Research line

Automatic Control Image

The AUTOMATIC CONTROL line develops basic and applied research in automatic control, with special emphasis on modelling, control and supervision of nonlinear, complex and/or large-scale systems.
The group has acquired specific expertise in the application of advanced control techniques to environmental resources management, specifically in the water and energy fields.

Head of line: Maria Serra Prat

Head of line

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Modelling and control of complex nonlinear systems

In order to design controllers for complex nonlinear systems, it is fundamental to have mathematical models of the systems' dynamic behaviour. Regarding dynamic modelling of complex nonlinear systems, the Control Group focuses on four subjects: models for multidomain systems using PHS formulation; distributed parameter models and their order reduction; experimental characterisation techniques combining the use of time and frequency responses of the dynamic system, conceived as diagnosis tools; the design of observers to be integrated in the control systems in order to improve the system performance and minimise the number of sensors. Regarding control system design, the work is based on the following advanced control techniques: passivity-based control, Optimal Control, Model Predictive Control, Variable Structure Control (VSC) and Linear Parameter Varying (LPV)-Robust Control.

Research area 1 of Automatic Control

Modelling and control of large-scale networked systems

In automation, it is more and more frequent to deal with large scale networked systems which are composed by a multitude of elements of diverse dynamical nature. Obtaining a mathematical model oriented to the management and control of such systems should take into account their real time operation and complex topology. Moreover, complementary considerations such as physical constraints, hybrid behaviour and bounded disturbances are also challenging topics in the study of this kind of systems.

Research area 2 of Automatic Control

Design and implementation of decision-support tools for resources management systems with multiple, heterogeneous constraints

A large variety of real-time resource allocation problems dealing with long- and medium-term resources management typically appear in public services and industry. Some examples are water management (both surface and pipeline systems), energy generation and distribution, and environmental planning. The operation of these systems requires dealing with multiple, heterogeneous constraints. Not just physical constraints are to be met, but also those imposed by regulations, operational practices, economy, ecology, etc. The overall aim is to step away from the classical trial-and-error-based simulation approach and create real problem-solving tools for optimal management of large-scale resources management problems.

Research area 3 of Automatic Control

Real-time Supervisory Control, Fault Diagnosis and Fault-Tolerance

Reliability is a feature required in modern control systems which implies the introduction of fault diagnosis and fault tolerant control modules that allow to know in real-time if there is any non-desired behaviour (fault) and activate some remedial action in order to keep the system in operation (fault tolerance). Complementary aspects as sensor/actuator location for achieving the desired fault diagnosis and tolerance are also addressed.

Research area 4 of Automatic Control

Applied Research

Theoretical knowledge is applied in real cases, in close collaboration with industry. Currently, research is mainly focused on four fields: modelling and control of systems based on Proton Exchange Membrane Fuel Cells based systems; modelling, control and management of electrical networks; design of optimal operational management of networked systems related to the urban water cycle and sensor data validation/reconstruction of instrumentation systems. The Control Group gives primary importance to the tasks of implementation and experimental validation of the proposed control and modelling methodologies. These final stages of the control design process are developed either in the industry or at the Institute's Laboratories: the Fuel Cells Laboratory and the Water Cycle Control Systems Lab.

Research area 5 of Automatic Control

These are the latest research projects of the Automatic Control research line:

These are the most recent publications (2024 - 2023) of the Automatic Control

  • A. Molavi, M. Serra and A.P. Husar. Improved supervisory controller design for a fuel cell hybrid electric vehicle. IEEE Transactions on Vehicular Technology, 73(4): 4918-4933, 2024.

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  • P. Cardona, R. Costa, V. Roda, J. Carroquino, L. Valiño, C. Ocampo-Martínez and M. Serra. Modelling and operation strategy approaches for on-site hydrogen refuelling stations. International Journal of Hydrogen Energy, 52: 49-64, 2024.

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  • T.P. Puleston, A. Cecilia, R. Costa and M. Serra. Nonlinear observer for online concentration estimation in vanadium flow batteries based on half-cell voltage measurements. Computers and Chemical Engineering, 185: 108664, 2024.

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  • A. Carrizosa, V. Puig and F. Nejjari. Safe motion planner for autonomous driving based on LPV MPC and reachability analysis. Control Engineering Practice, 147: 105932, 2024.

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  • J.A. Aguilar, D. Chanal, D. Chamagne, N. Yousfi, M. Péra, A.P. Husar and J. Andrade-Cetto. A hybrid control-oriented PEMFC model based on echo state networks and Gaussian radial basis functions. Energies, 17(2): 508, 2024.

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  • T.P. Puleston, M. Serra and R. Costa. Vanadium redox flow battery capacity loss mitigation strategy based on a comprehensive analysis of electrolyte imbalance effects. Applied Energy, 355: 122271, 2024, to appear.

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  • S. Zhang, V. Puig and S. Ifqir. Set-membership estimation of switched LPV systems: Application to fault/disturbance estimation. International Journal of Robust and Nonlinear Control, 34(7): 4509-4531, 2024.

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  • A. Luque, D. Parent, A. Colomé, C. Ocampo-Martínez and C. Torras. Model predictive control for dynamic cloth manipulation: Parameter learning and experimental validation. IEEE Transactions on Control Systems Technology, 32(4): 1254-1270, 2024.

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  • P. Irofti, L. Romero, F. Stoican and V. Puig. Learning dictionaries from physical-based interpolation for water network leak localization. IEEE Transactions on Control Systems Technology, 32(3): 755-766, 2023.

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  • C. Trapiello, L. Romero, J. Meseguer, V. Puig, G. Cembrano, B. Joseph, M. Sarrias, D. Saporta and M. Minoves. Automatic network response methodology for failure recovery or bursts in drinking water networks. Journal of Water Resources Planning and Management, 149(1): 04022073, 2023.

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  • Y.O. Eldigair, C. Kunusch and C. Ocampo-Martínez. Optimization-based thermal control strategy for auxiliary cooling circuits in fuel cell vehicles. IEEE Transactions on Transportation Electrification, 9(2): 2734-2743, 2023.

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  • A. Clemente, A. Cecilia and R. Costa. Online state of charge estimation for a vanadium redox flow battery with unequal flow rates. Journal of Energy Storage, 60: 106503, 2023.

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  • X. Fang, J. Blesa and V. Puig. Fault detection using data-driven LPV state estimation based on structural analysis and ANFIS, 2023 European Control Conference, 2023, Bucharest (Romania), pp. 1-6.

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  • S. Zhang, V. Puig and S. Ifqir. Zonotopic set-membership state estimation for switched LPV system, 2023 IFAC World Congress, 2023, Yokohama, pp. 9442-9447.

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  • M. Cugueró and V. Puig. Advances in the monitoring, diagnosis and optimisation of water systems. Sensors, 23(6): 3256, 2023.

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  • L. Romero, D. Alves, J. Blesa, G. Cembrano, V. Puig and E. Duviella. Leak detection and localization in water distribution networks: review and perspective. Annual Reviews in Control, 55: 392-419, 2023.

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  • A. Cecilia and R. Costa. Estimation of the liquid water saturation in PEM fuel cells: A low-power peaking-free dead-zone observer approach. ISA Transactions, 140: 368-384, 2023.

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  • Á. Ruiz, B. Escachx and R. Costa. Gestión de energía, mediante control predictivo, de un vehículo de pila de combustible, XLIV Jornadas de Automática, 2023, Zaragoza, Spain, pp. 358-363.

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  • J. Anderson, J. Moré, P.F. Puleston and R. Costa. Fuel cell module control based on Switched/Time-Based Adaptive Super-Twisting Algorithm: design and experimental validation. IEEE Transactions on Control Systems Technology, 31(1): 434-441, 2023.

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  • M. Marti, A. Cecilia and R. Costa. Modelling and estimation in lithium-ion batteries: a literature review. Energies, 16(19): 6846, 2023.

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  • B. Wang, R. Costa, N. Jing, O. de la Torre and X. Escaler. Modeling and adaptive parameter estimation for a piezoelectric cantilever beam. IEEE Transactions on Circuits and Systems I: Fundamental Theory and Applications, 70(1): 481-491, 2023.

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  • A. San-Miguel, V. Puig and G. Alenyà. Condition-based design of variable impedance controllers from user demonstrations. Control Engineering Practice, 140: 105658, 2023.

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  • Y. Xing, L. Bernadet, M. Torrell, A. Tarancón, R. Costa and J. Na. Offline and online parameter estimation of nonlinear systems: Application to a solid oxide fuel cell system. ISA Transactions, 133: 463-474, 2023.

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  • A. Clemente and R. Costa. Comparison of charging control techniques for electrochemical energy storage systems, 2023 IEEE International Conference on Emerging Technologies and Factory Automation, 2023, Sinaia (Romania), pp. 1-8.

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  • J. Anderson, J. Moré, P.F. Puleston, V. Roda and R. Costa. Control Super-Twisting con adaptación basada en cruce por cero. Análisis de estabilidad y validación. Revista Iberoamericana de Automática e Informática Industrial, 20(1): 104–114, 2023.

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  • C. Fustero, A. Clemente, R. Costa and C. Ocampo-Martínez. Energy management using predictive control and neural networks in microgrid with hybrid storage system, 2023 IEEE International Conference on Emerging Technologies and Factory Automation, 2023, Sinaia (Romania), pp. 1-8.

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  • A. Clemente, M. Montiel, F. Barreras, A. Lozano and R. Costa. Experimental validation of a vanadium redox flow battery model for state of charge and state of health estimation. Electrochimica Acta, 449: 142117, 2023.

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  • E. Caldarelli, A. Colomé, C. Ocampo-Martínez and C. Torras. Quadratic dynamic matrix control for fast cloth manipulation, 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2023, Detroit, MI, USA, pp. 8178-8185.

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  • P. Cardona, R. Costa, V. Roda, J. Carroquino, L. Valiño and M. Serra. Model predictive control of an on-site green hydrogen production and refuelling station. International Journal of Hydrogen Energy, 48(47): 17995-18010, 2023.

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  • T.P. Puleston, A. Cecilia, R. Costa and M. Serra. Vanadium redox flow batteries real-time State of Charge and State of Health estimation under electrolyte imbalance condition. Journal of Energy Storage, 68: 107666, 2023.

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  • J.L. Svensen, C. Sun, G. Cembrano and V. Puig. Model predictive control of urban drainage systems considering uncertainty. IEEE Transactions on Control Systems Technology, 31(6): 2968-2975, 2023.

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  • P. Fornaro, T.P. Puleston, P.F. Puleston, P. Battaiotto, R. Costa and M. Serra. Electric vehicle charging station based on wind energy: evaluation of the power profile for vanadium redox flow batteries estimation. IEEE Latin America Transactions , 21(9): 1056-1062, 2023.

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  • C. Trapiello, V. Puig and G. Cembrano. Reconfiguration of flow-based networks with back-up components using robust economic MPC. Journal of Process Control, 122: 100-112, 2023.

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  • A. Carrizosa, V. Puig and F. Nejjari. Zonotopic-tube-based LPV motion planner for safety coordination of autonomous vehicles, 22nd IFAC World Congress, 2023, Yokohama, pp. 2220-2225.

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  • J.P. Martínez, C. Ocampo-Martínez, N. Quijano and A. Ingimundarson. Microalgae production and maintenance optimization via mixed-integer model predictive control, 22nd IFAC World Congress, 2023, Yokohama, pp. 11100-11105.

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  • L. Romero, J. Blesa, G. Cembrano and V. Puig. A comparison between model-based and data-driven leak localization methods, 22nd IFAC World Congress, 2023, Yokohama, pp. 737-742.

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Fuel Cell Control Laboratory

The objective of the Laboratory is the validation and testing of control strategies of fuel cell based energy conversion systems. The facilities are equipped with a supervisor system which monitors necessary safety conditions. Each of the five fuel cell test stations is equipped with the necessary sensors and actuators to be able to operate in a safe and automated way, as well as to modify the working conditions that affect a fuel cell (humidity, temperature, flow, etc.).

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Research area 1 of Automatic Control

Water-cycle Control Systems Laboratory

The aim of this laboratory is to test and validate modelling and control developments for dynamic systems associated to the water cycle. Hence, it provides platforms of pressure, flow and level processes, over which it is possible to implement real-time advanced control strategies. This laboratory is also open to offer services to other teams in the research community.

Research area 2 of Automatic Control
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