Scalable model for industrial coffee roasting chamber

Abstract The temperature profile of the coffee beans during the roasting phase determines the colour, aroma and flavour of the coffee. In order to reproduce these desired characteristics, the control of the coffee beans temperature has a key role in the roasting process. A proper model of the plant is required to design an intelligent control. Recently, several physical models that share the main physical equations have been proposed, but they have physical parameters specific of each process. In such scenario, each plant requires an ad hoc identification of the model parameters. This work proposes a model of the roasting chamber that can be used on plants of different sizes by scaling only geometrical parameters directly measurable on the roasting plant. The proposed model was identified on a 120 kg plant and then applied to a 360 kg one. The obtained results show in both cases similar accuracy (FIT = 75.49%, MPE=4.66%)

Towards a Model-Based Field-Frequency Lock for Fast-Field Cycling NMR

Fast-field cycling nuclear magnetic resonance (FFC NMR) relaxometry allows to investigate molecular dynamics of complex materials. FFC relaxometry experiments require the magnetic field to reach different values in few milliseconds and field oscillations to stay within few ppms during signal acquisition. Such specifications require the introduction of a novel field-frequency lock (FFL) system. In fact, control schemes based only on current feedback may not guarantee field stability, while standard FFLs are designed to handle very slow field fluctuations, such as thermal derives, and may be ineffective in rejecting faster ones. The aim of this work is then to propose a methodology for the synthesis of a regulator that guarantees rejection of field fluctuations and short settling time. Experimental trials are performed for both model validation and evaluation of the closed-loop performances. Relaxometry experiments are performed to verify the improvement obtained with the new FFL. The results highlight the reliability of the model and the effectiveness of the overall approach

Improvement of manufacturing technologies through a modelling approach: an air-steam sterilization case-study

Abstract A milestone of Industry 4.0 is the improvement of the design procedures requiring models of complex processes. Models can be used to simulate the process, being accurate even if complex, and to predict process behaviour for control action, requiring simplicity and stability. In the last years, machine learning approaches came up alongside of the standard identification techniques for prediction purposes. In this work we propose two models of an industrial autoclave to describe the evolution of temperature and pressure. The first model (PhM) involves a physical structure with data-driven adaptation of the parameters, the second one is a Long Short-Term Memory network (LSTM), trained ensuring Input-to-State stability. Both models obtained good performance: FIT of 94.26% (91.55%) for the temperature (pressure) with PhM; 84.59% (78.31 %) for the temperature (pressure) with the LSTM. Future developments involve the synthesis of an MPC based on the LSTM to be tested in simulation via PhM

First Use of Model Predictive Control in Outpatient Wearable Artificial Pancreas

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Day and night closed-loop control in adults with type 1 diabetes: a comparison of two closed-loop algorithms driving continuous subcutaneous insulin infusion versus patient self-management.

OBJECTIVE: To compare two validated closed-loop (CL) algorithms versus patient self-control with CSII in terms of glycemic control. RESEARCH DESIGN AND METHODS: This study was a multicenter, randomized, three-way crossover, open-label trial in 48 patients with type 1 diabetes mellitus for at least 6 months, treated with continuous subcutaneous insulin infusion. Blood glucose was controlled for 23 h by the algorithm of the Universities of Pavia and Padova with a Safety Supervision Module developed at the Universities of Virginia and California at Santa Barbara (international artificial pancreas [iAP]), by the algorithm of University of Cambridge (CAM), or by patients themselves in open loop (OL) during three hospital admissions including meals and exercise. The main analysis was on an intention-to-treat basis. Main outcome measures included time spent in target (glucose levels between 3.9 and 8.0 mmol/L or between 3.9 and 10.0 mmol/L after meals). RESULTS: Time spent in the target range was similar in CL and OL: 62.6% for OL, 59.2% for iAP, and 58.3% for CAM. While mean glucose level was significantly lower in OL (7.19, 8.15, and 8.26 mmol/L, respectively) (overall P = 0.001), percentage of time spent in hypoglycemia (<3.9 mmol/L) was almost threefold reduced during CL (6.4%, 2.1%, and 2.0%) (overall P = 0.001) with less time ≤2.8 mmol/L (overall P = 0.038). There were no significant differences in outcomes between algorithms. CONCLUSIONS: Both CAM and iAP algorithms provide safe glycemic control

Role of the photoprotection mechanisms during the acclimation of Physcomitrium patens under different light conditions

openLa fotosintesi ossigenica è un processo attraverso il quale gli organismi fotoautotrofi, acquatici e terrestri, sfruttano l’energia solare per produrre energia chimica, scambiando con l’atmosfera molecole di ossigeno ed anidride carbonica. Le condizioni ambientali a cui un organismo è esposto in natura possono variare, influenzandone numerosi processi fisiologici. La fotosintesi deve essere finemente regolata per rispondere alle naturali variazioni ambientali, come ad esempio variazioni di intensità luminosa che possono causare la produzione di specie reattive dell’ossigeno, dannose per l’apparato fotosintetico. Gli organismi fotosintetici nel corso dell’evoluzione hanno sviluppato differenti meccanismi fotoprotettivi. In questo progetto di tesi sono stati studiati il non-photochemical-quenching ed i trasporti elettronici alternativi, due meccanismi fondamentali per proteggere i centri di reazione dell’apparato fotosintetico. A questo scopo, sono stati effettuati esperimenti di fisiologia e biochimica su piante wild-type (WT) e mutanti dell’organismo modello Physcomitrium patens. In particolare, è stata analizzata la composizione e l’efficienza del loro apparato fotosintetico durante i processi di acclimatazione a tre diverse condizioni di luce: luce di controllo, alta luce e luce fluttuante. L’analisi dei risultati di questi esperimenti e le informazioni fornite da studi antecedenti mostrano un rimodellamento dell’apparato fotosintetico, e permettono di approfondire il ruolo e l’importanza delle componenti dei meccanismi di fotoprotezione durante i processi di acclimatazione alle diverse condizioni di luce studiate

Artificial pancreas: from control-to-range to control-to-target

In the last decade, control algorithms designed for Artificial Pancreas (AP) systems were characterized by significant progresses. In particular, the Control-to-Range Model Predictive Control (MPC) showed its effectiveness and safety in several real life studies. Recent studies on model individualization and the enhanced quality of glucose sensors further improved the efficacy of MPC, thus allowing moving from a Control-to-Range to a Control-to-Target approach. In this study, an integral action in the MPC approach (IMPC) is proposed. This ensures beneficial effects in terms of regulation to the target in presence of disturbances such as delays, pump limitation and model uncertainties. The integral action is even more important when model individualization is performed since, during the identification phase, it allows to focus on the identification of the dynamical part of the model rather than to the static gain. The patient models considered in this contribution have been identified through a constrained optimization approach. A procedure for tuning the IMPC aggressiveness by considering both the glucose control performance and the integral of the error with respect to the target is described. Finally, in silico experiments are presented to assess the effectiveness of the proposed IMPC