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 (2025 - 2024) of the Automatic Control

  • 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, 2025, to appear.

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  • L. Romero, P. Irofti, F. Stoican and V. Puig. Nodal hydraulic head estimation through Unscented Kalman Filter for data-driven leak localization in water networks, 12th IFAC Symposium on Fault Detection Supervision and Safety for Technical Processes, 2024, Ferrara, Vol 58 of IFAC Papers Online, pp. 67-72.

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  • L. Gómez, I. Santos-Ruiz, J. Blesa, V. Puig and F.R. Lopez. Leak localization in an urban water distribution network using a LSTM deep neural network, 12th IFAC Symposium on Fault Detection Supervision and Safety for Technical Processes, 2024, Ferrara, Vol 58 of IFAC Papers Online, pp. 79-84.

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  • T.P. Puleston, A. Trovò, G. Marini, M. Serra, R. Costa and M. Guarnieri. Design and experimental validation of an optimal remixing procedure for vanadium flow batteries affected by faradaic imbalance. Journal of Power Sources, 624: 235487, 2024.

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  • A. Clemente, M. Montiel, F. Barreras, A. Lozano, B. Escachx and R. Costa. Online estimation of the state of charge and state of health of a vanadium redox flow battery. Journal of Power Sources, 598: 234181, 2024.

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  • M. Chen. Model modification and calibration of metal hydride tanks, 2024 IRI Doctoral Day, 2024, Barcelona, pp. 4.

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  • M. Chen, C. Batlle, B. Escachx, R. Costa and J. Na. Sensitivity analysis and calibration for a two-dimensional state-space model of metal hydride storage tanks based on experimental data. Journal of Energy Storage, 94: 112316, 2024.

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  • T.P. Puleston. Monitoring and optimal operation of vanadium redox flow batteries, 2024 IRI Doctoral Day, 2024, Barcelona, pp. 15.

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  • J.M. Burruel-Zazueta, H. Rodríguez, G.E. Peralta-Penunuri, V. Puig, I. Algredo-Badillo and L.A. Morales-Rosales. Biometric lock with facial recognition implemented with deep learning techniques. Computer Science and Information Systems, 21(4): 1359-1387, 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.

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  • L. Romero. Contributions to the real-time monitoring of water systems, 2024 IRI Doctoral Day, 2024, Barcelona, pp. 16.

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  • F.R. Lopez, H. Darias, V. Puig, G. Valencia, J. Domínguez-Zenteno and M.E. Guerrero-Sánchez. Cooperative convex control of multiagent systems applied to differential drive robots. International Journal of Applied Mathematics and Computer Science, 34(2): 199-210, 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, 2024.

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  • C. Xu. Data-driven control techniques for microgrids, 2024 IRI Doctoral Day, 2024, Barcelona, pp. 20.

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  • M.F. Ávila-Díaz, M.A. Márquez-Vera, O. Díaz-Parra, V. Puig and A. Ma'arif. Inverse fuzzy fault models for fault isolation and severity estimation in industrial pneumatic valves. Informatica, 48(3): 379-398, 2024.

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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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  • P. Cardona. Optimization-based control of renewable hydrogen production, storage and dispatchment systems for the transport sector, 2024 IRI Doctoral Day, 2024, Barcelona, pp. 2.

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  • M. Sheikhsamad and V. Puig. Learning-based control of autonomous vehicles using an adaptive neuro-fuzzy inference system and the linear matrix inequality approach . Sensors, 24(8): 2551, 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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  • T.P. Puleston, G. Marini, A. Trovò, M. Serra, R. Costa and M. Guarnieri. Optimised partial remixing procedure for mitigating capacity loss in imbalanced vanadium flow batteries, 2024 International Flow Battery Forum, 2024, Glasgow, UK, pp. 90-91.

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  • J.Y. Colín-Castillo, G.L. Osorio-Gordillo, V. Puig, R.A. Vargas-Méndez, G.V. Guerrero-Ramírez, J. Reyes-Reyes and C. Astorga-Zaragoza. Sensor fault detection for LPV systems using interval observers. IEEE Access, 12: 93701-93710, 2024.

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  • 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. Segovia, V. Puig and E. Duviella. A multilayer control strategy for the Calais canal. IEEE Transactions on Control Systems Technology, 32(2): 311-325, 2024.

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  • J.M. Burruel-Zazueta, H. Rodríguez, V. Puig, M.A. Medrano-Diaz, S.I. Fernandez-Gregorio and L.A. Morales-Rosales. Developing of a multi-angle and varied walking conditions dataset for human gait recognition. Engineering Applications of Artificial Intelligence, 138: 109404, 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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  • 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: 1-14, 2024, to appear.

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  • A. M. Borrell, V. Puig and O. Sename. Fixed-structure parameter-dependent state feedback controller: A scaled autonomous vehicle path-tracking application. Control Engineering Practice, 147: 105911, 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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  • E.d. Pérez, J. Fragoso-Mandujano, J. Guzmán-Rabasa, Y. González-Baldizón and S. Flores-Guirao. ANFIS and Takagi-Sugeno interval observers for fault diagnosis in bioprocess system. Journal of Process Control, 138: 103225, 2024.

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  • S. Barchinezhad, M.S. Haghighi and V. Puig. Identification and analysis of stochastic deception attacks on cyber physical systems. Journal of the Franklin Institute, 361(8): 106774, 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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  • A. Molavi, A.P. Husar, H. Hjortberg, N. Nilsson, M. Kogler, J. Sanchez Monreal, Y. Eldigair and M. Serra. State machine-based architecture to control system processes in a hybrid fuel cell electric vehicle. International Journal of Hydrogen Energy, 52: 1220-1235, 2024.

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  • S. Barchinezhad and V. Puig. Switching LPV approach for analysis and control of TCP-based cyber-physical systems under DoS attack. Neurocomputing, 608: 128310, 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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  • A. Cecilia, M. Serra and R. Costa. Real-time parameter estimation of polymer electrolyte membrane fuel cell in absence of excitation. International Journal of Hydrogen Energy, 52: 37-48, 2024.

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  • E.d. Pérez, V. Puig, F.R. Lopez, G. Valencia, I. Santos-Ruiz and G.L. Osorio-Gordillo. Robust fault diagnosis of wind turbines based on MANFIS and zonotopic observers. Expert Systems with Applications, 235: 121095, 2024.

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  • S. Zhang, V. Puig and S. Ifqir. Robust LPV fault diagnosis using the set-based approach for autonomous ground vehicles. IEEE Transactions on Intelligent Transportation Systems, 2024.

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  • X. Fang, J. Blesa and V. Puig. Fault diagnosis using interval data-driven LPV observers and structural analysis, 12th IFAC Symposium on Fault Detection Supervision and Safety for Technical Processes, 2024, Ferrara, Vol 58 of IFAC Papers Online, pp. 25-30.

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  • C. Xu, Z. Wang, V. Puig and Y. Shen. Simultaneous interval estimation of actuator fault and state for a class of nonlinear systems by zonotope analysi. Journal of Process Control, 142: 103303, 2024.

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  • S. Zhang, S. Ifqir and V. Puig. Linear Quadratic zonotopic control of switched systems: application to autonomous vehicle path-tracking. IEEE Control Systems Letters, 8: 1895-1900, 2024.

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  • X. Fang, J. Blesa and V. Puig. Fault prognosis approach using data-driven structurally generated residuals, 32nd Mediterranean Conference on Control and Automation, 2024, Chania - Crete, Greece, pp. 531-536.

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  • L. Romero, G. Cembrano and V. Puig. Leak learning for graph-based state interpolation in water distribution networks, 2024 European Control Conference, 2024, Stockholm (Sweden), pp. 110-115.

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  • S.M. Hosseindokht, J. Blesa and V. Puig. Control óptimo multicapa de redes inteligentes, XLV Jornadas de Automática, 2024, Málaga, Spain, pp. 1-6.

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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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