Eduardo F. Camacho

Universidad de Sevilla | US · Systems Engineering and Automatics

This paper presents the design of a model predictive control (MPC) for the Calais canal, located in the north of France for satisfactory management of the system. To estimate the unknown inputs/outputs arising from the uncontrolled pumps, a digital twin (DT) in the framework of a Matlab- is used to reproduce the dynamics of the canal, and the real...

This paper presents an original algorithm based on the Model Predictive Control strategy for estimating the direct normal irradiance of cloud shaded regions using a mobile robotic sensor system to improve the control of a solar thermal power plant. This new algorithm generates the waypoints of the robot team solving a minimisation problem where the...

This paper presents new results on the Gelbrich distance and the corresponding ambiguity sets, to analyze the correlation between two scalar random variables. A closed expression of the minimum disturbance in the Gelbrich metric necessary to achieve a specified correlation between two random variables is proposed. This expression allows us to analy...

Presents corrections to the paper, An MPC-Based Algorithm for Estimating the Spatial DNI of Cloud Shaded Regions Using a Robotic Sensor System.

This paper reports new properties of the Wasserstein/Gelbrich distance and associated ambiguity sets to analyze the correlation between two scalar random variables. A simple closed expression is derived for the Gelbrich distance between two bidimensional random distributions. Moreover, the minimum disturbance in the Gelbrich metric required to reac...

This review deals with the control of parabolic trough collector (PTC) solar power plants. After a brief introduction, we present a description of PTC plants. We then provide a short literature review and describe some of our experiences. We also describe new control trends in PTC plants. Recent research has focused on ( a) new control methods usin...

This paper proposes a Distributed Moving Horizon Estimation (DMHE) with an Extended Kalman Filter (EKF)-based pre-estimation to solve the constrained cooperative localization problem for a Multi-Agent System (MAS) using nonlinear measurements. The proposed DMHE strategy uses a fused arrival cost obtained by a consensus among neighbors to efficientl...

Fault detection is crucial for ensuring optimal operation and maintenance of solar plants. This paper proposes a methodology for fault detection and isolation using artificial neural networks (ANNs) in a model of a 50 MW parabolic-trough solar plant that employs a defocusing strategy. The proposed methodology focuses on detecting three different ty...

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 constrain...

We present a set-theoretical characterization of a bound on the maximal portion that an agent can cede of its input variable to another agent. By ceding control authority, agents can decompose coupling variables into public and private parts, which is of interest in situations of partial cooperation. In particular, sufficient conditions under whi...

This work develops digital entities of a commercial Fresnel Solar Collector (FSC) installed in an absorption cooling plant. The objective is to create and validate models that describe the FSC dynamics across its whole operation range during the day and the night. Thus, the temperatures range between operation temperature of 180 C and almost ambien...

This work develops digital entities of a commercial Fresnel Solar Collector (FSC) installed in an absorption cooling plant. The objective is to create and validate models that describe the FSC dynamics across its whole operation range during the day and the night. Thus, the temperatures range between operation temperature of 180 °C and almost ambie...

We propose a stochastic model predictive control (SMPC) in combination with a mobile robot to address a control problem for an irrigation canal with uncertain dynamics. We impose tightened constraints over the sampling time of the prediction horizon to make the controller calculate the best route for the robot to gather new measurements for the MPC...

Detecting and isolating faults in collector fields of solar thermal power plants is a crucial and challenging task. The system variables in the collector area are highly coupled, which can lead to a high misclassification rate. For this reason, it becomes necessary to combine knowledge of systems engineering with machine learning techniques that un...

This paper proposes a Distributed Moving Horizon Estimation (DMHE) approach performed by an external static Sensor Network (SN) composed of surveillance ameras and their associated low-cost computers. This approach allows to localize a non-cooperative Multi-Vehicle System (i.e. intruder vehicles which do not communicate with the SN) from sporadic m...

The aim of this study is to create a digital twin of a commercial absorption chiller for control and optimization purposes. The chiller is a complex system that is affected by solar intermittency and non-linearities. The authors use Adaptive Neuro-fuzzy Inference System (ANFIS) to model the chiller's behavior during transients and part-load events....

This article presents a robust coalitional model predictive control (MPC) approach where neighboring agents negotiate the bounds of their coupling variables. Also, the control variables of each agent are divided into a private part that is locally optimized, and a public part that is controlled by the corresponding neighbors. Under certain conditio...

This article proposes a real-time implementation of distributed model predictive controllers to maximize the thermal energy generated by parabolic trough collector fields. For this control strategy, we consider that each loop of the solar collector field is individually managed by a controller, which can form coalition with other controllers to att...

Parabolic-trough solar collector fields are large-scale systems, so the application of centralized optimization-based control methods to these systems is often not suitable for real-time control. As such, this paper formulates a novel coalitional control approach as an appropriate alternative to the centralized scheme. The key idea is to split the...

This paper presents a cloud-based learning model predictive controller that integrates three interacting components: a set of agents, which must learn to perform a finite set of tasks with the minimum possible local cost; a coordinator, which assigns the tasks to the agents; and the cloud, which stores data to facilitate the agents' learning. The t...

A cooperative game theory framework is proposed to solve multi-robot task allocation (MRTA) problems. In particular, a cooperative game is built to assess the performance of sets of robots and tasks so that the Shapley value of the game can be used to compute their average marginal contribution. This fact allows us to partition the initial MRTA pro...

In coalitional model predictive control, the overall system is controlled by a set of networked agents that are dynamically arranged into clusters of connected agents that coordinate their actions, also called coalitions. In this way, the overall coordination burden and the need for sharing information are reduced. In this article, the cluste...

Solar plants are exposed to numerous agents that degrade and damage their components. Due to their large size and constant operation, it is not easy to access them constantly to analyze possible failures on-site. It is, therefore, necessary to use techniques that automatically detect faults. In addition, it is crucial to detect the fault and know i...

The size of existing commercial solar trough plants poses new challenges in applying advanced control strategies to optimize operation. One of these challenges is to obtain a better thermal balance of the loops’ temperature. Since plants are made up of many loops, the efficiency of the loops can vary substantially if a group has been cleaned or aff...

This paper proposes the first application of a split-range control technique on a concentrating solar collector to improve an absorption plant production. Solar absorption plants have solar power availability in phase with cooling demand under design conditions. Thus, it is a powerful cooling technology in the context of renewable energy and energy...

Uno de los principales métodos para mejorar la eficiencia en el uso y aprovechamiento de la energía solar es la aplicación de técnicas avanzadas de control. En este trabajo se presenta un estado del arte de las aplicaciones de control predictivo en plantassolares de pequeña y gran escala. Se presentan además dos aplicaciones reales: una que se dise...

The size of the current commercial solar trough plants poses new challenges in the applications of advanced control strategies. Ensuring safe operation while maintaining the temperature around an adequate set-point can lead to substantial gains in power production. Furthermore, the controller has to take into account the steam generator constraints...

Solar plants are exposed to the appearance of faults in some of their components, as they are vulnerable to the action of external agents (wind, rain, dust, birds …) and internal defects. However, it is necessary to ensure a satisfactory operation when these factors affect the plant. Fault detection and diagnosis methods are essential to detecting...

This paper presents a mobile sensor system to detect and estimate low direct normal irradiance (DNI) areas caused by clouds shadows. This work proposes using a team of unmanned aerial vehicles (UAVs) to localise and characterise the shadow of mobile clouds. This information can be used by the plant control system to minimise its effects over a sola...

With the advancement of new technologies, power systems are increasingly equipped with more sensors and actuators, heightening the risk of failure. This fact, together with the vulnerability of solar plants \x96not only to internal faults but also to the action of the sun, rain, wind, and animals, among others\x96 gives rise to the need for detecti...

El control predictivo engloba a una familia de controladores que replanifican continuamente las entradas del sistema durante un cierto horizonte temporal con el fin de optimizar su evolución esperada conforme a un criterio dado. Esta metodología tiene entre sus retos actuales la adaptación al paradigma de los llamados sistemas ciberfísicos, que est...

This paper focuses on Distributed State Estimation over a peer-to-peer sensor network composed by possible low-computational sensors. We propose a new l-step Neighbourhood Distributed Moving Horizon Estimation technique with fused arrival cost and pre-estimation, improving the accuracy of the estimation, while reducing the computation time compared...

A coalitional robust model predictive controller for tracking target sets is presented. The overall system is controlled by a set of local control agents that dynamically merge into cooperative coalitions or clusters so as to attain an efficient trade-off between cooperation burden and global performance optimality. Within each cluster, the agents...

This article focuses on maximizing the thermal energy collected by parabolic-trough solar collector fields toincrease the production of the plant. To this end, we propose a market-based clustering model predictivecontrol strategy in which controllers of collector loops may offer and demand heat transfer fluid in a market.When a transaction is made...

Clustering strategies are becoming increasingly relevant to boost the scalability of distributed control methods by focusing the cooperation efforts on highly coupled agents. They are also relevant in systems where failing communication links and plug-and-play events are considered, which demand increased flexibility and modularity. This article re...

Coalitional control is concerned with the management of multi-agent systems where cooperation cannot be taken for granted (due to, e.g., market competition, logistics). This paper proposes a model predictive control (MPC) framework aimed at large-scale dynamically-coupled systems whose individual components, possessing a limited model of the system...

In solar parabolic-trough plants, the use of Model Predictive Control (MPC) increases the output thermal power. However, MPC has the disadvantage of a high computational demand that hinders its application to some processes. This work proposes using artificial neural networks to approximate the optimal flow rate given by an MPC controller to decrea...

En este artículo se presenta un algoritmo híbrido bio-inspirado para la detección de formas aplicado a la estimación solar en plantas solares. Se tiene como objetivo localizar y caracterizar la forma de una nube sobre una planta solar basándose en medidas de niveles bajos de la irradiancia con una pequeña flota de vehículos aéreos no tripulados (UA...

This paper focuses on distributed state estimation for sensor network observing a discrete-time linear system. The provided solution is based on a Distributed Moving Horizon Estimation (DMHE) algorithm considering a pre-estimating Luenberger observer in the formulation of the local problem solved by each sensor. This leads to reduce the computation...

Software rejuvenation was born to fix operating system faults by periodically refreshing the run-time code and data. This mechanism has been extended to protect control systems from cyber-attacks. This letter proposes a software rejuvenation design method in discrete-time where invariant sets for the safety and mission controllers are designed to s...

This paper presents a novel clustering model predictive control technique where transitions to the best cooperation topology are planned over the prediction horizon. A new variable, the so-called transition horizon, is added to the optimization problem to calculate the optimal instant to introduce the next topology. Accordingly, agents can predict...

Coalitional control groups dynamically local controllers into clusters that jointly determine their control actions to maximize control performance while minimizing the cooperation burden. This work presents linear matrix inequalities decision methods to set state-space regions where the switchings between network topologies satisfy properties of i...

One of the main control objectives in parabolic trough solar thermal plants is to maintain the outlet temperature around an operating point. For this, a synthetic oil flow is used as the main control variable. However, another crucial system of the plant is the defocusing safety system of the collectors to prevent the oil temperature from exceeding...

In this paper, an event-Mixed Integer Linear Programming (MILP)-based algorithm is proposed to solve the task allocation problem in a Robotic Sensor Network (RSN). A fleet of two types of vehicles is considered, giving, as a result, a heterogeneous configuration of the network, since each type of vehicle has a nominal velocity and a set of allowed...

p>La estimación de estados no observables de un proceso es importante cuando se aplican técnicas de control automático basadas en el espacio de estados. El diseño y uso de estos controladores conlleva suponer que los valores de los estados se podrán obtener de una u otra forma. Cuando todos los estados son medibles, no existe la necesidad de aplica...

This paper presents a Model Predictive Control (MPC) based autopilot for a fixed-wing Unmanned Aircraft Vehicle (UAV) for meteorological data sampling tasks, named Aerosonde. Aerosonde missions are featured by predetermined operating conditions, allowing the design of ad-hoc controllers for each control task by using the future knowledge of the ref...

This article shows how coalitional model predictive control (MPC) can be used to maximize thermal power of large-scale solar parabolic-trough plants. This strategy dynamically generates clusters of loops of collectors according to a given criterion, thus dividing the plant into loosely coupled subsystems that are locally controlled by their corresp...

In the context of state estimation of dynamical systems subject to bounded perturbations and measurement noises, this paper proposes an application of a guaranteed ellipsoidal-based set-membership state estimation technique to estimate the linear position of an octorotor used for radar applications. The size of the ellipsoidal set containing the re...

In solar thermal plants, as in any industrial process, it is important to maintain good control of the system and, more importantly, to have a good security system to avoid exceeding the safety limits of the components and avoid their degradation. In the case of solar thermal plants, one of the main components is the Heat Transfer Fluid (HTF), whic...

A linear matrix inequality approach for designing a family of observers suitable for systems with variable communication topologies is presented. In particular, the observer is composed of blocks associated to the status of the communication links, providing increasing performance as more links are enabled. The error boundaries for topology switchi...

This paper proposes a novel hierarchical coalitional MPC technique, where transitions to the best communication topology are considered over the prediction horizon. For this reason, a new variable, called transition horizon, is added to the optimization problem to compute the optimal instant to introduce a new topology. Consequently, local controll...

This paper proposes a new centralized Model Predictive Control (MPC) algorithm for the maximization of the thermal power obtained with a parabolic-trough collector field. The optimal operation of the plant is achieved by controlling a set of valves located at the beginning of each loop of collectors, which allow to outperform the response achieved...

This paper discusses the application of coalitional model predictive control (MPC) to freeways traffic networks, where the goal is reducing the time spent by the drivers through a dynamic setting of variable speed limits (VSL) and ramp metering. The prediction model METANET is used to represent the traffic flows evolution. The system behavior and o...

A centralized linear MPC is used to stabilize an irrigation system whose operation is represented by an integrator-delay model. Since not all the state variables can be measured, a decentralized ellipsoidal estimation strategy is proposed. This approach keeps the quality of a centralized estimation and reduces significantly the computation time for...

The majority of solar thermal plants which produce electricity and deliver it to the grid use parabolic trough technology. As examples of large scale solar trough plants we can mention the SOLANA power station (280 MW of electricity power with 6 hour of thermal storage) or the 280 MW Mojave solar complex. As stated by the National American Academy...

This paper proposes a new chance-constrained model predictive control (CCMPC) algorithm with state estimation applied to the two-dimensional deployment of a multi-vehicle system where each agent is subject to process noise and measurement noise. The bounded convex area of deployment is partitioned into time-varying Voronoi cells defined by the posi...

One of the ways to improve the efficiency of solar energy plants is by using advanced control and optimization algorithms. In particular, model predictive control strategies have been applied successfully in their control. The control objective of this kind of plant is to regulate the solar field outlet temperature around a desired set-point. Due...

Competitiveness of solar energy is one of current main research topics. Overall efficiency of solar plants can be improved by using advanced control strategies. To design and tuning properly advanced control strategies, a mathematical model of the plant is needed. The model has to fulfill two important points: (1) It has to reproduce accurately the...

One of the great challenges is to make solar energy economical and competitive. This can be achieved by maximizing the generated electricity by using optimal control strategies. A number of research works have been developed concerning control and optimization of solar plants. Most of these works have been developed for the experimental solar trou...

The main control objective in commercial solar parabolic plants is to track the average temperature of all the loops around a reference set by the operator, by manipulating the flow of a synthetic oil. Due to the large number of loops existing in current solar plants and the vast extension that they cover, obtaining a precise knowledge of every loo...

Control strategies allow steering water levels towards their desired values in irrigation canals. The knowledge of the system state is essential to apply any control strategy. Centralized ellipsoidal estimation techniques show adequate performance to estimate unmeasured state variables in small systems, but may became difficult to apply in large sc...

Solar energy for cooling systems has been widely used to fulfill the growing air conditioning demand. The advantage of this approach is based on the fact that the need of air conditioning is usually well correlated to solar radiation. These kinds of plants can work in different operation modes resulting on a hybrid system. The control approaches de...

HIGHLIGHTS • Development and tuning of the Wave-to-Wire model of the Mutriku plant with field data. • Design of three control algorithms for the biradial turbine including a nonlinear MPC. • Numerical results show significant improvement in performance with the MPC. • Sea trials results confirm the good performance and reliable operation of the...

Commercial solar plants produce energy around a nominal operating point in which the solar field outlet temperature is high and close to the thermal limit of the heat transfer fluid. The main control of the temperature is carried out by means of the fluid flow-rate that circulates through the solar field. Defocusing the collectors is normally used...

Commercial solar plants produce energy around a nominal operating point in which the solar field outlet temperature is high and close to the thermal limit of the heat transfer fluid. The main control of the temperature is carried out by means of the fluid flow-rate that circulates through the solar field. Defocusing the collectors is normally used...

Model predictive control strategies have been applied successfully when controlling solar plants. If the control algorithm uses a linear model associated only to an operating point, when the plant is working far from the design conditions, the performance of the controller may deteriorate. In this paper, a gain scheduling model predictive control s...