Artículos (Ingeniería de Sistemas y Automática)

URI permanente para esta colecciónhttps://hdl.handle.net/11441/11342

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  • Acceso AbiertoArtículo
    Physical-Virtual Impedance Control in Ultralightweight and Compliant Dual-Arm Aerial Manipulators
    (IEEE, 2018-02-26) Suárez Fernández-Miranda, Alejandro; Heredia Benot, Guillermo; Ollero Baturone, Aníbal; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Commission (EC); Ministerio de Economía y Competitividad (MINECO). España; Ministerio de Educación, Cultura y Deporte (MECD). España; Universidad de Sevilla. TEP151: Robótica, Visión y Control
    Dual-arm aerial manipulation requires the design and development of high performance robotic arms in terms of safety, robustness, and force/torque/impedance control, taking into account the integration in the aerial platform, the strong weight constraints, and the technological limitations of the servo actuators. A compliant joint arm also improves the response of the aerial manipulator to collisions and external forces during the flight operation. This letter evaluates the control capabilities in a lightweight manipulator built with smart servo actuators and a spring-lever transmission mechanism that provides joint compliance and deflection measurement. The dynamic model of a compliant joint is validated through frequency identification, demonstrating how virtual variable impedance can be achieved without a second motor. Mechanical joint compliance is the base of the Cartesian impedance control scheme of the dual-arm system, integrated with the controller of the aerial platform. A stereo vision system provides the Cartesian deflection of the end effector, derived from the definition of an equivalent stiff joint manipulator, allowing the estimation and control of the contact forces. Experimental results validate the developed concepts.
  • Acceso AbiertoArtículo
    Coalitional model predictive control of an irrigation canal
    (Elsevier, 2014-04) Fele, Filiberto; Maestre Torreblanca, José María; Hashemy, S. Mehdy; Muñoz de la Peña Sequedo, David; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Union (UE); Ministerio de Educación y Cultura (MEC). España
    We present a hierarchical control scheme for large-scale systems whose components can exchange information through a data network. The main goal of the supervisory layer is to find the best compromise between control performance and communicational costs by actively modifying the network topology. The actions taken at the supervisory layer alter the control agents’ knowledge of the complete system, and the set of agents with which they can communicate. Each group of linked subsystems, or coalition, is independently controlled through a decentralized model predictive control (MPC) scheme, managed at the bottom layer. Hard constraints on the inputs are imposed, while soft constraints on the states are considered to avoid feasibility issues. The performance of the proposed control scheme is validated on a model of the Dez irrigation canal, implemented on the accurate simulator for water systems SOBEK. Finally, the results are compared with those obtained using a centralized MPC controller.
  • Acceso AbiertoArtículo
    Coalitional Control: Cooperative Game Theory and Control
    (IEEE, 2017-02) Fele, Filiberto; Maestre Torreblanca, José María; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
    The evolution of information and communication technologies has yielded the means of sharing measurements and other information in an efficient and flexible way [1], which has enabled the size and complexity of control applications to increase [2]. At the same time, the improvements in the computational and communicational capabilities of control devices have fostered the development of noncentralized control architectures, already motivated by the inherent structural constraints of large-scale systems. Computer-based control approaches such as model predictive control (MPC) are visible beneficiaries of these advances and have registered a significant growth regarding both theoretical and applied fields [3], [4].
  • Acceso AbiertoCapítulo de Libro
    Distributed Thermal Identification and Exploitation for Multiple Soaring UAVs
    (Springer, 2014-11) Cobano Suárez, José Antonio; Alejo, David; Vera, Santiago; Heredia Benot, Guillermo; Sukkarieh, Salah; Ollero Baturone, Aníbal; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Spagnolo, P.; Mazzeo, P.; Distante, C.; European Commission (EC); Ministerio de Ciencia e Innovación (MICIN). España; Ministerio de Educación, Cultura y Deporte (MECD). España
    This chapter discusses the problem of cooperatively sensing the wind map of an area in order to efficiently harvest the wind energy with fixed-wing gliding UAVs, known as soaring. Moreover, a cooperative system with multiple gliding fixed-wing UAVs is presented for long endurance missions. This system is composed by three main blocks that include thermal detector, path planning, and collision avoidance. The main advantage is its low computational load, making it suitable for real-time applications. Extensive simulation results in several scenarios are given to test the complete system. In addition, real experiments have been carried out with real gliding aircrafts of the Robotics Vision and Control Group (GRVC) of the University of Sevilla in the Airfield of La Cartuja (Sevilla). The results of these experiments show the convenience of the proposed method.
  • EmbargoArtículo
    Collision-free path planning for multiple robots using efficient turn-angle assignment
    (Elsevier, 2024-07) Rodríguez Sánchez, Fabio; Díaz Báñez, José Miguel; Fabila Monroy, Ruy; Caraballo de la Cruz, Luis Evaristo; Capitán Fernández, Jesús; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia e Innovación (MICIN). España; Agencia Estatal de Investigación. España; European Union NextGeneration; Universidad de Sevilla. TEP995: Multi-robot And Control Systems
    The ability to avoid collisions with moving robots is critical in many applications. Moreover, if the robots have limited battery life, the goal is not only to avoid collisions but also to design efficient trajectories in terms of energy consumption and total mission time. This paper proposes a novel strategy for assigning turn angles for collision-free path planning in scenarios where a small team of robots cooperate in a certain mission. The algorithm allows each robot to reach a predetermined destination safely. It establishes consecutive, short time intervals, and at each interval, possible conflicts are solved centrally in an optimal manner. This is done by keeping constant speeds but generating a discrete set of possible directions for each robot, and solving efficiently the turn-angle allocation for a collision-free path that minimizes the path deviation from the shortest one. Due to the discretization, the final paths are not optimal, but the system can react to possible failures during execution, as conflicts are resolved at each time interval. Computational results and Software-In-The-Loop simulations are presented in order to evaluate the proposed algorithm. A comparison with a state-of-the-art approach shows that our algorithm is more energy-efficient and achieves lower mission completion time.
  • Acceso AbiertoArtículo
    Autonomous Aerial Filming with Distributed Lighting by a Team of Unmanned Aerial Vehicles
    (Institute of Electrical and Electronics Engineers (IEEE), 2021-10) Kratky, Vit; Alcántara Marín, Alfonso; Capitán Fernández, Jesús; Stepan, Petr; Saska, Martin; Ollero Baturone, Aníbal; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Junta de Andalucía
    This letter describes a method for autonomous aerial cinematography with distributed lighting by a team of unmanned aerial vehicles (UAVs). Although camera-carrying multi-rotor helicopters have become commonplace in cinematography, their usage is limited to scenarios with sufficient natural light or of lighting provided by static artificial lights. We propose to use a formation of unmanned aerial vehicles as a tool for filming a target under illumination from various directions, which is one of the fundamental techniques of traditional cinematography. We decompose the multi-UAV trajectory optimization problem to tackle non-linear cinematographic aspects and obstacle avoidance at separate stages, which allows us to re-plan in real time and react to changes in dynamic environments. The performance of our method has been evaluated in realistic simulation scenarios and field experiments, where we show how it increases the quality of the shots and that it is capable of planning safe trajectories even in cluttered environments
  • Acceso AbiertoArtículo
    A Dynamic Weighted Area Assignment Based on a Particle Filter for Active Cooperative Perception
    (Institute of Electrical and Electronics Engineers (IEEE), 2020-04) Acevedo Báñez, José Joaquín; Messias, Joao; Capitán Fernández, Jesús; Ventura, Rodrigo; Merino, Luis; Lima, Pedro U.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Union; Ministerio de Ciencia, Innovación y Universidades (MICINN). España; Universidade de Lisboa; Universidad de Sevilla. TEP151: Robótica, Visión y Control
    This article addresses an Active cooperative perception problem for networked robots systems. Given a team of networked robots, the goal is finding a target using their inherent uncertain sensor data. The article proposes a particle filter to model the probability distribution of the position of the target, which is updated using detection measurements from all robots. Then, an information-theoretic approach based on the RRT∗ algorithm is used to determine the optimal robots trajectories that maximize the information gain while surveying the map. Finally, a dynamic area weighted allocation approach based on particle distribution and coordination variables is proposed to coordinate the networked robots in order to cooperate efficiently in this active perception problem. Simulated and real experimental results are provided to analyze, evaluate and validate the proposed approach.
  • Acceso AbiertoArtículo
    The Velocity Assignment Problem for Conflict Resolution with Multiple Aerial Vehicles Sharing Airspace
    (Springer, 2013-01) Alejo, David; Díaz Báñez, José Miguel; Cobano Suárez, José Antonio; Pérez Lantero, Pablo; Ollero Baturone, Aníbal; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER); Universidad de Sevilla. TEP151: Robótica, Visión y Control
    Efficient conflict resolution methods for multiple aerial vehicles sharing airspace are presented. The problem of assigning a velocity profile to each aerial vehicle in real time, such that the separation between them is greater than a given safety distance, is considered and the total deviation from the initial planned trajectory is minimized. The proposed methods involve the use of appropriate airspace discretization. In the paper it is demonstrated that this aerial vehicle velocity assignment problem is NP-hard. Then, the paper presents three different collision detection and resolution methods based on speed planning. The paper also presents simulations and studies for several scenarios.
  • Acceso AbiertoArtículo
    Conflict Detection and Resolution Method for Cooperating Unmanned Aerial Vehicles
    (2012-01) Conde, Roberto; Alejo, David; Cobano Suárez, José Antonio; Viguria, Antidio; Ollero Baturone, Aníbal; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Commission (EC); Junta de Andalucía; Univarsidad de Sevilla. TEP151; Robotica, Vision y Control
    This paper presents a Conflict Detection and Resolution (CDR) method for cooperating Unmanned Aerial Vehicles (UAVs) sharing airspace. The proposed method detects conflicts using an algorithm based on axis-aligned minimum bounding box and solves the detected conflicts cooperatively using a genetic algorithm that modifies the trajectories of the UAVs with an overall minimum cost. The method changes the initial flight plan of each UAV by adding intermediate waypoints that define the solution flight plan while maintaining their velocities. The method has been validated with many simulations and experimental results with multiple aerial vehicles platforms based on quadrotors in a common airspace. The experiments have been carried out in the multi-UAV aerial testbed of the Center for Advanced Aerospace Technologies (CATEC).
  • Acceso AbiertoArtículo
    Human Modeling and Passivity Analysis for Semi-Autonomous Multi-Robot Navigation in Three Dimensions
    (Institute of Electrical and Electronics Engineers (IEEE), 2024) Hatanaka, Takeshi; Mochizuki, Takahiro; Sumino, Takumi; Maestre Torreblanca, José María; Chopra, Nikhil; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia, Innovación y Universidades (MICIU). España; Universidad de Sevilla. TEP116: Automática y Robótica Industrial
    In this article, we study a one-human-multiple-robot interaction for human-enabled multi-robot navigation in three dimensions. We employ two fully distributed control architectures designed based on human passivity and human passivity shortage. The first half of this article focuses on human modeling and analysis for the passivity-based control architecture through human operation data on a 3-D human-in-the-loop simulator. Specifically, we compare virtual reality (VR) interfaces with a traditional interface, and examine the impacts that VR technology has on human properties in terms of model accuracy, performance, passivity and workload, demonstrating that VR interfaces have a positive effect on all aspects. In contrast to 1-D operation, we confirm that operators hardly attain passivity regardless of the network structure, even with the VR interfaces. We thus take the passivity-shortage-based control architecture and analyze the degree of passivity shortage. We then observe through user studies that operators tend to meet the degree of shortage needed to prove closed-loop stability.
  • Acceso AbiertoArtículo
    Stochastic Optimization of Microgrids with Hybrid Energy Storage Systems for Grid Flexibility Services Considering Energy Forecast Uncertainties
    (Institute of Electrical and Electronics Engineers (IEEE), 2021-11) García Torres, Félix; Bordons Alba, Carlos; Tobajas, Javier; Real-Calvo, Rafael; Santiago, Isabel; Grieu, Stephane; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. TEP116: Automática y Robótica Industrial
    This paper presents a stochastic framework for the optimization of microgrids that has the functionality of providing flexibility services to System Operators (SOs) considering uncertainties in the energy forecast. The methodology is developed with the aim of being applied to complex microgrids composed of different distributed energy resources and hybrid energy storage systems (ESS). The associated optimization problem is operated in two stages: the first one performs a stochastic optimization of the microgrid in order to reserve an up/down regulation capacity with which to deal with the energy forecast uncertainties of the microgrid. The different microgrid devices are optimized by considering their operational costs in order to achieve their optimal operation in the Day-Ahead Market (DM). The second stage is used to re-schedule the initial planning according to the signal request and an economic offer from the SO. The control problem is developed using Stochastic Model Predictive Control (SMPC) techniques and Mixed-Integer Quadratic Programming (MIQP), owing to the presence of logic, integer, mixed and probabilistic variables. The simulation results show that the proposed methodology reduces the risk of undergoing up/down-penalty deviations in the Regulation Service Market (RM), also being able to provide flexibility services to the SOs, despite being subject to uncertainties in the energy forecast carried out for the microgrid.
  • Acceso AbiertoArtículo
    Chance Constraints and Machine Learning integration for uncertainty management in Virtual Power Plants operating in simultaneous energy markets
    (Elsevier, 2021-12) Aguilar, Juan; Bordons Alba, Carlos; Arce, Alicia; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. TEP116: Automática y Robótica Industrial
    The management of uncertainty is one of the most important issues affecting the optimal operation of Distributed Energy Resources (DERs). Virtual Power Plants (VPPs) aggregate different Energy Nodes (ENs) to enable them to participate in energy markets in an aggregated way. This participation requires very accurate forecast services to trade off between the revenue at bidding time, by making more aggresive bids, and the reduction of penalties at operation time due to deviations from the commitment. In this paper, a stochastic optimization layer is built over a Model Predictive Control (MPC) kernel to define a Stochastic Model Predictive Control (SMPC) scheme by combining Chance-Constrained (CC) and Machine Learning (ML) to handle the uncertainty related to generation and load profiles at optimization time.This technique can be applied to participate simultaneously in different energy markets depending on the configuration or capacity of the VPP, and according to the business model of the system operator. More accurate optimizations allow more profitable operations and more flexibility to redistribute the energy allocation to offer different energy services. The results are satisfactory as this scheme works better than the deterministic approach in terms of penalty reduction for most of the cases.
  • Acceso AbiertoArtículo
    Voronoi Multi-phase Predictive Current Control with Variable Application Times
    (IEEE, 2025) Arahal, Manuel R.; Barrero, Federico; Garrido Satué, Manuel; Colodro Ruiz, Francisco; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Agencia Estatal de Investigación. España
    Predictive Stator Current Control (PSCC) is a flexible technique for drives of different types. For the multiphase case, PSCC must deal with an increased number of available control options (the voltage vectors) and cope with the different current spaces: torque producing (α−β) and harmonic planes (x − y). In this paper, a Voronoi region based scheme is designed to cope with both issues while maintaining an affordable commutation frequency. The proposal is enhanced by using variable application times with fine resolution. The method is compared with state of the art dead-beat multi-vector approach. The comparison is made using a real, laboratory setup designed for experimentation based on a five-phase induction machine. The comparison shows enhanced control results together with a reduction in harmonic content, without compromising the switching frequency limits of the power converters and maintaining flexibility due to the cost function.
  • Acceso AbiertoArtículo
    Robust Model Predictive Control for an Ion Beam Shepherd in a large-debris removal mission
    (Elsevier, 2024-12) Urrios Gómez, Francisco Javier; Vázquez Valenzuela, Rafael; Gavilán Jiménez, Francisco; Alvarado Aldea, Ignacio; Universidad de Sevilla. Departamento de Ingeniería Aeroespacial y Mecánica de Fluidos; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Ciencia, Innovación y Universidades (MICINN). España; European Union (UE)
    The increasing accumulation of space debris poses significant risks to spacecraft, making the development of effective debris mitigation technologies necessary. This paper explores the Ion Beam Shepherd (IBS) method as a potential contactless solution for deorbiting large debris objects. The IBS system concept involves a spacecraft equipped with an ion thruster to direct a controlled ion beam at the debris, generating a small force that gradually lowers its orbit. A proposed configuration of the chaser’s actuator system integrates radial and out-of-plane cold-gas thrusters along with in-track ion thrusters to enhance control and safety while maintaining low mission costs. A robust Model Predictive Control (MPC) strategy is implemented, using the theory of MPC for Tracking to ensure accurate positioning and effective deorbiting. This theoretical approach addresses uncertainties and perturbations to robustly guarantee safe distances between the chaser and the debris. Additionally, a new ray-marching-based algorithm is introduced to estimate the force and torque exerted by the ion beam on the target, considered as a 6 degrees of freedom object, improving simulation accuracy and control performance assessment. A comprehensive simulation of the deorbit of a large debris object is performed, demonstrating the potential of the IBS technology for future large-debris removal missions. This research advances the conceptual framework and control techniques for the IBS technology, advancing towards its future implementation in space debris mitigation.
  • Acceso AbiertoArtículo
    Multi-Phase Stator Current Tracking with Gradual Penalization of Commutations
    (MDPI, 2024-07) Arahal, Manuel R.; Garrido Satué, Manuel; Martínez Heredia, Juana María; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. Departamento de Ingeniería Electrónica
    Energy efficiency in drives is an important issue. In converter-supplied variable-speed drives, switching losses can amount to a significant portion of all losses. This has been considered in Predictive Stator Current Control (PSCC), considering commutations at the power converter. However, in multi-phase drives, the computational burden limits the application of said techniques. Recent fast predictive algorithms have enabled shorter application times with enhanced tracking results. However, the switching frequency becomes larger with diminishing sampling periods. This paper presents a method that retains the fast computation of recent methods while reducing the switching frequency. The proposal revolves around a modification of the cost function to penalize commutations in a nonlinear way. For this task, a novel, gradual penalization is introduced. The method is experimentally applied to a five-phase induction motor. Experimental results show a significant reduction in switching frequency without compromising other control objectives. This results in an enhanced PSCC with a small sampling period and reduced switching losses.
  • Acceso AbiertoArtículo
    Collision-Free 4D Trajectory Planning in Unmanned Aerial Vehicles for Assembly and Structure Construction
    (Springer, 2014-01) Alejo, David; Cobano Suárez, José Antonio; Heredia Benot, Guillermo; Ollero Baturone, Aníbal; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Commission (EC); Ministerio de Ciencia e Innovación (MICIN). España; Junta de Andalucía; Universidad de Sevilla. TEP151: Robótica, Visión y Control
    This paper presents a new system for assembly and structure construction with multiple Unmanned Aerial Vehicles (UAVs) which automatically identifies conflicts among them. The system proposes the most effective solution considering the available computation time. After detecting conflicts between UAVs, the system resolves them cooperatively using a collision-free 4D trajectory planning algorithm based on a simple one-at-a-time strategy to quickly compute a feasible but non-optimal initial solution and a stochastic optimization technique named Particle Swarm Optimization (PSO) to improve the initial solution. An anytime approach using PSO is applied. It yields trajectories whose quality improves when available computation time increases. Thus, the method could be applied in real-time depending on the available computation time. The method has been validated with simulations in scenarios with multiple UAVs in a common workspace and experiment in an indoor testbed.
  • Acceso AbiertoArtículo
    Assessing SOC Estimations via Reverse-Time Kalman for Small Unmanned Aircraft
    (Multidisciplinary Digital Publishing Institute (MDPI), 2024-08) Arahal, Manuel R.; Pérez Vega-Leal, Alfredo; Garrido Satué, Manuel; Esteban Roncero, Sergio; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. Departamento de Ingeniería Electrónica; Universidad de Sevilla. Departamento de Ingeniería Aeroespacial y Mecánica de Fluidos; Agencia Estatal de Investigación. España; European Commission (EC). Fondo Europeo de Desarrollo Regional (FEDER)
    This paper presents a method to validate state of charge (SOC) estimations in batteries for their use in remotely manned aerial vehicles (UAVs). The SOC estimation must provide the mission control with a measure of the available range of the aircraft, which is critical for extended missions such as search and rescue operations. However, the uncertainty about the initial state and depth of discharge during the mission makes the estimation challenging. In order to assess the estimation provided to mission control, an a posteriori re-estimation is performed. This allows for the assessment of estimation methods. A reverse-time Kalman estimator is proposed for this task. Accurate SOC estimations are crucial for optimizing the utilization of multiple UAVs in a collaborative manner, ensuring the efficient use of energy resources and maximizing mission success rates. Experimental results for LiFePO4 batteries are provided, showing the capabilities of the proposal for the assessment of online SOC estimators.
  • Acceso AbiertoArtículo
    Spatio-temporal Kriging for spatial irradiance estimation with short-term forecasting in a thermosolar power plant
    (Elsevier, 2024-10) García Martín, Javier; Domínguez Frejo, José Ramón; Maestre Torreblanca, José María; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; European Research Council (ERC); Ministerio de Ciencia, Innovación y Universidades (MICIU). España; Universidad de Sevilla. TEP116: Automática y Robótica Industrial
    This article proposes a method to improve the efficiency of solar power plants by estimating and forecasting the spatial distribution of direct normal irradiance (DNI) using a sensor network and anemometer data. For this purpose, the proposed approach employs spatio-temporal kriging with an anisotropic spatio-temporal variogram that depends on wind speed to accurately estimate the distribution of DNI in real-time, making it useful for short-term forecast and nowcast of DNI. Finally, the method is validated using synthetic data from varying sky conditions, outperforming another state-of-the-art technique.
  • Acceso AbiertoArtículo
    On the optimization of flux distribution with flat receivers: A distributed approach
    (Elsevier, 2018-01-15) Gallego Len, Antonio Javier; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Junta de Andalucía; Ministerio de Educación. España
    One of the most important problems in the operation of solar power towers is to achieve a uniform flux density distribution at the receiver in order to avoid hot spots. The problem can be solved by computing the aim points of the heliostats by optimizing a function which measures the uniformity of the flux density over the receiver. Due to the high number of heliostats of current commercial plants (more than 900), the number of decision variables (1800) makes the centralized approach very difficult to be implemented in real time. In this paper, a distributed optimization algorithm that computes the aim points for the heliostat field to obtain a uniform flux density distribution and maximize the solar irradiation collected by the receiver is presented. The algorithm is tested using a model of the heliostat field of the CESA-1 solar tower plant at the Plataforma Solar de Almería (PSA) in southern Spain. Simulation results show that substantial reduction of the computational time is achieved while similar performance to that obtained with the centralized approach is attained.
  • Acceso AbiertoArtículo
    Estimation of effective solar irradiation using an unscented Kalman filter in a parabolic-trough field
    (2012-12) Gallego Len, Antonio Javier; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Educación y Ciencia (MEC). España; Junta de Andalucía; European Union (UE)
    Measurement of direct solar radiation has been shown to be very useful to improve control performance and disturbance rejection in solar fields by anticipating the effect of sudden changes in solar radiation due to clouds. Since direct solar radiation is measured locally by pyrheliometers, important errors in the estimation of the overall effective solar radiation can be produced when the pyrheliometer is covered by clouds while the rest of the solar field is not or viceversa. Furthermore, estimation of the overall efficiency affected by the reflectivity and absortance of metal tubes is very difficult because only local measurements can be obtained. This work proposes an algorithm for estimating overall solar radiation and efficiency at the field. The algorithm uses an unscented Kalman filter and it is validated by data obtained at the Plataforma Solar of Almerı´a (Spain).