Ponencias (Ingeniería de Sistemas y Automática)

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

Examinar

Mostrando 1 - 20 de 345

A CLT on the SINR of the diagonally loaded Capon/MVDR beamformer
(Institute of Electrical and Electronics Engineers (IEEE), 2011) Rodríguez Rubio, Francisco; Mestre, Xavier; Hachem, Walid; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
The Capon or minimum variance distorsionless response (MVDR) beamformer is a prominent example of spatial filtering structure in sensor array signal processing. Typical implementations of this beamformer are based on a regularized or diagonally-loaded version of the sample covariance matrix estimator. Conventionally, the performance evaluation of the beamformer relies on a measure of the signal-to-interference-plus-noise ratio (SINR) at the filter output. In this paper, we establish a central limit theorem characterizing the output SINR performance of MVDR beamforming implementations employing diagonal loading for both spatially and temporally correlated Gaussian observations.
A Coalitional Model Predictive Control Approach for Heterogeneous Cellular Networks*
(Institute of Electrical and Electronics Engineers (IEEE), 2020) Masero Rubio, Eva; A. Fletscher, Luís; Maestre Torreblanca, José María; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
Heterogeneous cellular networks (HetNets) are large-scale systems that comprise numerous base stations interacting with a significant number of users of diverse types. Finding a trade-off between energy consumption and quality of service is one of the major challenges in these networks. To deal with this issue, a coalitional model predictive control (MPC) approach is proposed for a HetNet powered by renewable power sources, and compared in simulation with the traditional best-signal level mechanism and the centralized MPC method. Furthermore, other key performance indicators associated with grid consumption such as the number of served users and transmission rates are also evaluated.
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.
A decision support system for bidding process
(Elsevier, 2002) Zafra Cabeza, Ascensión; Ridao Carlini, Miguel Ángel; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
This article has been developed in the frame of an IST European Project where Companies and Universities of several countries of Europe have collaborated. The work presents a Decision Support System (DSS) to provide help in the bidding process. Critical decisions as bid/no bid make/buy or decision of best final proposal have been realised. The tool performs a risk analysis and it uses the results in all the DSS phases.
A distributed model predictive control scheme with robustness against noncompliant controllers.
(Institute of Electrical and Electronics Engineers (IEEE), 2018) Maestre Torreblanca, José María; Trodden, Paul A.; Ishii, Hideaki; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
A tube-based distributed model predictive control (DMPC) scheme is proposed for dynamically coupled linear systems. The control scheme is designed to guarantee local performance even when neighboring controllers are not complying with the requirements of the algorithm (e.g., they are malicious or faulty). The resulting conservativeness is minimized, for controllers aim to minimize their state and input constraint sets to reduce mutual disturbances. Also, sufficient conditions for feasibility and exponential stability are given. Finally, these ideas are illustrated and assessed with respect to other robust DMPC via a simulated example.
A Genetic Algorithm for Assembly Sequence Planning
(Springer, 2003) Valle Sevillano, Carmelo del; Martínez Gasca, Rafael; Toro Bonilla, Miguel; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
This work presents a genetic algorithm for assembly sequence planning. This problem is more difficult than other sequencing problems that have already been tackled with success using these techniques, such as the classic Traveling Salesperson Problem (TSP) or the Job Shop Scheduling Problem (JSSP). It not only involves the arranging of tasks, as in those problems, but also the selection of them from a set of alternative operations. Two families of genetic operators have been used for searching the whole solution space. The first includes operators that search for new sequences locally in a predetermined assembly plan, that of parent chromosomes. The other family of operators introduces new tasks in the solution, replacing others to maintain the validity of chromosomes, and it is intended to search for sequences in other assembly plans. Furthermore, some problem-based heuristics have been used for generating the individuals in the population.
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.
A high-performance linear actuator laboratory set-up as an educative tool in control and electronic instrumentation subjects
(2006-07) Arahal, Manuel R.; Toral, S. L.; Barrero, Federico; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. Departamento de Ingeniería Electrónica
This paper presents a high-performance linear actuator for positioning control experiments to be used in control and electronic instrumentation subjects. The laboratory set-up and the educative experiments are described with some detail showing its possibilities for different engineering courses
A Java based simulation for basic control
(Elsevier, 2006) Limón Marruedo, Daniel; Salas Gómez, Francisco; Rodríguez Ramírez, Daniel; Alamo, Teodoro; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
In this paper we present a java based simulator for control education in basiccourses. The application has been developed using the well known tool Easy JavaSimulation.The objective of the application is to help the student to learn the design of classiccontrollers such as P,PI, PID, etc testing the tuning procedures to control the position ofan antenna controlled by a DC motor. Thus the application allows the student to choosethe parameters of the antenna and the DC motor, to choose the controller to be used andits parameters and finally to simulate the closed loop system observing the evolution ofthe signals as well as a 3-D view. Furthermore, in order to show the real behavior of thesystem, dead zone, saturation, disturbances and non-linearities can be added to the model.This application has been used by the authors to teach a basic control course at EscuelaSuperior de Ingenieros (University of Seville) as virtual laboratory.Moreover, since the application is java based, this can be used by the students from theauthors’ web pages and this can also be installed in the student’s laptop (whichever theplatform is) by downloading it from the authors web page (Limon and Salas, 2003
A model for assembly sequence planning in a multirobot environment
(Elsevier, 2002) Valle Sevillano, Carmelo del; Camacho, Eduardo F.; Toro Bonilla, Miguel; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos
This paper presents a model for the selection of optimal assembly sequences for a product in multirobot systems. The objective of the plan is the minimization of the total assembly time (makespan). To meet this objective, the model takes into account, in addition to the assembly times and resources for each task, the times needed to change tools in the robots, and the delays due to the transportation of intermediate subassemblies between different machines. An A* algorithm that solves the problem is also presented, which starts from the And/Or graph for the product (compressed representation of all feasible assembly plans).
A modifier-adaptation approach to the one-layer economic MPC
(Elsevier, 2020) Vergara-Dietrich, José D.; Mirasierra Calleja, Victor; Ferramosca, Antonio; Normey Rico, Julio Elías; Limón Marruedo, Daniel; ; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Fondo Europeo de Desarrollo Regional (FEDER); Ministerio de Economía, Industria y Competitividad (MINECO). España; Universidad de Sevilla. TEP950: Estimación, Predicción, Optimización y Control
In this paper, we address the problem of modeling error in economically optimal control. A single layer controller is proposed that integrates the economical part of the Real Time Optimization (RTO), the dynamic part of the Model Predictive Control (MPC) and the Modifier Adaptation strategy (MA), resulting in a controller with the following characteristics: a) recursive feasibility guarantee of the controller; b) asymptotic closed-loop stability for any change in the economic cost function; c) convergence guarantee to the economic optimum of the real plant (offset-free) for any change in the cost function of the controller; and d) simple implementation of the controller. We show the behaviour of the proposal by means of a motivating example that highlights the performance of the proposed algorithm
A modulation algorithm for inter-phase balancing in CHB Converters
(IEEE, 2017-04) Montero-Robina, Pablo; Gordillo Álvarez, Francisco; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Ministerio de Economía y Competitividad (MINECO). España; Universidad de Sevilla. TEP102: Ingeniería automática y robótica
This paper presents a simple modulation algorithm which accomplishes the voltage balance across the capacitors of a Cascaded H-bridge (CHB) converter using zero voltage injection. CHB converters are widely used in renewable energy production, especially in solar plants due to their modularity. This advantage can also become a problem when the power generated by the solar cell or consumed by a load is not equal among the three phases, leading to an unbalanced situation. The inter-phase unbalance refers to the voltage differences among the capacitors of different phases, for which a well-known technique to solve it consists of injecting a zero sequence voltage according to the power distribution. A simple modulation algorithm, which uses it, is presented in this paper including a mathematical proof. The proposed algorithm has been tested by simulation with a five-level CHB converter. At the end of the paper, a modification is introduced to improve the converter efficiency.
A multicriteria risk-based dss for bidding using mixed integer programming
(Elsevier, 2003) Zafra Cabeza, Ascensión; Ridao Carlini, Miguel Ángel; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
This work presents a Decision Support System to provide help in bidding processes. This phase of the project is characterised by a high level of uncertainty and it involves a huge expense in the preparation of the proposal and important mobilization of resources. In industrial practice, bids are usually evaluated on the basis of multiple criteria; this algorithm evaluates candidates according to different criteria configurations. A risk-based approach has been incorporated in the procedure in order to minimise an objective function that involves the mitigation actions of risks. Mitigation actions can own a discrete or continuous nature.
A new approach for Guaranteed ellipsoidal state estimation
(Elsevier, 2014) Ben Chabane, S.; Stoica Maniu, Cristina; Alamo, Teodoro; Camacho, Eduardo F.; Dumur, D.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
This paper proposes a new ellipsoid-based guaranteed state estimation approach for linear discrete-time systems with bounded perturbations and bounded measurement noise. This approach is based on the minimization of the radius of the ellipsoidal state estimation set. Firstly, the ellipsoidal state estimation is computed by off-line solving a Linear Matrix Inequality optimization problem. Secondly, a new online method is developed in order to improve the accuracy of the estimation but it leads to an increase of the online computation load. A new scaling technique is proposed to reduce the computation time, while keeping a good accuracy of the state estimation. An illustrative example is analyzed in order to show the advantages of the proposed approach.
A New Approach for Guaranteed State Estimation by Zonotopes
(Elsevier, 2011) Alamo, Teodoro; Camacho, Eduardo F.; Le, V.T.H.; Stoica Maniu, Cristina; Dumur, D.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
This paper proposes a methodology for guaranteed state estimation of linear discrete-time systems in the presence of bounded disturbances and noises. This aims at computing an outer approximation of the state estimation domain represented by a zonotope. A new criterion is used to reduce the size of the zonotope at each sample time. An illustrative example is analyzed in order to highlight the advantages of the proposed algorithm.
A New ℓ-step Neighbourhood Distributed Moving Horizon Estimator
(IEEE, 2021-12) Venturino, Antonello; Bertrand, Sylvain; Stoica Maniu, Cristina; Alamo, Teodoro; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. TEP950: Estimación, predicción, optimización y control; Universidad de Sevilla. TEP116: Automática y robótica industrial
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 to other approaches from the literature. Simultaneously, convergence of the estimation error is improved by means of spreading the information amongst neighbourhoods, which comes natural in the sliding window data present in the Moving Horizon Estimation paradigm.
A novel Controller for Grid-interfacing Solar Arrays through Five-level Diode-clamped Converters
(IEEE, 2018) Montero-Robina, Pablo; Gordillo Álvarez, Francisco; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. TEP102: Ingeniería Automática y Robótica
This paper presents an approach to control a grid-connected, five-level, diode-clamped converter (DCC) with solar arrays directly connected to each capacitor of the dc-link, On one hand, the control of such converters is challenging as the voltage imbalance among the capacitor may affect the power controller. On the other hand, when dealing with solar arrays, the dc voltage is a key point considering that the efficiency of the array highly depends on it. This article presents a solution where both aims are fulfilled: the desired capacitor voltages, set by the maximum power point tracking (MPPT) algorithm, are reached at the same time that these values are taken into account in the power controller. This is an unusual approach for five-level DCC that avoids the use of DC-DC stages, therefore it makes the system more affordable and avoids extra losses. Thanks to the capacitor voltage controller, proper power extraction from each solar array is achieved. The theoretical presentation of this approach is shown along with simulation results that validates its effectiveness.
A Novel Formulation of Economic Model Predictive Control for Periodic Operations
(IEEE, 2018) Wang, Ye; Muñoz de la Peña Sequedo, David; Puig, Vicenç; Cembrano, Gabriela; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática; Universidad de Sevilla. TEP950: Estimación, Predicción, Optimización y Control
This paper proposes a novel formulation of economic model predictive control (MPC) for linear systems with periodic operations. In this economic MPC design, the optimal periodic trajectory from an economic point of view is unknown, hence it is not possible to follow a standard control strategy in which the MPC uses this trajectory to define a terminal constraint to guarantee closed-loop convergence. The economic cost function is optimized with a periodicity constraint at each time step considering all periodic trajectories in a period including the current state. The recursive feasibility and closed-loop convergence to the optimal periodic trajectory are analyzed using the Karush-Kuhn-Tucker conditions. Finally, two simulations are provided to demonstrate the main results.
A Prediction approach to introduce dead-time process control in a basic control course
(Elsevier, 2006) Normey Rico, Julio Elías; Alamo, Teodoro; Camacho, Eduardo F.; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
This paper presents a methodology to introduce the control of dead-time processes using a simple and intuitive predictive approach. A trivial solutionfor the control of a process with a dead-time is first proposed. From this strategythe idea of the predictor based controller is derived. Open-loop predictors andclosed-loop ones are then used to analyze the obtained solution. A simple tuningof the proposed structure for a first order plus dead-time process together with apolynomial approximation of the dead-time allows to derive apidcontroller. Thus,the approach based on the idea of prediction can be used to interpret the use of apidto control a dead-time process. It is illustrated how the performance of thepidcontroller is limited by the modelling error introduced in the approximation. Thepresented approach gives a measurement of the achievable performance. Severalsimulation examples illustrate the results.
A probabilistic validation approach for penalty function design in stochastic model predictive control
(Elsevier B.V., 2020) Mammarella, Martina; Alamo, Teodoro; Lucía, Sergio; Dabbene, Fabrizio; Universidad de Sevilla. Departamento de Ingeniería de Sistemas y Automática
In this paper, we consider a stochastic Model Predictive Control able to account for effects of additive stochastic disturbance with unbounded support, and requiring no restrictive assumption on either independence nor Gaussianity. We revisit the rather classical approach based on penalty functions, with the aim of designing a control scheme that meets some given probabilistic specifications. The main difference with previous approaches is that we do not recur to the notion of probabilistic recursive feasibility, and hence we do not consider separately the unfeasible case. In particular, two probabilistic design problems are envisioned. The first randomization problem aims to design offline the constraint set tightening, following an approach inherited from tube-based MPC. For the second probabilistic scheme, a specific probabilistic validation approach is exploited for tuning the penalty parameter, to be selected offline among a finite-family of possible values. The simple algorithm here proposed allows designing a single controller, always guaranteeing feasibility of the online optimization problem. The proposed method is shown to be more computationally tractable than previous schemes. This is due to the fact that the sample complexity for both probabilistic design problems depends on the prediction horizon in a logarithmic way, unlike scenario-based approaches which exhibit linear dependence. The efficacy of the proposed approach is demonstrated with a numerical example.

Examinar

Examinando Ponencias (Ingeniería de Sistemas y Automática) por Título