemic H1N1v, are also present. The M2 protein displays the C55F and the PA protein the S409N substitutions, both corresponding to enhanced transmission phenotype markers. Phylogenetic analysis showed that the virus was genetically related to the pandemic H1N1 virus. In addition, serological samples were collected from 40 sows, of which 20 resulted positive to the pandemic H1N1 virus by HI test proving a virus circulation in the farm

SARS-CoV-2 complete genome sequencing from the Italian Campania region using a highly automated next generation sequencing system

Since the first complete genome sequencing of SARS-CoV-2 in December 2019, more than 550,000 genomes have been submitted into the GISAID database. Sequencing of the SARS-CoV-2 genome might allow identification of variants with increased contagiousness, different clinical patterns and/or different response to vaccines. A highly automated next generation sequencing (NGS)-based method might facilitate an active genomic surveillance of the virus