Health-aware predictive control schemes based on industrial processes

Aplicat embargament des de la data de defensa fins el dia 30 de desembre de 2021The research is motivated by real applications, such as pasteurization plant, water networks and autonomous system, which each of them require a specific control system to provide proper management able to take into account their particular features and operating limits in presence of uncertainties related to their operation and failures from component breakdowns. According to that most of the real systems have nonlinear behaviors, it can be approximated them by polytopic linear uncertain models such as Linear Parameter Varying (LPV) and Takagi-Sugeno (TS) models. Therefore, a new economic Model Predictive Control (MPC) approach based on LPV/TS models is proposed and the stability of the proposed approach is certified by using a region constraint on the terminal state. Besides, the MPC-LPV strategy is extended based on the system with varying delays affecting states and inputs. The control approach allows the controller to accommodate the scheduling parameters and delay change. By computing the prediction of the state variables and delay along a prediction time horizon, the system model can be modified according to the evaluation of the estimated state and delay at each time instant. To increase the system reliability, anticipate the appearance of faults and reduce the operational costs, actuator health monitoring should be considered. Regarding several types of system failures, different strategies are studied for obtaining system failures. First, the damage is assessed with the rainflow-counting algorithm that allows estimating the component’s fatigue and control objective is modified by adding an extra criterion that takes into account the accumulated damage. Besides, two different health-aware economic predictive control strategies that aim to minimize the damage of components are presented. Then, economic health-aware MPC controller is developed to compute the components and system reliability in the MPC model using an LPV modeling approach and maximizes the availability of the system by estimating system reliability. Additionally, another improvement considers chance-constraint programming to compute an optimal list replenishment policy based on a desired risk acceptability level, managing to dynamically designate safety stocks in flowbased networks to satisfy non-stationary flow demands. Finally, an innovative health-aware control approach for autonomous racing vehicles to simultaneously control it to the driving limits and to follow the desired path based on maximization of the battery RUL. The proposed approach is formulated as an optimal on-line robust LMI based MPC driven from Lyapunov stability and controller gain synthesis solved by LPV-LQR problem in LMI formulation with integral action for tracking the trajectory.Esta tesis pretende proporcionar contribuciones teóricas y prácticas sobre seguridad y control de sistemas industriales, especialmente en la forma maten ática de sistemas inciertos. La investigación está motivada por aplicaciones reales, como la planta de pasteurización, las redes de agua y el sistema autónomo, cada uno de los cuales requiere un sistema de control específico para proporcionar una gestión adecuada capaz de tener en cuenta sus características particulares y limites o de operación en presencia de incertidumbres relacionadas con su operación y fallas de averías de componentes. De acuerdo con que la mayoría de los sistemas reales tienen comportamientos no lineales, puede aproximarse a ellos mediante modelos inciertos lineales politopicos como los modelos de Lineal Variación de Parámetros (LPV) y Takagi-Sugeno (TS). Por lo tanto, se propone un nuevo enfoque de Control Predictivo del Modelo (MPC) económico basado en modelos LPV/TS y la estabilidad del enfoque propuesto se certifica mediante el uso de una restricción de región en el estado terminal. Además, la estrategia MPC-LPV se extiende en función del sistema con diferentes demoras que afectan los estados y las entradas. El enfoque de control permite al controlador acomodar los parámetros de programación y retrasar el cambio. Al calcular la predicción de las variables de estado y el retraso a lo largo de un horizonte de tiempo de predicción, el modelo del sistema se puede modificar de acuerdo con la evaluación del estado estimado y el retraso en cada instante de tiempo. Para aumentar la confiabilidad del sistema, anticipar la aparición de fallas y reducir los costos operativos, se debe considerar el monitoreo del estado del actuador. Con respecto a varios tipos de fallas del sistema, se estudian diferentes estrategias para obtener fallas del sistema. Primero, el daño se evalúa con el algoritmo de conteo de flujo de lluvia que permite estimar la fatiga del componente y el objetivo de control se modifica agregando un criterio adicional que tiene en cuenta el daño acumulado. Además, se presentan dos estrategias diferentes de control predictivo económico que tienen en cuenta la salud y tienen como objetivo minimizar el daño de los componentes. Luego, se desarrolla un controlador MPC económico con conciencia de salud para calcular los componentes y la confiabilidad del sistema en el modelo MPC utilizando un enfoque de modelado LPV y maximiza la disponibilidad del sistema mediante la estimación de la confiabilidad del sistema. Además, otra mejora considera la programación de restricción de posibilidades para calcular una política ´optima de reposición de listas basada en un nivel de aceptabilidad de riesgo deseado, logrando designar dinámicamente existencias de seguridad en redes basadas en flujo para satisfacer demandas de flujo no estacionarias. Finalmente, un enfoque innovador de control consciente de la salud para vehículos de carreras autónomos para controlarlo simultáneamente hasta los límites de conducción y seguir el camino deseado basado en la maximización de la bacteria RUL. El diseño del control se divide en dos capas con diferentes escalas de tiempo, planificador de ruta y controlador. El enfoque propuesto está formulado como un MPC robusto en línea optimo basado en LMI impulsado por la estabilidad de Lyapunov y la síntesis de ganancia del controlador resuelta por el problema LPV-LQR en la formulación de LMI con acción integral para el seguimiento de la trayectoria.Postprint (published version

Single-Server Single-Message Online Private Information Retrieval with Side Information

In many practical settings, the user needs to retrieve information from a server in a periodic manner, over multiple rounds of communication. In this paper, we discuss the setting in which this information needs to be retrieved privately, such that the identity of all the information retrieved until the current round is protected. This setting can occur in practical situations in which the user needs to retrieve items from the server or a periodic basis, such that the privacy needs to be guaranteed for all the items been retrieved until the current round. We refer to this setting as an \emph{online private information retrieval} as the user does not know the identities of the future items that need to be retrieved from the server. Following the previous line of work by Kadhe \emph{et al.}~we assume that the user knows a random subset of $M$ messages in the database as a side information which are unknown to the server. Focusing on scalar-linear settings, we characterize the \emph{per-round capacity}, i.e., the maximum achievable download rate at each round, and present a coding scheme that achieves this capacity. The key idea of our scheme is to utilize the data downloaded during the current round as a side information for the subsequent rounds. We show for the setting with $K$ messages stored at the server, the per-round capacity of the scalar-linear setting is $C_1= ({M+1})/{K}$ for round $i=1$ and ${C_i= {(2^{i-1}(M+1))}/{KM}}$ for round $i\geq2$, provided that ${K}/({M+1})$ is a power of $2$.Comment: 7 pages; This work is a long version of an article submitted to IEEE for possible publicatio

Output-feedback model predictive control of a pasteurization pilot plant based on an LPV model

In order to optimize the trade-off between components life and energy consumption, the integration of a system health management and control modules is required. This paper proposes the integration of model predictive control (MPC) with a fatigue estimation approach that minimizes the damage of the components of a pasteurization plant. The fatigue estimation is assessed with the rainflow counting algorithm. Using data from this algorithm, a simplified model that characterizes the health of the system is developed and integrated with MPC. The MPC controller objective is modified by adding an extra criterion that takes into account the accumulated damage. But, a steady-state offset is created by adding this extra criterion. Finally, by including an integral action in the MPC controller, the steady-state error for regulation purpose is eliminated. The proposed control scheme is validated in simulation using a simulator of a utility-scale pasteurization plant.Peer ReviewedPostprint (author's final draft

Model predictive control based on LPV models with parameter-varying delays

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.This paper presents a Model Predictive Control (MPC) strategy based on Linear Parameter Varying (LPV) models with varying delays affecting states and inputs. The proposed control approach allows the controller to accommodate the scheduling parameters and delay change. By computing the prediction of the state variables and delay along a prediction time horizon, the system model can be modified according to the evaluation of the estimated state and delay at each time instant. Moreover, the solution of the optimization problem associated with the MPC design is achieved by solving a series of Quadratic Programming (QP) problem at each time instant. This iterative approach reduces the computational burden compared to the solution of a non-linear optimization problem. A pasteurization plant system is used as a case study to demonstrate the effectiveness of the proposed approach.Peer ReviewedPostprint (author's final draft

Economic health-aware LPV-MPC based on system reliability assessment for water transport network

This paper proposes a health-aware control approach for drinking water transport networks. This approach is based on an economic model predictive control (MPC) that considers an additional goal with the aim of extending the components and system reliability. The components and system reliability are incorporated into the MPC model using a Linear Parameter Varying (LPV) modeling approach. The MPC controller uses additionally an economic objective function that determines the optimal filling/emptying sequence of the tanks considering that electricity price varies between day and night and that the demand also follows a 24-h repetitive pattern. The proposed LPV-MPC control approach allows considering the model nonlinearities by embedding them in the parameters. The values of these varying parameters are updated at each iteration taking into account the new values of the scheduling variables. In this way, the optimization problem associated with the MPC problem is solved by means of Quadratic Programming (QP) to avoid the use of nonlinear programming. This iterative approach reduces the computational load compared to the solution of a nonlinear optimization problem. A case study based on the Barcelona water transport network is used for assessing the proposed approach performance.Peer ReviewedPostprint (published version

Enzymatic in-situ generation of H2O2 for decolorization of Acid Blue 113 by fenton process

Decolorization of Acid Blue 113 in an aqueous medium by bio-Fenton process has been investigated in this research. Enzymatic oxidation of glucose was performed to in-situ generation of H2O2 which was employed to react with Fe2+ for producing hydroxyl radicals. The effect of various parameters include concentrations of 113, glucose, and FeSO4, activity of glucose oxidase (GOx) and the effect of pH were assessed. The highest decolorization of AB 113 were achieved at Fe2+ concentration of 0.2 mmol/L, pH =4.0, glucose concentration of 0.018 mol/L, and glucose oxidase activity of 2500 U/L in the constant temperature (23 ±0.1ºC) and constant shaking rate (160 r/min), while the concentration of 113 was 40 mg/L. In these conditions, 113 decolorization efficiency after 60 min was obtained about 95%

Electrochemical detection of carbidopa using a ferrocene-modified carbon nanotube paste electrode

A chemically modified carbon paste electrode (MCPE) containing ferrocene (FC) and carbon nanotubes (CNT) was constructed. The electrochemical behavior and stability of the MCPE were investigated by cyclic voltammetry. The electrocatalytic activity of the MCPE was investigated and it showed good characteristics for the oxidation of carbidopa (CD) in phosphate buffer solution (PBS). A linear concentration range of 5 to 600 μM CD, with a detection limit of 3.6±0.17 μM CD, was obtained. The diffusion coefficient of CD and the transfer coefficient () were also determined. The MCPE showed good reproducibility, remarkable long-term stability and especially good surface renewability by simple mechanical polishing. The results showed that this electrode could be used as an electrochemical sensor for the determination of CD in real samples, such as urine samples

Hematological profile of high-fat diet-induced murine model of metabolic syndrome

The present study was conducted to address how high-fat diet (HFD)-induced metabolic syndrome (MetS) makes alterations to murine hematological profile. Fasting plasma glucose (FPG) of 80 male NMRI mice was measured and mice with FPG falling within the range of 80-160 were included as healthy or non-diabetic mice. Afterward, mice in the selected population were categorized into two separate main groups including normal control (NC, n = 32) and HFD -induced MetS (n = 32) having received a normal chow diet and a HFD, respectively, and 8 mice sacrificed for a biochemical and hematological profile at weeks 2, 4, 8, and 16. Lipid profiling, peripheral blood analysis, and bone marrow (BM) interpretation were considered endpoints. Results were analyzed in a separated time panel using a non-paired t-test at the significance level of p˂0.05. Gained weight at week 16, increased accumulation of abdominal fat at week 8, raised FPG at weeks 2 and 8 and increased high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol (LDL-C) at week 8 were observed in MetS compared to NC group confirming successful translation of a murine model of MetS. Hematologically, no change in serum ferritin, serum iron, hematocrit, platelet count, and differential leukocyte count (DLC) was observed in MetS compared to NC group. By contrast, MetS group showed raised absolute basophil count compared to NC group at week 8. Strikingly, MetS group showed a downward trend in hemoglobin concentration compared to NC group. However, this downward trend was only significant in the 2nd week. In addition, mean corpuscular volume and mean corpuscular hemoglobin in MetS group dropped at week 8 compared to NC group. Furthermore, MetS group showed decreased erythroid lineage cells including proerythroblast, polychromatophilic erythroblast, and orthochromatophilic erythroblast proposing the presence of anemia in the murine model of MetS. Histopathologic evaluation of BM showed decreased cellularity and increased infiltration of lipids in MetS compared to NC group. Additionally, MetS group showed the reduced number of basophils, eosinophils, and monocytes in BM during the first 8 weeks of the study. However, in the 16th week, lymphocytes were the only decreased cells, and the absolute count of neutrophils, basophils, and monocytes was raised possibly towards higher production of inflammatory cells in MetS group. It is worth noting that change in the number of plasma cells was shown to be highly variable throughout study. Following the successful development of a HFD-induced murine model of MetS, histological examination of BM in MetS mice showed reduced cellularity and enhanced accumulation of adipose tissue. Additionally, BM analysis indicated significantly decreased basophils, eosinophils, and monocytes at early weeks of receiving diet; however, increased neutrophils, basophils, and monocytes were observed at the end of the study which can primarily be considered reactive leukocytosis due to MetS-mediated inflammatory response. Furthermore, enumeration of erythroid lineage cells in BM demonstrated a significant decrease in proerythroblasts, polychromatophilic erythroblasts, and orthochromatophilic erythroblasts, highly suggestive of anemia

On the Reidemeister spectrum of an Abelian group

The Reidemeister number of an automorphism ϕ of an Abelian group G is calculated by determining the cardinality of the quotient group G/(ϕ − 1G)(G), and the Reidemeister spectrum of G is precisely the set of Reidemeister numbers of the automorphisms of G. In this work we determine the full spectrum of several types of group, paying particular attention to groups of torsion-free rank 1 and to direct sums and products. We show how to make use of strong realization results for Abelian groups to exhibit many groups where the Reidemeister number is infinite for all automorphisms; such groups then possess the so-called R∞-property.We also answer a query of Dekimpe and Gonçalves by exhibiting an Abelian 2-group which has the R∞-property

Health-aware model predictive control including fault-tolerant capabilities for drinking water transport networks

© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting /republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksThis paper presents a health-aware Model Predictive Control (MPC) including fault-tolerant capabilities for drinking water transport networks. When a fault has occurred, the predictive controller must be redesigned to deal with the fault. This is done by considering the system reliability that is incorporated into the MPC model. The inclusion of components and system reliability in the MPC model is done through the Linear Parameter Varying (LPV) modelling approach with the aim of maximizing the availability of the system by considering system reliability. As a result, the MPC design is modified by considering the reliability model such that additionally to achieve the best achievable performance after the fault, the controller try to preserve the remaining useful life. The solution to the optimization problem related to the MPC problem is achieved by solving a series of Quadratic Programming (QP) problems thanks to the proposed LPV formulation. The proposed approach is applied to a part of a real drinking water transport network of Barcelona for demonstrating the performance of the method.Peer ReviewedPostprint (author's final draft