Uncertainty effect on leak localisation in a DMA

The leak localisation methodologies based on data and models are affected by both uncertainties in the model and in the measurements. This uncertainty should be quantified so that its effect on the localisation methods performance can be estimated. In this paper, a model-based leak localisation methodology is applied to a real District Metered Area using synthetic data. In the generation process of the data, uncertainty in demands is taken into account. This uncertainty was estimated so that it can justify the uncertainty observed in the real measurements. The leak localisation methodology consists, first, in generating the set of possible measurements, obtained by Monte Carlo Simulation under a certain leak assumption and considering uncertainty, and second, in falsifying sets of nodes using the correlation with a leak residual model in order to signal a set of possible leaky nodes. The assessment is done by means of generating the confusion matrix with a Monte Carlo approach.Peer ReviewedPostprint (author's final draft

The relative role of the intellectual and moral virtues in sustainable management decisions: The case of practical wisdom and justice

We analyze the status of virtues in management by going in some depth into the two main virtues, justice and practical wisdom. We next study how ethics requires that all virtues should be present under the ideal concept of a ‘unity of virtues’ for a completely wise person and discuss the practical limitations of this concept. Then, we draw a framework for decision making depending on whether the decision maker possesses justice and practical wisdom or lacks one of them and then discuss which one is better to have. We conclude that justice is more important, as it is about setting objectives and prioritizing, whereas practical wisdom is about attaining these objectives, once listed, in a rationally wise and contextual way. Hence, we conclude that objectives (justice) must come first, because this makes it more likely that, in the end, practical wisdom is developed, and thus we end up having the two virtue

Trust under bounded rationality: Competence, value systems, unselfishness and the development of virtue

Purpose: This paper analyses the foundations of trust in a context of bounded rationality to reach the conclusion that non-calculative trust is meaningful essentially because of bounded rationality, specifying what aspects of bounded rationality are relevant for this to happen. Design/methodology: Building on previous theoretical work we conceptually develop the reasoning involved to arrive deductively that bounded rationality provides a rationale for the concept of trust that goes beyond a calculative notion. Findings: We show that there are four reasons for trust to exist and that people assess probabilities to each in order to determine whether to trust a recipient, depending on each of the four. We also add to previous work and show how bounded rationality provides additional arguments to show how competence, value systems and unselfishness are necessary to underpin trust. We provide additional foundations to their three factors, focused on bounded rationality. We add the development of virtue as a crucial fourth aspect, which supports the argument that trust can be reinforced between people and developed through time. Originality/value: The concept of trust has been analyzed empirically, but it lacks some theoretical foundations to show under which assumptions trust is a requirement that goes beyond mere calculations, and can be developed or not through time. We also introduce how the concept of virtue has a major role in trust development

Impedance control of a planar quadrotor with an extended Kalman filter external wrench estimator

In this work we deal with the non-linear control of aerial vehicles under external disturbances. We develop a non-linear velocity controller able to accommodate estimations of the external disturbing forces and moments. To estimate the external actions and at the same time provide improvements on the state estimation we make use of the EKF approach. Finally, we present simulations comparing close loop performance of a system with the proposed methodology implemented against close loop performance of the same controller but without the estimation of the external forces.Postprint (published version

Backstepping with virtual filtered command: Application to a 2D autonomous Vehicle

Through this work a deep understanding of the backstepping control technique is sought when applied over non-affine systems. It is shown that in this case appears the necessity to bound the value of internal states and that a modification over standard backstepping is mandatory. The principal goal of this study is to evaluate the effects of finite frequency filters, and the effects of saturation affecting intermediate states and control actions, in the tracking performance when using the command filtered backstepping. Some relations that bind the controller gains to maintain performance appear naturally. Finally simulations over a 2D steering robot model are given to illustrate the found results.Peer ReviewedPostprint (author’s final draft

Ensemble model-based method for time series sensors’ data validation and imputation applied to a real waste water treatment plant

Intelligent Decision Support Systems (IDSSs) integrate different Artificial Intelligence (AI) techniques with the aim of taking or supporting human-like decisions. To this end, these techniques are based on the available data from the target process. This implies that invalid or missing data could trigger incorrect decisions and therefore, undesirable situations in the supervised process. This is even more important in environmental systems, which incorrect malfunction could jeopardise related ecosystems. In data-driven applications such as IDSS, data quality is a basal problem that should be addressed for the sake of the overall systems’ performance. In this paper, a data validation and imputation methodology for time-series is presented. This methodology is integrated in an IDSS software tool which generates suitable control set-points to control the process. The data validation and imputation approach presented here is focused on the imputation step, and it is based on an ensemble of different prediction models obtained for the sensors involved in the process. A Case-Based Reasoning (CBR) approach is used for data imputation, i.e., similar past situations to the current one can propose new values for the missing ones. The CBR model is complemented with other prediction models such as Auto Regressive (AR) models or Artificial Neural Network (ANN) models. Then, the different obtained predictions are ensembled to obtain a better prediction performance than the obtained by each individual prediction model separately. Furthermore, the use of a meta-prediction model, trained using the predictions of all individual models as inputs, is proposed and compared with other ensemble methods to validate its performance. Finally, this approach is illustrated in a real Waste Water Treatment Plant (WWTP) case study using one of the most relevant measures for the correct operation of the WWTPs IDSS, i.e., the ammonia sensor, and considering real faults, showing promising results with improved performance when using the ensemble approach presented here compared against the prediction obtained by each individual model separately.The authors acknowledge the partial support of this work by the Industrial Doctorate Programme (2017DI-006) and the Research Consolidated Groups/Centres Grant (2017 SGR 574) from the Catalan Agency of University and Research Grants Management (AGAUR), from Catalan Government.Peer ReviewedPostprint (published version

Parameter uncertainty modelling in water distribution network models

The use of water distribution network (WDN) models is an extended practice [13]. Confidence on decisions taken upon such models depends highly on their accuracy [11]. The parameters uncertainty has to be defined in order to include it in the model. Some of the parameters in a network (e.g. pipes lengths and diameters) can be easily measured and their uncertainty can be calculated on a statistical basis [4]. Demands cannot be measured directly and they have to be estimated using other measurements [10][8]. The uncertainty in the measurements used for that estimation is propagated to the parameters [1]. Besides, demands have their own stochastic nature that induces uncertainty. This paper describes how the pressure measurements are used to infer the uncertainty model in demands for a real network. The real data are treated in order to avoid the effect of boundary conditions. An uncertainty model for demands is calculated to justify the observed behaviour of the measurements. Montecarlo simulations are used for the validation.Peer ReviewedPostprint (published version

An interoperable workflow-based framework for the automation of building intelligent process control systems

One of the major problems to design and implement a control/supervision system for a process lies in the need to establish an ad-hoc system for each process installation. On the other side, an open challenge related to the deployment of Intelligent Decision Support Systems (IDSSs) is the interoperability of the different methods used, in order to allow interaction and reuse of different data mining methods and the use of methods based on a model or an expert. Thus, this paper proposes the use of visual workflows, to enable the automation of the design task and the implementation of Intelligent Process Control Systems (IPCSs). The framework will allow the user to specify the design and control of a concrete process as well as the required data-driven and expert models using a graphical workflow environment. The framework is based on a three-layer architecture: first, a comprehensive data science flow description layer (dataflow layer) to produce/discover data-driven models from process data; second, a flowchart of the different components of the process (process-design flow layer) to obtain a simulation model from the design. Finally, the on-line IPCS (process control workflow layer), where the different data-driven models, expert-based models and intelligent reasoning methods interoperate to control and supervise the process. Thus, the resulting system can automatically generate both simulation models of the process and programming code to control and supervise the process, using workflows designed for each particular installation. The case study is focused on the supervision of a Wastewater Treatment Plant (WWTP) located in the Barcelona region.The authors acknowledge the partial support of this work by the Industrial Doctorate Programme (2017-DI-006) and the Research Consolidated Groups/Centres Grant (2017 SGR 574) from the Catalan Agency of University and Research Grants Management (AGAUR), from Catalan Government.Peer ReviewedPostprint (author's final draft

Herramienta basada en minería de datos para la automatización del diseño de sistemas inteligentes en EDAR

Uno de los principales problemas para diseñar e implementar un sistema de supervisión y control para un proceso radica en la necesidad de establecer una solución ad-hoc para cada instalación. La interoperabilidad de los diferentes métodos utilizados para este fin es uno de los desafíos actuales relacionados con el desarrollo de Sistemas Inteligentes de Soporte a la Toma de Decisiones (IDSS), con el objetivo de garantizar la interacción y reutilización de los diferentes métodos basados en modelos, en conocimiento experto o en minería de datos. En este trabajo se propone el uso de entornos y flujos de trabajo visuales para permitir la automatización del diseño e implementación de Sistemas Inteligentes de Control de Procesos (IPCS). Estos entornos permitirán al usuario especificar las características de un proceso concreto, así como los modelos requeridos —basados en datos y en conocimiento experto—, utilizando un entorno de desarrollo visual, con la finalidad de implementar la estrategia de control más adecuada a cada instalación particular. La herramienta propuesta se basa en una arquitectura de tres capas: la primera se corresponde a un proceso offline de generación de modelos e.g. data-driven a partir de datos históricos del sistema, con la finalidad de supervisarlo y controlarlo. La segunda se corresponde a un diagrama de flujo del sistema, incluyendo los distintos subprocesos que lo configuran y las señales correspondientes. Finalmente, la tercera capa es el núcleo de la aplicación, en la que se utilizan los modelos obtenidos por parte de los diferentes métodos de razonamiento inteligente, usados para supervisar el sistema, así como para generar las consignas de los actuadores. Así, a partir de la arquitectura propuesta se podrá generar automáticamente el diseño final para el control y supervisión del proceso. La naturaleza visual de la solución propuesta permite utilizar el propio flujo de control como interfaz gráfica de usuario, pudiéndose añadir distintos parámetros configurables por el usuario, así como indicadores clave de rendimiento (en inglés, KPI), útiles para dar soporte a las decisiones relacionadas con el sistema. El método presentado es genérico, pudiéndose implementar en aplicaciones de distinta tipología a la presentada en este trabajo, siendo la evolución natural el escalado a sistemas reales más complejos, aprovechando las ventajas que proporciona la generalidad de la solución propuesta para adaptar el método a otras instalaciones/aplicaciones. Finalmente se muestran los resultados obtenidos con un prototipo probado en una EDAR en el ámbito del Consorci Besos Tordera (CBT), para el control de una de las variables del proceso biológico.Los autores agradecen el soporte en este trabajo del Programa de Doctorado Industrial (2017-DI-006) y de los Grupos/Centros de Investigación Consolidados (2017 SGR 574) por la Agència de Gestió d’Ajuts Universitaris i de Recerca (AGAUR) de la Generalitat de Catalunya.Postprint (published version

Creació d'un bloc d'optativitat amb un projecte pràctic comú, coherent i integrador

El projecte s’emmarca dins la transformació dels estudis cap a l’EEES i concretament a l’Escola d’Enginyers de Terrassa (EET). L’objectiu era dissenyar i aplicar un bloc de 3 assignatures optatives del Grau d’Enginyeria en Electrònica Industrial i Automàtica, que treballin els diferents nivells d’un projecte pràctic comú buscant com a característiques rellevants la coherència, la integració de coneixements, el treball en grup i la coordinació i interrelació entre assignatures i entre els equips docents. El projecte presentat tenia com objectiu l’adaptació dels nous currículums a les noves formes d’aprenentatge social, així com a la formació d’hàbits de treball cooperatiu, de formació d’un esperit crític integrador, i d’anàlisi i deducció d’un problema real. S’ha perseguit que l’estudiant disposi d’uns lligams entre els coneixements obtinguts durant el seu període formatiu i que, davant reptes plantejats, sàpiga utilitzar-los de forma correcta.Peer Reviewe