Ponencias (Ingeniería de Sistemas y Automática)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/11344

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A Hierarchical MPC Framework to Mitigate Faults and Risks in Microgrids
(Elsevier, 2024-07-01) Zafra Cabeza, Ascensión; Velarde Rueda, Pablo; Bordons Alba, Carlos; Ridao Carlini, Miguel Ángel; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Agencia Estatal de Investigación. España; European Union (UE); Universidad de Sevilla. TEP116: Automática y Robótica Industrial
This paper presents a hierarchical MPC-based control framework for a real microgrid including solar panels and batteries, that considers the uncertainty from the point of view of faults and risks (F&R) mitigation. While fault management is applied during plant operation, risk management considers external factors that can change microgrid planning in the medium-long term. Due to their different time-scales, a two-layer control scheme is proposed using Model Predictive Control (MPC) at both levels. At the bottom layer, the fault-tolerant predictive controller optimizes the operation by manipulating inputs to follow microgrid set-points. A reconfiguration strategy is implemented using structured residuals and stochastic thresholds. On the other hand, the upper layer develops an optimal mitigation strategy, also based on MPC, to reduce the effects of risks obtained from external information, i.e., unexpected changes in demands, maintenance costs, or deviations in generation. The decision variables of this layer are the selection of mitigation actions to be undertaken, which minimise a proposed multicriteria objective function. different simulations have been carried out to show the efficacy of this methodology in a F&R scenario from a stochastic point of view.
Robust FOPID Control of an After-Cooler Heat Exchanger with TES
(Elsevier, 2024-06-01) Schiavo, Michele; Garrido Satué, Manuel; Beschi, Manuel; Visioli, Antonio; Arahal, Manuel R.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Union (UE); Universidad de Sevilla. TEP201: Ingeniería de Automatización, Control y Robótica; Universidad de Sevilla. TIC275: Investigación y Desarrollo en Electrónica, Automática y Tecnologías Emergentes
In this paper the temperature control of an after-cooler heat exchanger (AHX) with Thermal Energy Storage (TES) is considered. The AHX can be modelled as a nonlinear system whose gain strongly depends on the operating point. This can cause the reduction of the phase margin which translates into the risk of excessive temperature overshoots. The generalized isodamping approach has been applied to design a fractional-order robust PID controller that guarantees the invariance of the phase margin despite the gain variations. Simulation results performed on a realistic model of the system demonstrate the effectiveness of the proposed design approach.
Modeling and control scheme of the absorption machine of a solar cooling plant
(Elsevier, 2024-06-01) Garrido Satué, Manuel; Castilla Nieto, María del Mar; Rodríguez Rubio, Francisco; Ortega Linares, Manuel Gil; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Universidad de Sevilla. TEP201: Ingeniería de Automatización, Control y Robótica
The article presents the modeling of an absorption machine and a low level control system necessary to ultimately control the cooling power demanded by air conditioning systems. The modeling of the components has been implemented in Simulink in order to obtain a simulator of an absorption-machine-based cooling plant for controller design purposes. In the simulator, the proposed refrigeration system presents control loops to maintain the output variables of the flow rates and temperatures in established references. Finally, the results of the simulation are presented, which show the behavior of the absorption machine system and support the good performance of the proposed low level control system.
Pareto Analysis of PI Tuning in Direct Digital Control of Multi-phase Drives
(Elsevier, 2024) Garrido Satué, Manuel; Álvarez, J.D.; Perales Esteve, Manuel Ángel; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; European Union (UE); European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Universidad de Sevilla. TEP201: Ingeniería de Automatización, Control y Robótica; Universidad de Sevilla. TEP203: Física Interdisciplinar Fundamentos y Aplicaciones
PI tuning for variable-speed multi-phase drives is a complex task. In this paper, a Pareto analysis is introduced to reveal not previously reported links between figures of merit. The drive used for the study includes a 5-phase induction motor supplied by a voltage source inverter. A finite state predictive method is used for the inner loop (current control). The outer loop (speed control) is governed by a PI. The analysis is done experimentally thus including all sorts of non-idealities not appearing in commonly found models. The experimental results show how the pursuit for better performance is hindered by the existence of links between figures of merit. The importance of the result lies in showing that arbitrary performance enhancements are not possible in a general case.
Bridging Time and Frequency for Low-Order, Model-Based PID Control
(Elsevier, 2024-06-01) Ortega Linares, Manuel Gil; Vargas Villanueva, Manuel; Garrido Satué, Manuel; Arahal, Manuel R.; Berenguel, Manuel; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Universidad de Sevilla. TEP201: Ingeniería de Automatización, Control y Robótica; Universidad de Sevilla. TIC275: Investigación y Desarrollo en Electrónica, Automática y Tecnologías Emergentes
In the context of traditional PID model-based control, where sinusoidal or PRBS excitation on a real plant is not advisable or desirable, this paper outlines a method to obtain some relevant information by merely comparing model-based and actual time-domain reaction curves. This comparative analysis yields valuable information that can be subsequently translated into a practical estimate of uncertainty in the frequency domain. This, in turn, will enable the control designer to gain some insight into imposing realistic boundaries for closed-loop response specifications, which will ultimately be consistent with what can be expected from the actual plant response. The conditions for robust stability and robust performance are outlined and further assessed through academic simulation experiments.
Fault Data Injection Detection on a Digital-Twin: Fresnel Solar Concentrator
(Elsevier, 2024-07-01) Chicaiza Salazar, William David; Ortiz Machado, Diogo; Sánchez, Adolfo J.; Escaño González, Juan Manuel; Normey Rico, Julio Elías; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Union (UE). H2020; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; Conselho Nacional de Desenvolvimento Científico e Tecnológico. Brasil; Universidad de Sevilla. TEP116: Automática y Robótica Industrial
This work focuses on developing a neurofuzzy detector capable of identifying a cyber attack of false data injection into the outlet temperature sensor of a Fresnel-type solar field which has a PI+FF controller to control the refered temperature. A digital twin of the Fresnel plant and its controller are used for simulation purposes. The digital twin is situated in the domain of behavior and rules, as it contains a set of models, including a partial Differential equation (PDE) model and a neurofuzzy model. Results from simulation are shown using three different scenarios: (1) without fault, (2) a ramp and threhold with negative injection and (3) the last scenario with positive injection. The presented fault data injection detector has solid performance with more than 97% detection accuracy and precision.
Automatic Drawbridge Scheduling by Integrating Highway and Waterway Traffic Flow Information
(Elsevier, 2024-07-01) Mooij, M. J.; Domínguez Frejo, José Ramón; Reppa, Vasso; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Union (UE). H2020
As inland waterway usage intensifies, it increasingly intersects and conflicts with railway and road transportation modes, highlighting the need for efficient management of these critical junctures. In particular, movable bridges represent a key intersection of highway and waterway Traffic but also a potential source of conflict. This paper proposes and analyzes the use of automatic schedulers that consider both highway and waterway Traffic, reduce conflicts, and make key decisions about bridge use. The METANET macroscopic Traffic model is elaborated to allow the simulation of drawbridge openings on the highway mainline, based on the modelling of mainstream metering. Several MPC-based schedulers are proposed using the designed highway Traffic model and key vessel information, aiming to study the impact of the bridge opening and scheduling on highway Traffic. The simulation results indicate a significant reduction in Traffic conflicts at drawbridge intersections due to the implementation of these schedulers. The functioning of the schedulers is shown to be robust and demonstrate verifiable behavior, indicating their high potential in real-world applications.
Multi-set based model predictive control to explore large freshwater resources
(Elsevier, 2024-06-01) García Martín, Javier; Anderson, Alejandro; Sánchez, Ignacio J.; D'Jorge, Agustina; Duviella, Éric; Maestre Torreblanca, José María; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. TEP116: Automática y robótica industrial
Unmanned surface vehicles can become cutting-edge aquatic laboratories for real-time water quality assessment, evaluating the physical, chemical, and biological profiles of water to detect degradation in freshwater resources. The development of control strategies for surface scanning missions is essential for efficient and effective water resource management. This paper introduces novel exploration methods for analysis experiments. Our approach is founded on an optimizing target-set tracking controller and innovates by adopting a dynamic target-switching method. The target transitions to a further objective once the current target is assured, result in smoother system behavior, as shown by the simulations using the nonlinear model of a commercial surface vehicle tasked with covering a designated area of Heron Lake, located in Villeneuve d’Ascq. The method is implemented in two distinct ways: the first prioritizes passing through all the sets, while the second compromises between passing through and computational cost.
Nonlinear MPC for Thermal Balancing of the TCP-100 Parabolic Trough Collectors Solar Plant
(Institute of Electrical and Electronics Engineers (IEEE), 2023-07) Gallego Len, Antonio Javier; Yebra, Luis J.; Sánchez del Pozo Fernández, Adolfo Juan; Escaño González, Juan Manuel; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Agencia Estatal de Investigación. España; Agencia Estatal de Investigación. España; Agencia Estatal de Investigación. España; Agencia Estatal de Investigación. España; Agencia Estatal de Investigación. España; Agencia Estatal de Investigación. España; Universidad de Sevilla. TEP116: Automatica y Robotica Industrial
The efficiency of the solar plants is conditioned by the control strategies applied in their operation. In this paper, an application of a Model Predictive Controller based on nonlinear models of the TCP-100 parabolic trough collector solar plant is presented as one example of the advanced control techniques that can contribute to enhance the efficiency of this type of plants. Both types of nonlinear models of the TCP-100 facility are applied for this application: lumped and distributed parameter ones. The objective of the proposed control strategy is to face a problem that arises in current commercial solar trough plants, with hundreds of loops, where in practice each of those loops get a different outlet temperature of the heat transfer fluid. These temperature differences might cause inefficiency in the operation and/or irreversible damages by overheating, if not properly controlled. The presented control strategy computes the set-points of the control valves of each of the loops to achieve a good thermal balance of the solar plant. The proposed strategy implements also a heuristic based algorithm when strong transients are affecting the field. The simulation results show that the application of the proposed control technique balances the outlet temperatures of the loops, protecting the TCP-100 facility from damages and increasing its efficiency in the operation.
Aprendizaje de la señal de control para un electrolizador tipo PEM
(Universidade da Coruña, 2024-07) Becerra-Mora, Yeyson; Chicaiza Salazar, William David; Barros-Queiroz, Juliana Sobral; Acosta Rodríguez, José Ángel; Escaño González, Juan Manuel; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia e Innovación (MICIN). España; Universidad de Sevilla
Este trabajo propone el aprendizaje de una señal de control para un electrolizador tipo PEM, considerando variables de entrada y salida del sistema como la corriente eléctrica suministrada por una fuente fotovoltaica, la temperatura ambiente y la energía disipada por el caudal del sistema de refrigeración acoplado al electrolizador. Los datos de corriente eléctrica y temperatura ambiente son medidos por el sistema. Por otro lado, los datos de energía disipada por el caudal del sistema de refrigeración fueron obtenidos a partir de simulaciones de un controlador de temperatura que utiliza la técnica de Control Predictivo Basado en Modelo (MPC). Se proponen dos técnicas de aprendizaje: Gaussian Mixture Model (GMM) / Gaussian Mixture Regression (GMR) y un modelo NeuroFuzzy (NF). Los resultados de las simulaciones demuestran que las técnicas de aprendizaje modelaron con precisión el comportamiento de la señal de control en el electrolizador.
Plataforma para experimentación de controladores basada en sistema aeropropulsado de cuatro rotores coplanarios
(Editorial de la Universidad de Sevilla, 2011-09) García Rodríguez, Ramón Andrés; González Villagómez, Jesús María; Raffo, Guilherme V.; Ortega Linares, Manuel Gil; Vargas Villanueva, Manuel; Rodríguez Rubio, Francisco; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
Este trabajo presenta el diseño e implementación de la arquitectura de un helicóptero a pequeña escala de tipo Quadrotor. Asímismo se presentan resultados de simulación de controladores robustos de estabilización en posición y orientación con realimentación de información visual.
Estimación garantista de la posición de un quadrotor con GPS
(UPC ; CEA, 2013) García Rodríguez, Ramón Andrés; Ortega Linares, Manuel Gil; Rodríguez Rubio, Francisco; Raffo, Guilherme V.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
La aplicación de dos métodos de estimación garantistas sobre un quadrotor se presentan en este artículo. Se tiene un modelo del sistema discretizado en el que se calcula su posición cada T segundos, mientras que la medida del GPS es cada t sincro segundos. Se aplicaron los algoritmos garantistas para contemplar las posibles posiciones en las que se puede encontrar el quadrotor y posteriormente, gracias a la medida del sensor corregir y mejorar la estimación realizada.
ALADIN-Based Distributed Model Predictive Control with Dynamic Partitioning: An Application to Solar Parabolic Trough Plants
(IEEE (Institute of Electrical and Electronics Engineers), 2024-01) Chanfreut Palacio, Paula; Maestre Torreblanca, José María; Krishnamoorthy, D.; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Union (UE); Ministerio de Ciencia e Innovación (MICIN). España; Universidad de Sevilla. TEP-116: Automática y robótica industrial
This article presents a distributed model predictive controller with time-varying partitioning based on the augmented Lagrangian alternating direction inexact Newton method (ALADIN). In particular, we address the problem of controlling the temperature of a heat transfer fluid (HTF) in a set of loops of solar parabolic collectors by adjusting its flow rate. The control problem involves a nonlinear prediction model, decoupled inequality constraints, and coupled affine constraints on the system inputs. The application of ALADIN to address such a problem is combined with a dynamic clustering-based partitioning approach that aims at reducing, with min-imum performance losses, the number of variables to be coordinated. Numerical results on a 10-loop plant are presented.
A Coalitional MPC Approach to Control of Collaborative Vehicle Platoons
(Elsevier, 2023) Chanfreut Palacio, Paula; Keijzer, Twan; Maestre Torreblanca, José María; Ferrari, Riccardo M.G.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. TEP116: Automática y Robótica Industrial
This work presents a coalitional model predictive controller for collaborative vehicle platoons. The overall system is modeled as a string of locally controlled vehicles that can share data through a wireless communication network. The vehicles can dynamically form disjoint groups that coordinate their actions, i.e., the so-called coalitions. The control goals are keeping a desired reference distance between all vehicles while allowing for occasional switching of the communication topology. Likewise, the presented controller promotes a string-stable evolution of the platoon system. Numerical results are provided to illustrate the proposed approach.
Neurofuzzy Defocusing strategy for a Fresnel collector
(Elsevier, 2023) Brandao, Adriano S.M.; Chicaiza Salazar, William David; Sánchez, Adolfo J.; Normey Rico, Julio Elías; Escaño González, Juan Manuel; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia e Innovación (MICIN). España; European Union (UE). H2020; Universidad de Sevilla. TEP116: Automática y Robótica Industrial
Concentrating Solar Power systems are widely applied as a means to utilize the sun's abundant renewable energy, but the design of these processes facilitates the occurrence of overheating. This work presents two approaches for calculating the mirror angles of a fresnel collector in order to limit the amount of solar energy collected. The proposed structures are designed to receive a desired focus value from a controller and generate references for the mirror inclination controllers of the collector. The first strategy consists of the use of an optimization problem coupled with a simplified model of the collector. Whereas, the second approach consists of an ANFIS network that is trained with data from a reliable collector model made in SolTrace®. Both approaches are compared with simulations in SolTrace® the results show that the ANFIS solution presented overall better results, taking into account error and computational time.
Predictive Control of Irrigation Canals Considering Well-being of Operators
(Elsevier / International Federation of Automatic Control (IFAC), 2023-07) Ranjbar, Roza; Sadowska, Anna D.; Maestre Torreblanca, José María; Overloop, Peter Jules van; Schutter, Bart D. de; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; European Research Council (ERC); Universidad de Sevilla. TEP116: Automática y Robótica Industrial
We propose a model-predictive control (MPC) approach to solve a human-in-the-loop control problem for a non-automatic networked system with uncertain dynamics. There are no sensors or actuators installed in the system and we involve humans in the loop to travel between various nodes in the network and to provide the remote controller with measurements as well as actuating the system according to the control requirements. We compute the time instants at which the measurements and actuations should take place to yield better performance with respect to current control methods. We present simulation results using a numerical model of a real canal, the West-M canal in Arizona, and we demonstrate the superiority of the new method over previously proposed ones for such setting.
Real-time monitoring and optimal vessel rescheduling in natural inland waterways
(Elsevier / International Federation of Automatic Control (IFAC), 2023-07) Moreno Nadales, Juan; Muñoz de la Peña Sequedo, David; Limón Marruedo, Daniel; Alamo, Teodoro; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; Universidad de Sevilla. TEP950: Estimación, Predicción, Optimización y Control
Despite the efforts made by the port community and the academia to develop Efficient strategies to mitigate the effect of unexpected events on the planning of vessels through natural waterways, most scheduling algorithms developed so far are not against these events unforseen events. These incidents may lead to nonoptimal operation or even to potentially dangerous situations. To tackle this issue, in this paper we propose a real-time monitoring architecture and a series of optimal rescheduling strategies to re-schedule vessels in real time when an unexpected incident is detected. The objective is to reduce the impact of the incident in the overall process while preserving safety. This is done by detecting deviations from the originally scheduled plans and taking the proper measures when incidents are detected, which will depend on the type of anomaly detected. The proposed methodology is applied to the case of the Guadalquivir river, a natural waterway located in the south of Spain.
Learning-based NMPC on SoC platforms for real-time applications using parallel Lipschitz interpolation
(Elsevier / International Federation of Automatic Control (IFAC), 2023-07) Moreno Nadales, Juan; Carnerero Panduro, Alfonso Daniel; Moreno Blázquez, Carlos; Haes-Ellis, Richard Mark; Limón Marruedo, Daniel; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Agencia Estatal de Investigación. España; Ministerio de Ciencia e Innovación (MICIN). España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Universidad de Sevilla. TEP950: Estimación, Predicción, Optimización y Control
One of the main problems associated with advanced control strategies is their implementation on embedded and industrial platforms, especially when the target application requires real-time operation. Frequently, the dynamics of the system are totally or partially unknown, and data-driven methods are needed to learn an approximate model of the plant to control. On many occasions, these learning techniques use non-differentiable functions that cannot be handled by most traditional low-level gradient-based optimization methods. In addition, many data-driven techniques require the online processing of a vast amount of data, which may be exceedingly time-consuming for most real-time applications. To solve these two problems at once, we propose a low-cost solution based on a system on a chip (SoC) platform featuring an embedded microprocessor (MP) and a field programmable gate array (FPGA) to implement nonlinear model predictive control strategies. The model employed to make predictions about the future evolution of the system is learnt by means of a data-driven learning method know as parallel Lipschitz interpolation (LI) and implemented in the FPGA part. On the other hand, the optimization problem associated with the model predictive control strategy is solved by software in the MP using an adapted version of the particle swarm optimization method.
Population-Dynamics-Assisted Coalitional Model Predictive Control for Parabolic-Trough Solar Plants
(Elsevier / International Federation of Automatic Control (IFAC), 2023-07) Sánchez Amores, Ana; Martínez Piazuelo, Juan; Maestre Torreblanca, José María; Ocampo-Martínez, Carlos; Camacho, Eduardo F.; Quijano, Nicanor; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Unión Europea, Horizonte 2020; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; Universidad de Sevilla. TEP116: Automática y Robótica Industrial
This paper proposes a coalitional model predictive control method for temperature regulation in parabolic-trough solar fields. The global optimization problem is divided into a set of local subproblems that will be solved in parallel by a set of coalitions. However, these local (smaller) problems remain coupled by a common global resource constraint. In this regard, we present a population-dynamics-assisted resource allocation approach to fully decouple the local optimization problems. By doing this, each coalition can address its corresponding optimization problem without relying on the solutions of the other coalitions. To illustrate the proposed methodology, we provide simulation results for a 100-loop parabolic-trough solar collector field.
Two-layer Coalitional Model Predictive Control for Parabolic-Trough Collector Fields
(Elsevier / International Federation of Automatic Control (IFAC), 2023-07) Sánchez Amores, Ana; Maestre Torreblanca, José María; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Unión Europea, Horizonte 2020; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; Universidad de Sevilla. TEP116: Automática y Robótica Industrial
Coalitional control partitions a system into multiple clusters or coalitions that solve independent local subproblems in parallel. This paper presents a two-layer coalitional model predictive control approach for regulation in constrained-coupled subsystems. We formulate a resource allocation mechanism to distribute the coupled constraint so that the global control problem can be solved in a decentralized manner, guaranteeing the satisfaction of the common constraint. In particular, a top layer will calculate the system's partition according to a given criterion and supervise the shared resource allocation. In turn, the lower control layer will calculate the local optimization problems for every coalition in a decentralized fashion, according to the available shared resource determined by the upper layer. This strategy is applied to regulate the outlet temperature of parabolic-trough solar collector fields, which are composed of a set of loops that remain coupled through a global shared resource constraint.

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