Núcleo de control y diseño de controladores modulares en entornos distribuidos

Los sistemas empotrados tienen un amplio rango de aplicabilidad en muchos sectores y su importancia crece continuamente. Uno de los campos de aplicación incluye la realización de tareas de control. La heterogeneidad de los sistemas actuales, formados por múltiples componentes de diferentes características conectados en red, sugiere el desarrollo de sistemas de control distribuido en los que las distintas funciones del control se implementen a diferentes niveles. La consideración de sistemas distribuidos con presencia de redes de comunicación, unido a potencia de cálculo limitada, implica la necesidad de considerar la realización del control en condiciones no convencionales, tales como un control local que garantice la seguridad, controles alternativos en función de la disponibilidad de recursos, activación de distintos modos de funcionamiento que garanticen una degradación admisible de prestaciones ante la presencia de retardos, pérdidas de medidas o tiempo excesivo de cálculo. El núcleo de control, asimilable al núcleo de un sistema operativo, se define como el código mínimo que debe ejecutarse en una aplicación de control para que el funcionamiento sea seguro, aunque pueda presentar una fuerte degradación de prestaciones o incluso evolucionar hacia un estado seguro de desconexión. El núcleo de control permite la modularidad y adaptación del sistema, así como la capacidad de desarrollo rápido de aplicaciones de control mediante servicios de soporte (middleware), necesarios para ofrecer a los algoritmos de control soporte para sistemas distribuidos, computación ubicua, movilidad de código y restricciones de tiempo real. El objetivo de la tesis es la creación de una estrategia de control distribuida, con elementos empotrados, utilizando el núcleo de control, en el que se utilicen controladores digitales de altas prestaciones en sistemas con capacidad de cómputo limitada. Además, el sistema de control debe hacer frente a los problemas mencionados anteriormente de pérSimarro Fernández, R. (2011). Núcleo de control y diseño de controladores modulares en entornos distribuidos [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/11405Palanci

Comparative Study of Optimal Multivariable LQR and MPC Controllers for Unmanned Combat Air Systems in Trajectory Tracking

[EN] Guidance, navigation, and control system design is, undoubtedly, one of the most relevant issues in any type of unmanned aerial vehicle, especially in the case of military missions. This task needs to be performed in the most efficient way possible, which involves trying to satisfy a set of requirements that are sometimes in opposition. The purpose of this article was to compare two different control strategies in conjunction with a path-planning and guidance system with the objective of completing military missions in the most satisfactory way. For this purpose, a novel dynamic trajectory-planning algorithm is employed, which can obtain an appropriate trajectory by analyzing the environment as a discrete 3D adaptive mesh and performs a softening process a posteriori. Moreover, two multivariable control techniques are proposed, i.e., the linear quadratic regulator and the model predictive control, which were designed to offer optimal responses in terms of stability and robustness.This work was partially funded by project RTI2018-096904-B-I00 from the Spanish Ministry of Economy and by project AICO/2019/055 from Generalitat Valenciana.Ortiz, A.; Garcia-Nieto, S.; Simarro Fernández, R. (2021). Comparative Study of Optimal Multivariable LQR and MPC Controllers for Unmanned Combat Air Systems in Trajectory Tracking. Electronics. 10(3):1-31. https://doi.org/10.3390/electronics1003033113110

Control kernel based adaptive control implementation

[EN] A control system with distributed computing resources always should guarantee the safe control of the plant. In this contribution, the concept of control kernel is used for that purpose. Two types of nodes with different resources are defined: the powerful server node and the resource-constrained light node. This architecture allows to split the control tasks into two blocks. Those demanding strong computing resources are allocated in the server nodes and those compelling tasks required to ensure the safety of the controlled plant are allocated in the light nodes. Resource limitations lead to control adaptation. Two simple applications illustrate some of the benefits of this architecture with one server node and one light node, even the architecture can be extended to several nodes. In the first case, an adaptive control is implemented in the server node, providing the control algorithm to the light node, which is also able to compute a local safe control action. In the second experiment, two different control tasks requiring different resources are implemented in a mobile robot control. To keep bounded the computing time at the local level, the supervisor decides the time allocated to each activity, providing the resulting controller to the light node.This work has been partially granted by Conselleria de Educación Generalitat Valenciana, under PROMETEO project number 2008-088, and Ministerio de Ciencia e Innovaci´on under COBAMI project DPI2011-28507-C02-01/02.Simarro Fernández, R.; Albertos Pérez, P.; Simó Ten, JE. (2013). Control kernel based adaptive control implementation. SIGBED review. 10(1):24-28. doi:10.1145/2492385.2492389S242810

Smooth 3D Path Planning by Means of Multiobjective Optimization for Fixed-Wing UAVs

[EN] Demand for 3D planning and guidance algorithms is increasing due, in part, to the increase in unmanned vehicle-based applications. Traditionally, two-dimensional (2D) trajectory planning algorithms address the problem by using the approach of maintaining a constant altitude. Addressing the problem of path planning in a three-dimensional (3D) space implies more complex scenarios where maintaining altitude is not a valid approach. The work presented here implements an architecture for the generation of 3D flight paths for fixed-wing unmanned aerial vehicles (UAVs). The aim is to determine the feasible flight path by minimizing the turning effort, starting from a set of control points in 3D space, including the initial and final point. The trajectory generated takes into account the rotation and elevation constraints of the UAV. From the defined control points and the movement constraints of the UAV, a path is generated that combines the union of the control points by means of a set of rectilinear segments and spherical curves. However, this design methodology means that the problem does not have a single solution; in other words, there are infinite solutions for the generation of the final path. For this reason, a multiobjective optimization problem (MOP) is proposed with the aim of independently maximizing each of the turning radii of the path. Finally, to produce a complete results visualization of the MOP and the final 3D trajectory, the architecture was implemented in a simulation with Matlab/Simulink/flightGear.The authors would like to acknowledge the Spanish Ministerio de Ciencia, Innovacion y Universidades for providing funding through the project RTI2018-096904-B-I00 and the local administration Generalitat Valenciana through projects GV/2017/029 and AICO/2019/055. Franklin Samaniego thanks IFTH (Instituto de Fomento al Talento Humano) Ecuador (2015-AR2Q9209), for its sponsorship of this work.Samaniego, F.; Sanchís Saez, J.; Garcia-Nieto, S.; Simarro Fernández, R. (2020). Smooth 3D Path Planning by Means of Multiobjective Optimization for Fixed-Wing UAVs. Electronics. 9(1):1-23. https://doi.org/10.3390/electronics9010051S12391Kyriakidis, M., Happee, R., & de Winter, J. C. F. (2015). Public opinion on automated driving: Results of an international questionnaire among 5000 respondents. Transportation Research Part F: Traffic Psychology and Behaviour, 32, 127-140. doi:10.1016/j.trf.2015.04.014Münzer, S., Zimmer, H. D., Schwalm, M., Baus, J., & Aslan, I. (2006). Computer-assisted navigation and the acquisition of route and survey knowledge. Journal of Environmental Psychology, 26(4), 300-308. doi:10.1016/j.jenvp.2006.08.001Morales, Y., Kallakuri, N., Shinozawa, K., Miyashita, T., & Hagita, N. (2013). 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(2016). Attitude-based dynamic and kinematic models for wheels of mobile robot on deformable slope. Robotics and Autonomous Systems, 75, 161-175. doi:10.1016/j.robot.2015.10.006Mekonnen, G., Kumar, S., & Pathak, P. M. (2016). Wireless hybrid visual servoing of omnidirectional wheeled mobile robots. Robotics and Autonomous Systems, 75, 450-462. doi:10.1016/j.robot.2015.08.008Xu, J., Wang, M., & Qiao, L. (2015). Dynamical sliding mode control for the trajectory tracking of underactuated unmanned underwater vehicles. Ocean Engineering, 105, 54-63. doi:10.1016/j.oceaneng.2015.06.022Gafurov, S. A., & Klochkov, E. V. (2015). Autonomous Unmanned Underwater Vehicles Development Tendencies. Procedia Engineering, 106, 141-148. doi:10.1016/j.proeng.2015.06.017Qi, X., & Cai, Z. (2018). Three-dimensional formation control based on nonlinear small gain method for multiple underactuated underwater vehicles. 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Control-Oriented Modeling of the Cooling Process of a PEMFC-Based u-CHP System

[EN] Micro-combined heat and power systems (¿-CHP) based on proton exchange membrane fuel cell stacks (PEMFC) are capable of supplying electricity and heat for the residential housing sector with a high energy efficiency and a low level of CO2 emissions. For this reason, they are regarded as a promising technology for coping with the current environmental challenges. In these systems, the temperature control of the stack is crucial, since it has a direct impact on its durability and electrical efficiency. In order to design a good temperature control, however, a dynamic model of the ¿-CHP cooling system is required. In this paper, we present a model of the cooling system of a PEMFC-based ¿-CHP system, which is oriented to the design of the temperature control of the stack. The model has been developed from a ¿-CHP system located in the laboratory of our research team, the predictive control and heuristic optimization group (CPOH). It is based on first principles, dynamic, non-linear, and has been validated against the experimental data. The model is implemented in Matlab/Simulink and the adjustment of its parameters was carried out using evolutionary optimization techniques. The methodology followed to obtain it is also described in detail. Both the model and the test data used for its adjustment and validation are accessible to anyone who wants to consult them. The results show that the model is able to faithfully represent the dynamics of the ¿-CHP cooling system, so it is appropriate for the design of the stack temperature controlThis work was supported in part by the Ministerio de Economia y Competitividad, Spain, under Grant DPI2015-71443-R and Grant RTI2018-096904-B-I00, and in part by the Local Administration Generalitat Valenciana under Project GV/2017/029Navarro-Giménez, S.; Herrero Durá, JM.; Blasco, X.; Simarro Fernández, R. (2019). Control-Oriented Modeling of the Cooling Process of a PEMFC-Based u-CHP System. IEEE Access. 7:95620-95642. https://doi.org/10.1109/ACCESS.2019.2928632S9562095642

Design and Experimental Validation of the Temperature Control of a PEMFC Stack by Applying Multiobjective Optimization

[EN] The current environmental challenges require the implementation of environmentally friendly energy production systems. In this context, proton exchange membrane fuel cell stacks (PEMFC) represent, due to their high electrical efficiency and their low level of CO2 emissions, a promising alternative technology. However, there are still many technical aspects that need to be improved before they become a commercial reality. One of them is the temperature control of the stack, since its electrical efficiency and its lifetime depend on the performance of this control. In this work, we design a multiloop PID control of the temperature of a PEMFC stack and validate it experimentally. The stack is the prime mover of a micro combined heat and power system (micro-CHP). For this task, we use a previously developed nonlinear model and apply a multiobjective optimization methodology. To assess its performance, the PID control is compared to a second PID control designed with a linearized model. The results show, on the one hand, the importance of having a nonlinear model valid in a wide operation range for the correct design of the temperature control of a PEMFC stack and, on the other hand, the advantages of applying a multiobjective optimization methodology to this problem.This work was supported in part by the Spanish Ministry of Science, Innovation, and Universities under Grant RTI2018-096904-B-I00, and in part by the Generalitat Valenciana Regional Government under Project AICO/2019/055.Navarro-Giménez, S.; Herrero Durá, JM.; Blasco, X.; Simarro Fernández, R. (2020). Design and Experimental Validation of the Temperature Control of a PEMFC Stack by Applying Multiobjective Optimization. IEEE Access. 8:183324-183343. https://doi.org/10.1109/ACCESS.2020.3029321S183324183343

Multivariable controller design for the cooling system of a PEM fuel cell by considering nearly optimal solutions in a multi-objective optimization approach

[EN] This paper presents a design for the multivariable control of a cooling system in a PEM (proton exchange membrane) fuel cell stack. This system is complex and challenging enough: interactions between variables, highly nonlinear dynamic behavior, etc. This design is carried out using a multiobjective optimization methodology. There are few previous works that address this problem using multiobjective techniques. Also, this work has, as a novelty, the consideration of, in addition to the optimal controllers, the nearly optimal controllers nondominated in their neighborhood (potentially useful alternatives). In the multiobjective optimization problem approach, the designer must make decisions that include design objectives; parameters of the controllers to be estimated; and the conditions and characteristics of the simulation of the system. However, to simplify the optimization and decision stages, the designer does not include all the desired scenarios in the multiobjective problem definition. Nevertheless, these aspects can be analyzed in the decision stage only for the controllers obtained with a much less computational cost. At this stage, the potentially useful alternatives can play an important role. These controllers have significantly different parameters and therefore allow the designer to make a final decision with additional valuable information. Nearly optimal controllers can obtain an improvement in some aspects not included in the multiobjective optimization problem. For example, in this paper, various aspects are analyzed regarding potentially useful solutions, such as (1) the influence of certain parameters of the simulator; (2) the sample time of the controller; (3) the effect of stack degradation; and (4) the robustness. Therefore, this paper highlights the relevance of this in-depth analysis using the methodology proposed in the design of the multivariable control of the cooling system of a PEM fuel cell. This analysis can modify the final choice of the designer.This study was supported in part by the Ministerio de Ciencia, Innovacion y Universidades (Spain) (grant no. RTI2018-096904-B-I00) and by the Generalitat Valenciana regional government through project AICO/2019/055.Pajares-Ferrando, A.; Blasco, X.; Herrero Durá, JM.; Simarro Fernández, R. (2020). Multivariable controller design for the cooling system of a PEM fuel cell by considering nearly optimal solutions in a multi-objective optimization approach. Complexity. 2020:1-17. https://doi.org/10.1155/2020/8649428S1172020Gunantara, N. (2018). A review of multi-objective optimization: Methods and its applications. Cogent Engineering, 5(1), 1502242. doi:10.1080/23311916.2018.1502242Engau, A., & Wiecek, M. M. (2007). 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A New Point of View in Multivariable Controller Tuning Under Multiobjective Optimization by Considering Nearly Optimal Solutions. IEEE Access, 7, 66435-66452. doi:10.1109/access.2019.2915556Fredriksson, A., Forsgren, A., & Hårdemark, B. (2011). Minimax optimization for handling range and setup uncertainties in proton therapy. Medical Physics, 38(3), 1672-1684. doi:10.1118/1.3556559Lee, J., & Johnson, G. E. (1993). Optimal tolerance allotment using a genetic algorithm and truncated Monte Carlo simulation. Computer-Aided Design, 25(9), 601-611. doi:10.1016/0010-4485(93)90075-yAndújar, J. M., & Segura, F. (2009). Fuel cells: History and updating. A walk along two centuries. Renewable and Sustainable Energy Reviews, 13(9), 2309-2322. doi:10.1016/j.rser.2009.03.015Mehta, V., & Cooper, J. S. (2003). Review and analysis of PEM fuel cell design and manufacturing. Journal of Power Sources, 114(1), 32-53. doi:10.1016/s0378-7753(02)00542-6De las Heras, A., Vivas, F. J., Segura, F., Redondo, M. J., & Andújar, J. M. (2018). Air-cooled fuel cells: Keys to design and build the oxidant/cooling system. Renewable Energy, 125, 1-20. doi:10.1016/j.renene.2018.02.077Kandlikar, S. G., & Lu, Z. (2009). Thermal management issues in a PEMFC stack – A brief review of current status. Applied Thermal Engineering, 29(7), 1276-1280. doi:10.1016/j.applthermaleng.2008.05.009Yan, Q., Toghiani, H., & Causey, H. (2006). Steady state and dynamic performance of proton exchange membrane fuel cells (PEMFCs) under various operating conditions and load changes. Journal of Power Sources, 161(1), 492-502. doi:10.1016/j.jpowsour.2006.03.077Maghanki, M. M., Ghobadian, B., Najafi, G., & Galogah, R. J. (2013). Micro combined heat and power (MCHP) technologies and applications. Renewable and Sustainable Energy Reviews, 28, 510-524. doi:10.1016/j.rser.2013.07.053Notter, D. A., Kouravelou, K., Karachalios, T., Daletou, M. K., & Haberland, N. T. (2015). 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Recursive Rewarding Modified Adaptive Cell Decomposition (RR-MACD): A Dynamic Path Planning Algorithm for UAVs

[EN] A relevant task in unmanned aerial vehicles (UAV) flight is path planning in 3D environments. This task must be completed using the least possible computing time. The aim of this article is to combine methodologies to optimise the task in time and offer a complete 3D trajectory. The flight environment will be considered as a 3D adaptive discrete mesh, where grids are created with minimal refinement in the search for collision-free spaces. The proposed path planning algorithm for UAV saves computational time and memory resources compared with classical techniques. With the construction of the discrete meshing, a cost response methodology is applied as a discrete deterministic finite automaton (DDFA). A set of optimal partial responses, calculated recursively, indicates the collision-free spaces in the final path for the UAV flight.The authors would like to acknowledge the Spanish Ministry of Economy and Competitiveness for providing funding through the project DPI2015-71443-R and the local administration Generalitat Valenciana through the project GV/2017/029. Franklin Samaniego thanks IFTH (Instituto de Fomento al Talento Humano) Ecuador (2015-AR2Q9209), for its sponsorship of this work.Samaniego-Riera, FE.; Sanchís Saez, J.; Garcia-Nieto, S.; Simarro Fernández, R. (2019). Recursive Rewarding Modified Adaptive Cell Decomposition (RR-MACD): A Dynamic Path Planning Algorithm for UAVs. Electronics. 8(3):1-21. https://doi.org/10.3390/electronics8030306S12183Valavanis, K. P., & Vachtsevanos, G. J. (Eds.). (2015). 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Co-simulation platform for geometric design, trajectory control and guidance of racing drones

[EN] The design of racing drones brings quite a thrilling challenge from a flight dynamics point of view. This work aims to offer a single-based simulation platform combining its geometric design, trajectory control, and guidance of racing drones. Also, it is reckoned from a pilot¿s view in a classic FPV competition. Hence, it is an active platform for studying racing drones¿ design founded on dynamics, with fifteen different drone models. It is one of the few existing platforms that combine all aspects of racing drones in a single simulation environment. Also, it is open access via Matlab Central - File Exchange.This work was partially supported by proyect PID2020-119468RA-I00 funded by MCIN/AEI/10.13039/501100011033.Castiblanco Quintero, J.; Garcia-Nieto, S.; Simarro Fernández, R.; Salcedo-Romero-De-Ávila, J. (2022). Co-simulation platform for geometric design, trajectory control and guidance of racing drones. International Journal of Micro Air Vehicles. 14:1-20. https://doi.org/10.1177/175682932211437851201

Experimental study on the dynamic behaviour of drones designed for racing competitions

[EN] Drones designed for racing usually feature powerful miniaturised electronics embedded in fairly light and strong geometric composite structures. The main objective of this article is to analyse the behaviour of various models of racing drones and their geometrical structures (airframes). Two approaches have been made: (i) an analysis of the information collected by a set of speed and time sensors located on an indoor race track and using a statistical technique (box and whiskers diagram) and (ii) an analysis of the know-how (flight sensations) of a group of racing pilots using a series of technical interviews on the behaviour of their drones. By contrasting these approaches, it has been possible to validate numerically the effects of varying the arm angles, as well as lengths, on a test race track and relate the geometry of these structures to racing behaviourThe author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was partially supported by project RTI2018-096904-B-I00 from the Spanish Ministry of Economy, and by project AICO/2019/055 from Generalitat Valenciana.Castiblanco Quintero, JM.; Garcia-Nieto, S.; Simarro Fernández, R.; Salcedo-Romero-De-Ávila, J. (2021). Experimental study on the dynamic behaviour of drones designed for racing competitions. International Journal of Micro Air Vehicles. 13:1-22. https://doi.org/10.1177/175682932110057571221