Research line

Automatic Control

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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

Tech. transfer

Our activity finds applications in several fields through collaboration with our technological partners.

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Research projects

We carry out projects from the European Framework Programme and others national and international research programmes.
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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 (2026 - 2025) of the Automatic Control

  • L. Romero, P. Irofti, F. Stoican and V. Puig. Dual unscented Kalman filter architecture for sensor fusion in water networks leak localization. IEEE Transactions on Control Systems Technology, 34(1): 343-354, 2026.

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  • B. Garcia, P. Cardona, L. Valiño, C. Ocampo-Martínez, L. Siemon and M. Serra. Techno-economic analysis of a renewable hydrogen refuelling station network: The case study of Spain. International Journal of Hydrogen Energy, 198: 152325, 2026.

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  • J. Caballé, P. Segovia, C. Ocampo-Martínez and N. Quijano. Large-scale EV charging coordination: a detailed exploration of mean-field and reinforcement learning approaches. Control Engineering Practice, 168: 106669, 2026.

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  • P. Segovia, R. Ummels, T. van den Boom and V. Reppa. Multi-vessel placement in multi-chamber inland waterway transport locks using switching max-plus algebra. Ocean Engineering, 343(5): 123414, 2026.

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  • J.P. Arango, L. Etienne, E. Duviella, K. Langueh, P. Segovia and V. Puig. An observer-based tracking controller for one sided Lipschitz – quadratically inner bounded perturbed nonlinear systems. International Journal of Systems Science: 1–12, 2026, to appear.

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  • M. de Lange, P. Segovia, R. Negenborn and L. van Biert. Model predictive control for thermal stress-aware power modulation of solid oxide fuel cell systems. Energy Conversion and Management, 347: 120395, 2026.

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  • M. Arcila, C. Ocampo-Martínez and H. Alvarez. A detailed model deduction and parameter values for the Tennessee-Eastman benchmark. Brazilian Journal of Chemical Engineering, 2026, to appear.

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  • M. Arcila, C. Ocampo-Martínez and H. Alvarez. A phenomenological-based dynamic model of ethanol steam reforming for hydrogen production. International Journal of Hydrogen Energy, 222: 154199, 2026.

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  • M. Chen, R. Costa, C. Batlle and J. Na. Metal hydride storage tanks real-time state of charge estimation based on nonlinear observer with a non-observable subsystem. Applied Energy, 399: 126448, 2025.

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  • R. Nasri, J. Jamii, M. Mansouri, Z. Affi and V. Puig. A novel data-driven MPC framework using KDE and KPCA for autonomous vehicles. IEEE Access, 13: 109638-109656, 2025.

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  • J.C. Paredes, R. Costa, R. Vázquez, J.A. Flores-Campos and C.R. Torres. Experimental study on using biodiesel in hybrid electric vehicles . Energies, 18(7): 1621, 2025.

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  • M. Witczakc, D. Rotondo, M. Pazera and V. Puig. Output-feedback integrated fault-tolerant control for discrete-time systems subject to input and state constraints. European Journal of Control, 86: 101375, 2025.

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  • C. Conejo, V. Puig, B. Morcego, F. Navas and V. Milanés. Enhancing safety in autonomous vehicles using zonotopic LPV-EKF for fault detection and isolation in state estimation. Control Engineering Practice, 156: 106192, 2025.

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  • M. Zhou, Y. Zhang, J. Wang, T. Raïssi and V. Puig. Robust fault detection method based on interval neural networks optimized by ellipsoid bundles. Automatica, 176: 112233, 2025.

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  • M. Cardona and F.E. Serrano. Rehabilitation robotics. Kinematics, dynamics, and control techniques. Springer Nature, 2025.

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  • J.P. Arango, E. Duviella, L. Etienne, K. Langueh, P. Segovia and V. Puig. Unknown Input Observer design for LPV OSL-QIB nonlinear systems. IFAC-PapersOnLine, 59(15): 103-108, 2025.

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  • L. Gómez, J. Blesa, I. Santos-Ruiz, F.R. Lopez and V. Puig. Neural network-based leak localization in water distribution networks using the gravity center of pressure measurements. Journal of Water Process Engineering, 77: 108348, 2025.

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  • X. Li, J. Blesa and V. Puig. Tube-based robust model predictive control for pressurized water distribution networks. IFAC-PapersOnLine, 59(33): 62-67, 2025.

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  • J. Blesa. Detección y localización de fugas en redes de distribución de agua potable , XLVI Jornadas de Automática, 2025, Cartagena, Spain, pp. 1-6.

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  • J.P. Arango, L. Etienne, E. Duviella, K. Langueh, P. Segovia and V. Puig. Unknown input observer for quadratically inner bounded-one sided Lipschitz perturbed nonlinear systems. International Journal of Systems Science, 56(9): 1959–1972, 2025.

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  • E. Villalba-Aguilera, J. Blesa and P. Ponsa. Implementación de MPC para el seguimiento de trayectorias en un robot móvil omnidireccional, XLVI Jornadas de Automática, 2025, Cartagena, Spain, pp. 1-6.

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  • P. Segovia, V. Puig, R. Negenborn and V. Reppa. Dynamic coordination of multiple movable bridges and vessels for time-efficient inland waterway navigation. IEEE Transactions on Intelligent Transportation Systems, 26(4): 5481-5493, 2025.

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  • P.S. Pessim, P.H. Coutinho, M.J. Lacerda, V. Puig and R. Martinez Palhares. Distributed leader-following formation of discrete-time multi-agent LPV systems. International Journal of Robust and Nonlinear Control, 35(18): 7942-7956, 2025.

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  • E. Caldarelli, A. Chatalic, A. Colomé, C. Molinari, C. Ocampo-Martínez, C. Torras and L. Rosasco. Linear quadratic control of nonlinear systems with Koopman operator learning and the Nyström method. Automatica, 177: 112302, 2025.

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  • D. Jung, E. Frisk, M. Krysander, A. Sztyber-Betley, F. Corrini, A. Arici, N. Anselmi, M. Mazzoleni, J. Xu, S. Mo, Z. Xu, C. Yang, Z. Du, H. Safaeipour, M. Forouzanfar, V. Mirahi, A. Pinnarelli, V. Puig, Q. Deng, Y. Liu, J. Liu, H. Ke, W. Zhu, S. Merkelbach, M. Ahang and H. Najjaran. A fault diagnosis benchmark of technical systems with incomplete data - six solutions. Control Engineering Practice, 164: 106427, 2025.

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  • M. Marti, A. Cecilia, R. Ortega, A. Bobstov and R. Costa. OCV Estimation in electrochemical batteries with an unknown linear model and finite excitation. Journal of Energy Storage, 132: 117665, 2025.

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  • J.P. Arango, L. Etienne, E. Duviella, K. Langueh, P. Segovia and V. Puig. A robust unknown input observer for open channel irrigation systems. Control Engineering Practice, 165: 106510, 2025.

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  • A. Carrizosa, J. Zhou, E. Frisk, V. Puig and F. Nejjari. Behavior-aware online prediction of obstacle occupancy using zonotopes, 2025 IEEE Conference on Decision and Control, 2025, Rio de Janeiro, Brazil, pp. 7337-7342, .

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  • J.P. Arango, L. Etienne, E. Duviella, K. Langueh, P. Segovia and V. Puig. Interval Luenberger-like observer design for fault detection and state estimation in one-sided Lipschitz quadratically inner-bounded systems, 2025 6th International Conference on Control and Fault-Tolerant Systems, 2025, Ayia Napa (Cyprus), pp. 216-221.

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  • P. Cardona, L. Valiño, C. Ocampo-Martínez and M. Serra. Mixed logical dynamical modelling of renewable hydrogen refuelling stations for the design of optimization-based operational schemes. Applied Energy, 393(126037), 2025.

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  • J.P. Arango, L. Etienne, E. Duviella, K. Langueh, P. Segovia and V. Puig. Robust unknown input observer design for uncertain and noisy OSL-QIB nonlinear systems, 2025 European Control Conference, 2025, , pp. 2390-2395.

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  • T.P. Puleston, A. Cecilia, A. Clemente, R. Costa and M. Serra. Kazantzis-Kravaris/Luenberger observer for the joint estimation of vanadium flow battery concentrations and side-reaction rates. Journal of Energy Storage, 139: 118760, 2025.

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  • J.P. Arango, L. Etienne, E. Duviella, K. Langueh, P. Segovia and V. Puig. A novel unknown input observer design for nonlinear LPV systems. IEEE Control Systems Letters, 9: 1658-1663, 2025.

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  • M. Chen, C. Batlle, B. Escachx, R. Costa and J. Na. Multi-objective identification of a metal hydride tank lumped parameter model. Journal of Energy Storage, 139(118759), 2025.

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  • J.P. Arango, E. Duviella, L. Etienne, K. Langueh, P. Segovia and V. Puig. A nonlinear state feedback tracking controller for open channel irrigation systems, 2025 IFAC Workshop on Control Methods for Water Resource Systems, 2025, Douai (France), pp. 44-49.

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  • E. Villalba-Aguilera, J. Blesa and P. Ponsa. Model-based predictive control for position and orientation tracking in a multilayer architecture for a three-wheeled omnidirectional mobile robot . Robotics, 14(6): 72, 2025.

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  • A. Vázquez, P. Segovia and V. Puig. Optimal regional water network management in drought conditions: the Catalonia case study, 2025 IFAC Workshop on Control Methods for Water Resource Systems, 2025, Douai (France), pp. 56-61.

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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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