Emulación Hardware de un robot implementado en una FPGA bajo la filosofía de Rapid Control Prototyping (RCP)

Este proyecto trata numerosos aspectos relacionados con los conocimientos adquiridos en el grado, entre otros la electrónica analógica y digital, la simulación mediante el entorno de programación visual MATLAB® Simulink o la programación hardware de FPGA usando el lenguaje VHDL. Además, se han utilizado recursos completamente nuevos en cuanto a contacto previo, tales como la creación de mundos virtuales empleando el lenguaje de programación VRML, el empleo del hardware y software de ROBOTIS® (controladora, servos, cableado), etc. Todo esto en conjunto ha permitido simular los tres servos de un robot manipulador virtual, para comprobar y verificar el correcto funcionamiento de la controladora OpenCM9.04 de ROBOTIS.This project deals with several fields of engineering which students work on at my degree, as analogue and digital electronics, systems simulation employing graphical programming environments like MATLAB® Simulink or FPGA hardware programming using VHDL. Moreover, I have used completely new resources regarding previous contact, such as developing virtual worlds by VRML programming language or using ROBOTIS® hardware and software (controllers, servos, wiring), etc. All these aspects together have allow me to simulate three servos belonging to a virtual manipulator robot, in order to check the proper functioning of the ROBOTIS® OpenCM9.04 controller.Universidad de Sevilla. Grado en Ingeniería Electrónica, Robótica y Mecatrónic

Learning Dictionaries from Physical-Based Interpolation for Water Network Leak Localization

This article presents a leak localization methodology based on state estimation and learning. The first is handled by an interpolation scheme, whereas dictionary learning is considered for the second stage. The novel proposed interpolation technique exploits the physics of the interconnections between hydraulic heads of neighboring nodes in water distribution networks. Additionally, residuals are directly interpolated instead of hydraulic head values. The results of applying the proposed method to a well-known case study (Modena) demonstrated the improvements of the new interpolation method with respect to a state-of-the-art approach, both in terms of interpolation error (considering state and residual estimation) and posterior localization

Data-driven leak localization in water distribution networks via dictionary learning and graph-based interpolation

© 2022 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 worksIn this paper, we propose a data-driven leak localization method for water distribution networks (WDNs) which combines two complementary approaches: graph-based interpolation and dictionary classification. The former estimates the complete WDN hydraulic state (i.e., hydraulic heads) from real measurements at certain nodes and the network graph. Then, we append to the actual measurements a subset of relevant estimated states to feed and train the dictionary learning scheme. Thus, the meshing of these two methods is explored, and several promising performance results are attained, even deriving different mechanisms to increase the resilience to classical issues (e.g., dimensionality, interpolation errors, etc.). The approach is validated using the L-TOWN benchmark proposed in the BattLeDIM2020 competition.Peer ReviewedPostprint (author's final draft

A feedback simulation procedure for real-time control of urban drainage systems

This paper presents a feedback simulation procedure for the real-time control (RTC) of urban drainage systems (UDS) with the aim of providing accurate state evolutions to the RTC optimizer as well as illustrating the optimization performance in a virtual reality. Model predictive control (MPC) has been implemented to generate optimal solutions for the multiple objectives of UDS using a simplified conceptual model. A high-fidelity simulator InfoWorks ICM is used to carry on the simulation based on a high level detailed model of a UDS. Communication between optimizer and simulator is realized in a feedback manner, from which both the state dynamics and the optimal solutions have been implemented through realistic demonstrations. In order to validate the proposed procedure, a real pilot based on Badalona UDS has been applied as the case study.Peer ReviewedPostprint (author's final draft

Model-free sensor placement for water distribution networks using genetic algorithms and clustering

This paper presents a model-free methodology for the placement of pressure sensors in water distribution networks (WDNs) with the aim of performing leak detection/localization tasks. The approach is based on a custom genetic algorithm (GA) optimization scheme, which considers a population whose individuals are binary vectors encoding the network nodes with/without sensors. The optimization process pursues the minimization of a distance-based metric, computed considering the pipe distance from the possible sensors to the complete set of nodes of the network, hence removing the necessity of a hydraulic model of the WDN. The methodology is completed by means of an iterative clustering technique that seeks the enhancement of incoming individuals. The proposed methodology is tested over a well-known case study, L-TOWN from the BattLeDIM2020 challenge, in order to assess its performance.Peer ReviewedPostprint (published version

A fully data-driven approach for leak localization in water distribution 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 data-driven technique for the localization of leaks in water distribution networks (WDN). The methodology requires hydraulic data, i.e., pressure measurements from a set of sensors installed throughout the network and topological information. Therefore, the hydraulic model of the WDN is not necessary for its operation. The hydraulic state of the complete set of nodes of the network is approximated by means of a graph-based interpolation technique. Then, a set of candidates where the leak can be located is achieved by comparing the computed states for both the leaky and nominal cases. The methodology is applied to a case study based on a real network, providing and discussing several graphical results and key performance indicators.The authors want to thank the RIS3CAT Utilities 4.0 SENIX project (COMRDI16-1-0055), as well as the Spanish national project DEOCS (DPI2016-76493-C3-3-R) and the Spanish State Research Agency through the María de Maeztu Seal of ExcelPeer ReviewedPostprint (author's final draft

Leak localization in water distribution networks using data-driven and model-based approaches

The detection and localization of leaks in water distribution networks (WDNs) is one of the major concerns of water utilities, due to the necessity of an efficient operation that satisfies the worldwide growing demand for water. There exists a wide range of methods, from equipment-based techniques that rely only on hardware devices to software-based methods that exploit models and algorithms as well. Model-based approaches provide an effective performance but rely on the availability of an hydraulic model of the WDN, while data-driven techniques only require measurements from the network operation but may produce less accurate results. This paper proposes two methodologies: a model-based approach that uses the hydraulic model of the network, as well as pressure and demand information; and a fully data-driven method based on graph interpolation and a new candidate selection criteria. Their complementary application was successfully applied to the Battle of the Leakage Detection and Isolation Methods (BattLeDIM) 2020 challenge, and the achieved results are presented in this paper to demonstrate the suitability of the methods.Peer ReviewedPostprint (author's final draft

Integrated pollution-based real-time control of sanitation systems

© 2020. ElsevierAn integrated pollution-based real-time control (RTC) approach is proposed for a sewer network (SN) integrated with wastewater treatment plants (WWTPs) in a sanitation system (SS) to mitigate the impacts of pollution from combined sewer overflows (CSOs) on ecosystems. To obtain the optimal solution for the SS while considering both quantity and quality dynamics for multiple objectives, model predictive control (MPC) is selected as the optimal control method. To integrate SN and WWTP management, a feedback coordination algorithm is developed. A closed-loop virtual-reality simulator is used to assess the results of the optimal management approach achieved by applying MPC. The Badalona SS (Spain) provides a pilot case study to assess the efficacy and applicability of the proposed approach. A comparison with local rule-based and volume-based control strategies currently in use indicates that the proposed integrated pollution-based RTC approach can reduce the pollutant loads released to the receiving environment.Peer ReviewedPostprint (author's final draft

Automatic network response methodology for failure recovery or bursts in drinking water networks

This article presents a novel response methodology for the operational recovery of a drinking water network after an incident causes an interruption of service. The proposed optimization-based methodology allows computing the optimal set of interventions to be performed in order to mitigate, or even prevent, the impact of the incident on the network operation. Besides, a proof-of-concept scheme has been designed for the automatic generation of failure scenarios and the systematic implementation and validation of the proposed response methodology. Several results are presented to demonstrate the capability of the methodology to mitigate harmful incidents, as well as the performance improvements derived from the application of the obtained interventions.Peer ReviewedPostprint (author's final draft