1,703 research outputs found

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

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    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

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    © 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

    Reliability-based economic model predictive control for generalized flow-based networks including actuators' health-aware capabilities

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    This paper proposes a reliability-based economic model predictive control (MPC) strategy for the management of generalized flow-based networks, integrating some ideas on network service reliability, dynamic safety stock planning, and degradation of equipment health. The proposed strategy is based on a single-layer economic optimisation problem with dynamic constraints, which includes two enhancements with respect to existing approaches. The first enhancement considers chance-constraint programming to compute an optimal inventory replenishment policy based on a desired risk acceptability level, leading to dynamically allocate safety stocks in flow-based networks to satisfy non-stationary flow demands. The second enhancement computes a smart distribution of the control effort and maximises actuators’ availability by estimating their degradation and reliability. The proposed approach is illustrated with an application of water transport networks using the Barcelona network as the considered case study.Peer ReviewedPostprint (author's final draft

    Remote Sensing and UAVs for the Geomorphological and Habitat Analysis in Ephemeral and Permanent Mediterranean Streams

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    Tesis por compendio[ES] Los ecosistemas riparios presentan una gran variabilidad, desde un punto de vista geomorfológico como hidrológico y ecológico, incluyendo las complejas interacciones que la morfología y la vegetación de ribera puede presentar. La vegetación se presenta como un factor físico muy influyente en los sistemas fluviales, con una relación directa en los procesos geomorfológicos que tienen lugar en los corredores fluviales. La detección, monitoreo y evaluación de los procesos que se desarrollan en el espacio ripario son clave a la hora de poder entender las funciones ecológicas y el desarrollo de dichos hábitats, y por tanto para tomar decisiones para su conservación y restauración. Según la distribución de especies y los rasgos de las plantas, las comunidades vegetales y su dinámica presentan distintas características en el ecosistema ripario, a las cuales los métodos de detección y monitoreo deben adaptarse. Los constantes cambios que sufren estos espacios a lo largo del tiempo se deben en gran parte a procesos físicos relacionados con las dinámicas de erosión y sedimentación, las variaciones de la trayectoria del cauce, variaciones en la distribución de especies y vegetación en el bosque de ribera, etc., pero también se deben al impacto antropogénico, que puede llegar a generar grandes desajustes en la dinámica ecológica de los ecosistemas en cuestión. Debido a las interacciones de diversos procesos y alteraciones antropogénicas, y las complejas dinámicas espacio-temporales, resulta necesario continuar desarrollando metodologías teóricas y prácticas para la monitorización y caracterización de estos ecosistemas. La teledetección, incluyendo el uso de drones, se presenta como una herramienta muy interesante y óptima para el mapeo y recogida de información en estos espacios naturales. Los beneficios que demuestran las aeronaves no tripuladas -UAV- incluyen las mejoras en la resolución espacial y temporal de los datos capturados, así como la cartografía de áreas extensas en poco tiempo, lo que los convierte en instrumentos clave en tareas de gestión y conservación de los espacios riparios. La necesidad de estudiar la dinámica geomorfológica que se produce en los cauces fluviales ha sido la principal motivación en los estudios que se presentan en esta tesis doctoral. Los capítulos 2 y 3 se basan en técnicas de captura de datos con láser escáner terrestre (TLS) y en el modelado de los datos obtenidos en vuelos fotogramétricos de UAV. Con ellos se han caracterizado los procesos que tienen lugar en una cierta área de estudio, un cauce efímero del sureste de la Península Ibérica, la Rambla de la Azohía (Murcia). Estos estudios también han permitido comparar el ajuste y precisión de los datos capturados a partir de dos técnicas distintas. Además, el interés en caracterizar los cauces fluviales con un flujo permanente ha motivado el estudio de la topografía sumergida en un tramo de río, segmentado por tipos de mesohábitat. Así pues, el capítulo 4 presenta un algoritmo y una herramienta de corrección para el efecto de la refracción en un tramo del rio Palancia (Castellón), para llevar a cabo la correcta representación de la morfología del lecho sumergido. A partir de la metodología planteada y el algoritmo desarrollado, es posible minimizar los efectos de distorsión debidos a la presencia del agua, para obtener la reconstrucción tridimensional del lecho a partir de imágenes tomadas con UAV. La construcción del modelo 3D se llevó a cabo mediante la técnica de Structure from Motion. Finalmente, y como elemento clave en la dinámica de los ecosistemas riparios, el capítulo 5 desarrolla una metodología para clasificar las fases de sucesión de la vegetación del bosque ripario. Dichas fases de sucesión se basan en la metodología del proyecto RIPFLOW, que también está implementada en el modelo dinámico CASiMiR-vegetation.[CA] Els ecosistemes riparis presenten una gran variabilitat, des d'un punt de vista geomorfològic com a hidrològic i ecològic, incloent les complexes interaccions que la morfologia i la vegetació de ribera pot presentar. La vegetació es presenta com un factor físic molt influent en els sistemes fluvials, amb una relació directa en els processos geomorfològics que tenen lloc en els corredors fluvials. La detecció, monitoratge i avaluació dels processos que es desenvolupen en l'espai ripari són clau a l'hora de poder entendre les funcions ecològiques i el desenvolupament d'aquests hàbitats, i per tant per a prendre decisions per a la seua conservació i restauració. Segons la distribució d'espècies i els trets de les plantes, les comunitats vegetals i la seua dinàmica presenten diferents característiques en l'ecosistema ripario, a les quals els mètodes de detecció i monitoratge han d'adaptar-se. Els constants canvis que pateixen aquests espais al llarg del temps es deuen en gran part a processos físics relacionats amb les dinàmiques d'erosió i sedimentació, les variacions de la trajectòria del llit, variacions en la distribució d'espècies i vegetació en el bosc de ribera, etc., però també es deuen a l'impacte antropogènic, que pot arribar a generar grans desajustaments en la dinàmica ecològica dels ecosistemes en qüestió. A causa de les interaccions de diversos processos i alteracions antropogèniques, i les complexes dinàmiques espaciotemporals, resulta necessari continuar desenvolupant metodologies teòriques i pràctiques per al monitoratge i caracterització d'aquests ecosistemes. La teledetecció, incloent l'ús de drons, es presenta com una eina molt interessant i òptima per al mapatge i recollida d'informació en aquests espais naturals. Els beneficis que demostren les aeronaus no tripulades -UAV- inclouen les millores en la resolució espacial i temporal de les dades capturades, així com la cartografia d'àrees extenses en poc temps, la qual cosa els converteix en instruments clau en tasques de gestió i conservació dels espais riparis. La necessitat d'estudiar la dinàmica geomorfològica que es produeix en els llits fluvials ha sigut la principal motivació en els estudis que es presenten en aquesta tesi doctoral. Els capítols 2 i 3 es basen en tècniques de captura de dades amb làser escàner terrestre (TLS) i en el modelatge de les dades obtingudes en vols fotogramètrics de UAV. Amb ells s'han caracteritzat els processos que tenen lloc en una certa àrea d'estudi, un llit efímer del sud-est de la Península Ibèrica, la Rambla de la Azohía (Múrcia). Aquests estudis també han permés comparar l'ajust i precisió de les dades capturades a partir de dues tècniques diferents. A més, l'interés a caracteritzar els llits fluvials amb un flux permanent ha motivat l'estudi de la topografia submergida en un tram de riu, segmentat per tipus de mesohábitat. Així doncs, el capítol 4 presenta un algorisme i una eina de correcció per a l'efecte de la refracció en un tram del va riure Palància (Castelló), per a dur a terme la correcta representació de la morfologia del llit submergit. A partir de la metodologia plantejada i l'algorisme desenvolupat, és possible minimitzar els efectes de distorsió deguts a la presència de l'aigua, per a obtindre la reconstrucció tridimensional del llit a partir d'imatges preses amb UAV. La construcció del model 3D es va dur a terme mitjançant la tècnica de Structure from Motion. Finalment, i com a element clau en la dinàmica dels ecosistemes riparis, el capítol 5 desenvolupa una metodologia per a classificar les fases de successió de la vegetació del bosc ripari. Aquestes fases de successió es basen en la metodologia del projecte RIPFLOW, que també està implementada en el model dinàmic CASiMiR-vegetation.[EN] Riparian ecosystems show great variability, from a geomorphological, hydrological and ecological point of view, including the complex interactions that riparian morphology and vegetation can present. Vegetation appears as a very influential physical factor in river systems, with a direct relationship in the geomorphological processes that take place in river corridors. The detection, monitoring and evaluation of the processes that take place in the riparian space are key when it comes to understanding the ecological functions and development of these habitats, and therefore for making decisions for their conservation and restoration. According to the distribution of species and plant traits, plant communities and their dynamics present different characteristics in the riparian ecosystem, to which detection and monitoring methods must be adapted. The constant changes that these spaces undergo over time are largely due to physical processes related to the dynamics of erosion and sedimentation, variations in the path of the channel, variations in the distribution of species and vegetation in the riparian forest, etc. These processes also are due to the anthropogenic impact, which can generate major imbalances in the ecological dynamics of the ecosystems in question. Due to the interactions of various anthropogenic processes and alterations, and the complex spatio-temporal dynamics, it is necessary to continue developing theoretical and practical methodologies for the monitoring and characterization of these ecosystems. Remote sensing, including the use of drones, is presented as a very interesting and optimal tool for mapping and collecting information in these natural spaces. The benefits demonstrated by unmanned aircraft -UAV- include improvements in the spatial and temporal resolution of the captured data, as well as the mapping of large areas in a short time, which makes them key instruments in the management and conservation tasks of riparian spaces. The need to study the geomorphological dynamics that occur in river channels has been the main motivation in the studies presented in this doctoral thesis. Chapters 2 and 3 are based on ground-based laser scanner (TLS) data capture techniques and modelling of UAV photogrammetric flight data. They have characterized the processes that take place in a certain study area, an ephemeral riverbed in the southeast of the Iberian Peninsula, the Rambla de la Azohía (Murcia). These studies have also made it possible to compare the fit and precision of the data captured from two different techniques. In addition, the interest in characterizing the fluvial channels with a permanent flow has motivated the study of the submerged topography in a stretch of river, segmented by types of mesohabitat. Thus, chapter 4 presents an algorithm and a correction tool for the effect of refraction in a stretch of the Palancia river (Castellón), to carry out the correct representation of the submerged bed morphology. From the proposed methodology and the developed algorithm, it is possible to minimize the distortion effects due to the presence of water, to obtain the three-dimensional reconstruction of the bed from images taken with UAVs. The construction of the 3D model was carried out using the Structure from Motion technique. Finally, and as a key element in the dynamics of riparian ecosystems, chapter 5 develops a methodology to classify the phases of succession of riparian forest vegetation. These succession phases are based on the RIPFLOW project methodology, which is also implemented in the dynamic CASiMiR-vegetation model.Agradezco a Francisca Segura y a Carles Sanchis por su ayuda y trabajo conjunto en el proyecto “Natural and anthropogenic changes in Mediterranean river drainage basins: historical impacts on rivers morphology, sedimentary flows and vegetation” financiado por el Ministerio de Economía y Competitividad (MINECO) (CGL2013-44917-R). Agradezco también a la Universidad de Murcia y la Universidad de Alicante así como al proyecto de investigación “Respuesta morfológica y sistémica al cambio climático en cauces efímeros mediterráneos: dinámica, resiliencia y propuestas de actuación” funded by ERDF/Spanish Ministry of Science, Innovation and Universities—State Research Agency/Project CGL2017-84625-C2-1-R (CCAMICEM); State Program for Research, Development and Innovation Focused on the Challenges of Society, del Ministerio de Economía y Competitividad (MINECO) y EU FEDER (Project TEC2017- 85244-C2-1-P) y de la Universidad de Alicante (vigrob-157 and GRE18-05).Puig Mengual, CA. (2021). Remote Sensing and UAVs for the Geomorphological and Habitat Analysis in Ephemeral and Permanent Mediterranean Streams [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/177643TESISCompendi

    Detection of replay attacks in CPSs using observer-based signature compensation

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    © 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 replay attack detection method that addresses the performance loss of watermarking-based approaches. The proposed method injects a sinusoidal signal that affects a subset, chosen at random, of the system outputs. The presence of the signal in each one of the outputs is estimated by means of independent observers and its effect is compensated in the control loop. When a system output is affected by a replay attack, the loss of feedback of the associated observer destabilizes the signal estimation, leading to an exponential increase of the estimation error up to a threshold, above which the estimated signal compensation in the control loop is disabled. This event triggers the detection of a replay attack over the output corresponding to the disrupted observer. The effectiveness of the method is demonstrated using results obtained with a quadruple-tank system simulator.Peer ReviewedPostprint (author's final draft

    Decentralised fault diagnosis of large-scale systems: Application to water transport networks

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    Trabajo presentado al 26th International Workshop on Principles of Diagnosis celebrado en Paris (Francia) del 31 de agosto al 3 de septiembre de 2015.In this paper, a decentralised fault diagnosis approach for large-scale systems is proposed. This approach is based on obtaining a set of local diagnosers using the analytical redundancy relation (ARRs) approach. The proposed approach starts with obtaining the set of ARRs of the system yielding into an equivalent graph. From that graph, the graph partitioning problem is solved obtaining a set of ARRs for each local diagnoser. Finally, a decentralised fault diagnosis strategy is proposed and applied over the resultant set of partitions and ARRs. In order to illustrate the application of the proposed approach, a case study based on the Barcelona drinking water network (DWN) is used.This work has been partially supported by the EFFINET grant FP7-ICT-2012-318556 of the European Commission and the Spanish project ECOCIS (Ref. DPI2013-48243-C2-1-R).Peer Reviewe

    Decentralised fault diagnosis of large-scale systems: Application to water transport networks

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    Trabajo presentado al 26th International Workshop on Principles of Diagnosis celebrado en Paris (Francia) del 31 de agosto al 3 de septiembre de 2015.In this paper, a decentralised fault diagnosis approach for large-scale systems is proposed. This approach is based on obtaining a set of local diagnosers using the analytical redundancy relation (ARRs) approach. The proposed approach starts with obtaining the set of ARRs of the system yielding into an equivalent graph. From that graph, the graph partitioning problem is solved obtaining a set of ARRs for each local diagnoser. Finally, a decentralised fault diagnosis strategy is proposed and applied over the resultant set of partitions and ARRs. In order to illustrate the application of the proposed approach, a case study based on the Barcelona drinking water network (DWN) is used.This work has been partially supported by the EFFINET grant FP7-ICT-2012-318556 of the European Commission and the Spanish project ECOCIS (Ref. DPI2013-48243-C2-1-R).Peer Reviewe

    Reliable fault-tolerant model predictive control of drinking water transport networks

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    This paper proposes a reliable fault-tolerant model predictive control applied to drinking water transport networks. After a fault has occurred, the predictive controller should be redesigned to cope with the fault effect. Before starting to apply the fault-tolerant control strategy, it should be evaluated whether the predictive controller will be able to continue operating after the fault appearance. This is done by means of a structural analysis to determine loss of controllability after the fault complemented with feasibility analysis of the optimization problem related to the predictive controller design, so as to consider the fault effect in actuator constraints. Moreover, by evaluating the admissibility of the different actuator-fault configurations, critical actuators regarding fault tolerance can be identified considering structural, feasibility, performance and reliability analyses. On the other hand, the proposed approach allows a degradation analysis of the system to be performed. As a result of these analyses, the predictive controller design can be modified by adapting constraints such that the best achievable performance with some pre-established level of reliability will be achieved. The proposed approach is tested on the Barcelona drinking water transport network.Postprint (author's final draft

    Probability-guaranteed set-membership state estimation for polynomially uncertain linear time-invariant systems

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    2018 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 worksConventional deterministic set-membership (SM) estimation is limited to unknown-but-bounded uncertainties. In order to exploit distributional information of probabilistic uncertainties, a probability-guaranteed SM state estimation approach is proposed for uncertain linear time-invariant systems. This approach takes into account polynomial dependence on probabilistic uncertain parameters as well as additive stochastic noises. The purpose is to compute, at each time instant, a bounded set that contains the actual state with a guaranteed probability. The proposed approach relies on the extended form of an observer representation over a sliding window. For the offline observer synthesis, a polynomial-chaos-based method is proposed to minimize the averaged H2 estimation performance with respect to probabilistic uncertain parameters. It explicitly accounts for the polynomial uncertainty structure, whilst most literature relies on conservative affine or polytopic overbounding. Online state estimation restructures the extended observer form, and constructs a Gaussian mixture model to approximate the state distribution. This enables computationally efficient ellipsoidal calculus to derive SM estimates with a predefined confidence level. The proposed approach preserves time invariance of the uncertain parameters and fully exploits the polynomial uncertainty structure, to achieve tighter SM bounds. This improvement is illustrated by a numerical example with a comparison to a deterministic zonotopic method.Peer ReviewedPostprint (author's final draft

    Sensor-fault tolerance using robust MPC with set-based state estimation and active fault isolation

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    In this paper, a sensor fault-tolerant control (FTC) scheme using robust model predictive control (MPC) and set theoretic fault detection and isolation (FDI) is proposed. The MPC controller is used to both robustly control the plant and actively guarantee fault isolation (FI). In this scheme, fault detection (FD) is passive by interval observers, while fault isolation (FI) is active by MPC. The advantage of the proposed approach consists in using MPC to actively decouple the effect of sensor faults on the outputs such that one output component only corresponds to one sensor fault in terms of FI, which can utilize the feature of sensor faults for FI. A numerical example is used to illustrate the effectiveness of the proposed scheme.Postprint (author’s final draft
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