J.M. Maestre

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• PhD
• Professor (Full) at University of Seville

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 th...

The evolution of information and communication technologies has yielded the means of sharing measurements and other information in an efficient and flexible way, which has enabled the size and complexity of control applications to increase. At the same time, the improvements in the computational and communicational capabilities of control devices h...

The recent major developments in information technologies have opened interesting possibilities for the effective management of multi-agent systems. In many cases, the important role of central control nodes can now be undertaken by several controllers in a distributed topology that suits better the structure of the system. This opens as well the p...

In this article, we address aquatic environmental monitoring using a fleet of unmanned surface vehicles (USVs). Specifically, we develop an online path generator that provides either of circular or elliptic paths based on the real-time feedback so that the USVs efficiently sample the sensor data over given aquatic environment. To this end, we begin...

Highlights •An anisotropic spatio-temporal kriging approach is proposed to estimate/forecast DNI in a thermosolar plant on cloudy days. •The method considers wind speed and direction, improving accuracy with fewer parameters than other estimation techniques. •The proposed method outperforms state-of-the-art techniques in estimating DNI distribution...

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...

In this article, we present an enhanced version of Cutler's deconvolution method to address the limitations of the original algorithm in estimating realistic input and output parameters. Cutler's method, based on orthogonal polynomials, suffers from unconstrained solutions, leading to the lack of realism in the deconvolved signals in some applicati...

Distributed electric drive vehicles offer maneuver-ability but face stability challenges under different driving conditions. Model Predictive Control (MPC) algorithms can improve lateral stability, but their high computational demands hinder real-time implementation. To address this, the proposed strategy combines Nonlinear Autoregressive Exogenous...

Software rejuvenation is a cyberdefense mechanism that periodically resets the control software of a system to limit the impact of cyberattacks. We propose open and closed-loop tree-based model predictive controllers to explicitly account for the software refresh events and the cyberattacks. The benefits of the proposed methods are illustrated usin...

This study aims to introduce a comprehensive framework for canal modernization, emphasizing the integration of the Archimedes screw turbine as an alternative to traditional drop structures. The goal is to harness renewable energy, improve water distribution efficiency, and address both economic and environmental concerns within canal systems. Our a...

This article combines data and tube-based predictive control to deal with systems with bounded parametric uncertainty. This integration generates robustly feasible control sequences that can also be exploited in cooperative scenarios where controllers learn from each other’s data. In particular, the approach is based on a database that contains inf...

In this article, a stochastic programming method is used to control a residential microgrid where possible disturbance realizations over a horizon are shaped into a tree structure with a given probability. This tree is used by model predictive controllers within a hierarchical and distributed scheme. The upper layer is characterized by a smart cont...

El Comité Español de Automática (CEA) es una asociación científica sin ánimo de lucro que impulsa el desarrollo, la investigación y las enseñanzasuniversitarias en Automática. Es miembro nacional de la Federación Internacional de Control Automático (IFAC), y celebra anualmente desde el año 1977 las Jornadas de Automática. Estas se organizan por dis...

We propose a model-predictive control (MPC)-based approach to solve a human-in-the-loop control problem for a network system lacking sensors and actuators to allow for a fully automatic operation. The humans in the loop are, therefore, essential; they travel between the network nodes to provide the remote controller with measurements and to actuate...

This paper proposes an offset-free distributed implementation of a model predictive controller that employs fuzzy negotiation between agents. The scheme is based on model augmentation with additional disturbances to enable zero-offset tracking. Moreover, we code the negotiation criteria as a set of suitable fuzzy rules and consider stability and fe...

This paper presents a distributed setting of model predictive control (MPC) to manage linear multi-agent systems consisting of coupled subsystems. Specifically, local controllers can work in coalitions to improve performance and handle plug-and-play events. This study provides insight into a coalitional MPC strategy based on optimized tubes that ha...

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...

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 t...

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 paper presents a distributed setting of model predictive control (MPC) to manage linear multi-agent systems consisting of coupled subsystems. Specifically, local controllers can work in coalitions to improve performance and handle plug-and-play events. This study provides insight into a coalitional MPC strategy based on optimized tubes that ha...

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 fl...

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...

Model Predictive Control (MPC) has recently gained increasing interest in the adaptive management of water resources systems due to its capability of incorporating disturbance forecasts into real-time optimal control problems. Yet, related literature is scattered with heterogeneous applications, case-specific problem settings, and results that are...

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 stochastic model predictive control (SMPC) strategy to maximize the economic profit of a greenhouse crop production. The strategy consists of an optimization problem that is solved with a multi-scenario MPC formulation (MS-MPC). It considers the uncertainty of market price by using its historical evolution per year as multiple...

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 measureme...

In this paper, 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 paper focuses on human modeling and analysis for the passivity-based control archite...

This article focuses on the improvement of the real-time operation of the microgrid based on model predictive control (MPC), taking into account the stochastic nature of renewable resources and demand, as well as fault-tolerant mechanisms. Thus, a fault-tolerant strategy (FTS) module is inserted into the control loop, which is devoted to fault diag...

A reputation-based consensus algorithm taking full advantage of the blockchain technology is proposed so that each networked entity has a reputation level that increases or decreases depending on its past behavior. In particular, there is a verification phase within the blockchain smart contracts that decides the reputation update for each agent in...

Electric companies need to plan carefully the updates in their distribution power networks, assessing not only the expected impact on supply quality indicators, but also the cost of the different possibilities considered. To this end, we propose a planning method to improve the quality of supply in distribution power networks by upgrading devices s...

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...

Unmanned Surface Vehicles (USVs) are used to collect data of physicochemical parameters used to determine the degradation of freshwater resources. An optimal strategy based on a Nonlinear set-based Model Predictive Control (NMPC) is designed to improve the control of the USVs. This work offers a theoretical novel formulation of NMPC and explains th...

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...

Systems with elements linked via a communication network are vulnerable to communication problems and attacks of malicious agents, with potentially harmful consequences for performance and stability. This paper proposes a stochastic Model Predictive Control (MPC) scheme to deal with two different sources of uncertainties simultaneously, namely, pac...

Digital twins of hydrographical networks can be designed based on simulators. They aim not only at reproducing with accurate dynamics of the rivers and canals but also to analyze past events, to design, test, and compare new control algorithms. A delicate stage is an estimation of uncontrolled in/outputs along the canal during a specific event. Obs...

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...

In a networked control architecture, the semivalues of a coalitional game where links are the players can be used to provide information regarding their relevance. The linear relationship between the characteristic function of the game and the semivalues can be exploited to impose constraints on the design of the corresponding networked controllers...

Electric vehicles (EVs) are gaining attention because they are environmentally friendly. Also, EVs can use in-hub motors, which can be independently controlled, improving maneuverability and allowing to set more ambitious control goals. In this paper, the lateral motion of an EV is controlled using the direct yaw control (DYC) method. The proposed...

The vulnerability of conventional operational systems in agricultural water distribution systems becomes controversial under successive water shortages. Accordingly, inadequate, unfair, and unreliable surface water distribution has led to crop yield reduction and economic damage. To address these issues, a novel configuration of an automated operat...

Inventory management is an essential task in a hospital that the pharmacy department has to carry out. It is a difficult problem that involves different and contradictory optimization criteria. Also, the problem becomes more challenging due to issues such as delays and constraints that naturally arise in this context. The chapter presents advanced...

The poor performance of surface irrigation water distribution systems in terms of reliability, sufficiency, and timely delivery makes researchers develop and employ new methods to reduce its consequent challenges, including environmental, energy, and groundwater withdrawal issues. In this regard, many model-based control systems have been considere...

Nowadays, pressurized irrigation systems have been developing in farms to increase water use efficiency that are successful when the inflow is accurately supplied from water sources. In large irrigation networks, water conveyance and distribution systems are mainly open channels facing several uncertainties. Therefore, water delivery to farms is of...

Coalitional control is a type of distributed control characterized by the dynamic adjustment of the overall controller structure so that only strongly coupled agents interact with each other. In particular, local controllers merge into cooperative coalitions (or clusters) only when it improves global performance, thus reducing the overall cooperati...

Groundwater extraction from aquifers is the primary approach for supplying agricultural water demand due to the inadequate, unfair, and unreliable distribution of surface water (SW) systems. In this regard, the present study developed an automated operating system for conjunctive surface and groundwater (GW) resources. By centralized model predicti...

Applying a stabilizing model predictive control to a non-linear system is presented in this work. For this purpose, the quadruple-tank system has been considered for which a precise control benchmark was available and worked on previously. We could design a multi-model for the mentioned benchmark and to ensure the asymptotic stability of this non-l...

The assessment of the quality of water can be shortly defined as the analysis of its physical, chemical and biological characteristics in order to determine the degradation of freshwater resources. In this context, one of the latest technological methods for real-time data acquisition comes from the use of unmanned vehicles (aerial, surface and und...

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...

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...

Distributed model predictive control (DMPC) schemes have become a popular choice for networked control problems. Under this approach, local controllers use a model to predict its subsystem behavior during a certain horizon so as to find the sequence of inputs that optimizes its evolution according to a given criterion. Some convenient features of t...

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...

In this paper, we present an analysis of the vulnerability of a distributed model predictive control (DMPC) scheme in the context of cyber-security. We consider different types of the so-called insider attacks. In particular, we consider the situation where one of the local controllers sends false information to others to manipulate costs for its o...

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...

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...

Digital twins of hydrographical networks can be designed based on simulators. They aim not only at reproducing with accurate dynamics of the rivers and canals but also to analyze past events, to design, test, and compare new control algorithms. A delicate stage is an estimation of uncontrolled in/outputs along the canal during a specific event. Obs...

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...

Hydrographical systems which are mainly comprised of dams, rivers, channels, etc. are in the category of large-scale networks. These systems are not only complex systems in case of consisting of different hydraulic devices such as pumps or gates, but also they are in exposure to complicated circumstances like different demands, unknown inputs, drou...

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...

An algorithm for mapping Direct Normal Irradiance (DNI) in thermosolar power plants using a Mobile Robotic Sensor Network (RSN) is presented. The algorithm selects measurement spots and allocates the RSN accordingly to carry out the dynamic estimation of DNI. A generic thermosolar power plant with a fleet of vehicles is used as a simulated case stu...

Archimedes Screw Turbines (ASTs) can become a popular device to generate electricity from hydraulic power at very low-head or nearly zero-head places. In this article, the performance of ASTs is numerically investigated using Computational Fluid Dynamics (CFD) to assess different screw rotation speeds, volume flow rates, and inclination angles. The...

In this paper a coalitional control and observation scheme is presented in which the coalitions are changed online by enabling and disabling communication links. Transitions between coalitions are made to best balance overall system performance and communication costs. Linear Matrix Inequalities are used to design the controller and observer, guara...

We present a solution to deal with information package dropouts in distributed controllers for large-scale networks. We do this by leveraging the System Level Synthesis approach, a control framework particularly suitable for large-scale networks that addresses information exchange in a very transparent manner. To this end, we propose two different...

This work presents a hierarchical distributed model predictive control approach for multiple agents with cooperative negotiations based on fuzzy inference. Specifically, a fuzzy-based two-layer control architecture is proposed. In the lower control layer, there are pairwise negotiations between agents according to the couplings and the communicatio...

Operational management of agricultural water based on an economic perspective was investigated as a sustainable approach in water shortage periods. Accordingly, an automatic water distribution system was coupled with the Positive Mathematical Programming economic model for a sustainable agricultural water operation in the Roodasht irrigation networ...

This article presents a method based on linear matrix inequalities (LMIs) for designing a modular feedback control law, whose synthesis guarantees the system stability, while switching to different network topologies. Such stability is achieved by means of a common Lyapunov function to all network admissible configurations. Several mechanisms to re...

In this paper, we introduce a learning approach for the controller structure in coalitional model predictive control (MPC) schemes. In this context, the local control entities can dynamically perform in a decentralized manner or assemble into groups of controllers that coordinate their control actions, i.e., coalitions. Such control strategy aims a...

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...