Publicaciones del Grupo de innovacion Docente

Publicaciones

Tesis Doctorales

Juan Antonio Domínguez Hernández. Contribuciones al Modelado de un Motor Lineal de Inducción de Flujo Transversal mediante Elementos Finitos-3D. Directora: Natividad Duro Carralero. 2024. Programa de Doctorado en Ingeniería de Sistemas y de Control. Universidad Nacional de Educación a Distancia (España).

Pablo Mantilla. Ingeniería de características en inteligencia artificial para datos financieros de alta frecuencia. Director: Sebastián Dormido Canto. 2023. Programa de Doctorado en Ingeniería de Sistemas y de Control. Universidad Nacional de Educación a Distancia (España).

Francisco José Mañas Álvarez. Development, Control and Evaluation of a Heterogeneous Multi-Agent Robotic Platform. Directoras: Raquel Dormido, María Guinaldo. 2023. Programa de Doctorado en Ingeniería de Sistemas y de Control. Universidad Nacional de Educación a Distancia (España).

Samantha Orlando. Análisis del aprendizaje de los estudiantes en un entorno educativo con actividades de robótica. Directores: Elena Gaudioso y Félix de la Paz. 2021. Programa de Doctorado en Sistemas Inteligentes. Universidad Nacional de Educación a Distancia (España).

Yolanda Matas Martín. Una aplicación adaptativa integral para el entrenamiento visual online de niños con baja visión. Directores: Elena Gaudioso y Félix Hernández Del Olmo. 2021. Programa de Doctorado en Sistemas Inteligentes. Universidad Nacional de Educación a Distancia (España).

Francisco Javier Hernández Martín. Optimización de predictores de disrupciones en espacios bidimensionales. Directores: S. Dormido-Canto y J. Vega. 2020. Programa de Doctorado en Ingeniería de Sistemas y de Control. Universidad Nacional de Educación a Distancia (España).

Álvaro Antonio Olmedo Rodríguez. Modelos de clasificación con medidas de confianza en predictores conformales aplicados a imágenes de fusión nuclear. Directores: S. Dormido-Canto y J. Vega. 2020. Programa de Doctorado en Ingeniería de Sistemas y de Control. Universidad Nacional de Educación a Distancia (España).

Publicaciones en revista dentro del ámbito docente

Díaz-Lauzurica, B., & Moreno-Salinas, D. (2025). Active Learning Methodologies for Increasing the Interest and Engagement in Computer Science Subjects in Vocational Education and Training. Education Sciences, 15(8), 1017.

de León, Á. S. S., de Blanco, V. G., & Caro, P. J. H. (2025). Uso de avatares parlantes para la gamificación de la asignatura de Derecho Penitenciario. Aprendizaje jurídico colaborativo, 403-410.

Horcas, I., Moreno-Salinas, D., & Sánchez-Moreno, J. (2025). A cost-effective design for a mid-range microcontroller-based lock-in amplifier. Microprocessors and Microsystems, 113, 105145.

Orlando, S., Gaudioso, E., & de la Paz, F. (2024). Toward Embedding Robotics in Learning Environments with Support to Teachers: The IDEE Experience. IEEE Transactions on Learning Technologies, 17, 874–884. https://doi.org/10.1109/TLT.2023.3339882

Díaz, B., & Moreno-Salinas, D. (2023). Applying Design Thinking to Enhance Programming Education in Vocational and Compulsory Secondary Schools. Applied Sciences, 13(23), 12792. https://doi.org/10.3390/app132312792

Taj, A. M., Fabregas, E., Abouhilal, A., Taifi, N., & Malaoui, A. (2021). Comparative Study of Traditional, Simulated and Real Online Remote Laboratory: Student's Perceptions in Technical Training of Electronics. International Journal of Online & Biomedical Engineering, 17(5). https://doi.org/10.3991/ijoe.v17i05.21949

Orlando, S., Gaudioso, E., & De La Paz, F. (2020). Supporting Teachers to Monitor Student's Learning Progress in an Educational Environment With Robotics Activities. IEEE Access, 8, 48620–48631. https://doi.org/10.1109/ACCESS.2020.2978979

Díaz-Lauzurica, B., & Moreno-Salinas, D. (2019). Computational Thinking and Robotics: A Teaching Experience in Compulsory Secondary Education with Students with High Degree of Apathy and Demotivation. Sustainability, 11, 5109.

Farias, G., Fabregas, E., Peralta, E., Vargas, H., Dormido-Canto, S., & Dormido, S. (2019). Development of an easy-to-use multi-agent platform for teaching mobile robotics. IEEE Access, 7, 55885–55897. https://doi.org/10.1109/ACCESS.2019.2913916

Matas, Y., Hernández-Del-Olmo, F., Gaudioso, E., & Santos, C. (2019). An Adaptive, Comprehensive Application to Support Home-Based Visual Training for Children With Low Vision. IEEE Access, 7, 169018–169028. https://doi.org/10.1109/ACCESS.2019.2954953

Galan, D., Chaos, D., de la Torre, L., Aranda-Escolástico, E., & Heradio, R. (2019). A general tool for customizing online laboratory experiments and its application to the Furuta inverted pendulum system. IEEE Control Systems Magazine, 39(5), 75–87.

Publicaciones en revista dentro del ámbito del aprendizaje automático y la ciencia de datos

Ganzábal, A. G., Rattá, G. A., Dormido-Canto, S., Carvalho, P., Silburn, S., Coffey, I., & JET Contributors. (2025). A methodology for TIE detection and tracking for JET's experimental cameras. Fusion Engineering and Design, 218, 115164.

Garcia, G., Eskandarian, A., Fabregas, E., Vargas, H., & Farias, G. (2025). Cooperative Formation Control of a Multi-Agent Khepera IV Mobile Robots System Using Deep Reinforcement Learning. Applied Sciences, 15(4), 1777.

Escorza, O., Garcia, G., Fabregas, E., Velastin, S. A., Eskandarian, A., & Farias, G. (2025). Deep Reinforcement Learning Applied to a Spherical Robot for Target Tracking. IEEE Transactions on Industrial Electronics.

Aranda-Escolástico, E., Abdelrahim, M., Fernández-Amorós, D., Guinaldo, M., & Colombo, L. (2025). Passivity-Based Distributed Event-Triggered Flocking Control of Port-Hamiltonian Systems. IEEE Control Systems Letters.

Mañas-Álvarez, F. J., Guinaldo, M., & Dormido, R. (2025). A Benchmark on Formation Control of Multi-agent Robotic System. En Control Systems Benchmarks (pp. 151–167). Springer Nature Switzerland.

Bañales, S., Dormido, R., & Duro, N. (2025). Multi-Step Clustering of Smart Meters Time Series: Application to Demand Flexibility Characterization of SME Customers. CMES-Computer Modeling in Engineering & Sciences, 142(1).

Vega, J., Dormido-Canto, S., Castro, R., Fernández, J. D., Murari, A., & JET Contributors. (2024). Real-time disruption prediction in multi-dimensional spaces leveraging diagnostic information not available at execution time. Nuclear Fusion, 64(4), 046010. https://doi.org/10.1088/1741-4326/ad288a

Ganzábal, A. G., Rattá, G. A., Gadariya, D., Dormido-Canto, S., & JET Contributors. (2024). Advancing MARFE detection in JET's operational camera videos through Machine Learning techniques. Fusion Engineering and Design, 205, 114534. https://doi.org/10.1016/j.fusengdes.2024.114534

Correa, R., Farias, G., Fabregas, E., Dormido-Canto, S., Pastor, I., & Vega, J. (2024). Deep learning models to reduce stray light in TJ-II Thomson scattering diagnostic. Sensors, 24(9), 2764. https://doi.org/10.3390/s24092764

Dormido-Canto, S., Rohland, J., López, M., Garcia, G., Fabregas, E., & Farias, G. (2024). Enhancing Photovoltaic Power Predictions with Deep Physical Chain Model. Algorithms, 17(10), 445. https://doi.org/10.3390/a17100445

Morilla, F., Vega, J., Dormido-Canto, S., Romero-Maestre, A., de-Martín-Hernández, J., Morilla, Y., & Domínguez, M. (2024). A Machine Learning Approach to Predict Radiation Effects in Microelectronic Components. Sensors, 24(13), 4276.

Alonso, F., Samaniego, B., Farias, G., & Dormido-Canto, S. (2024). Analysis of cryptographic algorithms to improve cybersecurity in the industrial electrical sector. Applied Sciences, 14(7), 2964.

Schröder, K., Farias, G., Dormido-Canto, S., & Fabregas, E. (2024). Comparative Analysis of Deep Learning Methods for Fault Avoidance and Predicting Demand in Electrical Distribution. Energies, 17(11), 2709. https://doi.org/10.3390/en17112709

Duro, N. (2024). Sensor Data Fusion Analysis for Broad Applications. Sensors, 24(12), 3725.

Domínguez, J. A., Duro, N., & Gaudioso, E. (2024). Finite Element Analysis of Different Transverse Flux Linear Induction Motor Models to Improve the Performance of the Main Magnetic Circuit. Machines, 12(2), 89. https://doi.org/10.3390/machines12020089

Cuéllar, S., Santos, M., Alonso, F., Fabregas, E., & Farias, G. (2024). Explainable anomaly detection in spacecraft telemetry. Engineering Applications of Artificial Intelligence, 133, 108083. https://doi.org/10.1016/j.engappai.2024.108083

Olivares, E., Curé, M., Araya, I., Fabregas, E., Arcos, C., Machuca, N., & Farias, G. (2024). Estimation of Physical Stellar Parameters from Spectral Models Using Deep Learning Techniques. Mathematics, 12(20), 3169.

Guerrero-Chilabert, G. S., Moreno-Salinas, D., & Sánchez-Moreno, J. (2024). Design and Development of an SVM-Powered Underwater Acoustic Modem. Journal of Marine Science and Engineering, 12(5), 773. https://doi.org/10.3390/jmse12050773

Cerrada, C., Chaos, D., Moreno-Salinas, D., Pascoal, A., & Aranda, J. (2024). An energy efficient fault-tolerant controller for homing of underactuated AUVs. Control Engineering Practice, 146, 105883. https://doi.org/10.1016/j.conengprac.2024.105883

Aranda-Escolástico, E., Colombo, L. J., Guinaldo, M., & Visioli, A. (2024). Event-Triggered Control of Port-Hamiltonian Systems Under Time-Delay Communication. IEEE Control Systems Letters, 8, 175–180.

Carbonell, R., Cuenca, Á., Salt, J., Aranda-Escolástico, E., & Casanova, V. (2024). Remote path-following control for a holonomic Mecanum-wheeled robot in a resource-efficient networked control system. ISA Transactions, 151, 377–390.

Almakhles, D., Aranda-Escolástico, E., & Abdelrahim, M. (2024). Dynamic periodic event-triggered control for nonlinear systems with output dynamic quantization. Journal of the Franklin Institute, 361(14), 107085.

Acevedo, J., Garcia, G., Ramirez, R., Fabregas, E., Hermosilla, G., Dormido-Canto, S., & Farias, G. (2024). Uncertainty Detection in Supervisor–Operator Audio Records of Real Electrical Network Operations. Electronics, 13(1), 141. https://doi.org/10.3390/electronics13010141

Ceballos-Gutierrez, J., Aranda-Escolastico, E., & Moreno-Salinas, D. (2024). Optimisation of spectrum use by Mode S surveillance systems through coordinated DAP extraction. IEEE Aerospace and Electronic Systems Magazine.

Mañas-Álvarez, F. J., Guinaldo, M., Dormido, R., & Dormido-Canto, S. (2023). Scalability of Cyber-Physical Systems with Real and Virtual Robots in ROS 2. Sensors, 23(13), 6073. https://doi.org/10.3390/s23136073

Schröder, K., Garcia, G., Chacón, R., Montenegro, G., Marroquín, A., Farias, G., Dormido-Canto, S., & Fabregas, E. (2023). Development and Control of a Real Spherical Robot. Sensors, 23(8), 3895. https://doi.org/10.3390/s23083895

Esquembre, F., Chacón, J., Saenz, J., Vega, J., & Dormido-Canto, S. (2023). A programmable web platform for distributed access, analysis, and visualisation of data. Fusion Engineering and Design, 197, 114049. https://doi.org/10.1016/j.fusengdes.2023.114049

Hernández-del-Olmo, F., Gaudioso, E., Duro, N., Dormido, R., & Gorrotxategi, M. (2023). Advanced Control by Reinforcement Learning for Wastewater Treatment Plants: A Comparison with Traditional Approaches. Applied Sciences, 13(8), 4752. https://doi.org/10.3390/app13084752

Mañas-Álvarez, F. J., Guinaldo, M., Dormido, R., & Dormido, S. (2023). Muestreo y comunicación: impacto en el control de formaciones en sistemas multi-robot heterogéneos. Revista Iberoamericana de Automática e Informática Industrial (RIAI). https://doi.org/10.4995/riai.2023.20155

Mañas-Álvarez, F. J., Guinaldo, M., Dormido, R., & Dormido, S. (2023). Robotic Park: Multi-Agent Platform for Teaching Control and Robotics. IEEE Access, 11. https://doi.org/10.1109/ACCESS.2023.3264508

Gadariya, D., Vega, J., Stuart, C., Rattá, G. A., Card, P., Murari, A., & Dormido-Canto, S. (2022). Performance Analysis of the Centroid Method Predictor Implemented in the JET Real Time Network. Plasma Physics and Controlled Fusion, 64, 114003. https://doi.org/10.1088/1361-6587/ac963f

Vega, J., Murari, A., Dormido-Canto, S., Rattá, G. A., Gelfusa, M., & JET Contributors. (2022). Disruption prediction with artificial intelligence techniques in tokamak plasmas. Nature Physics, 18, 741–750. https://doi.org/10.1038/s41567-022-01602-2

Ruiz-Parrado, V., Heradio, R., Aranda-Escolastico, E., Sánchez, Á., & Vélez, J. F. (2022). A Bibliometric Analysis of Off-line Handwritten Document Analysis Literature (1990–2020). Pattern Recognition, 125, 108513.

Navarro-Iribarne, J. F., Moreno-Salinas, D., & Sánchez-Moreno, J. (2022). Low-cost portable system for measurement and representation of kinematic parameters in 3D. Sensors, 22(23), 9408. https://doi.org/10.3390/s22239408

Montenegro, G., Chacón, R., Fabregas, E., Garcia, G., Schröder, K., Marroquín, A., Dormido-Canto, S., & Farias, G. (2022). Modelling and Control of a Spherical Robot in the CoppeliaSim Simulator. Sensors, 22(16), 6020. https://doi.org/10.3390/s22166020

Quiroga, F., Hermosilla, G., Farias, G., Fabregas, E., & Montenegro, G. (2022). Position Control of a Mobile Robot through Deep Reinforcement Learning. Applied Sciences, 12(14), 7194. https://doi.org/10.3390/app12147194

Cuéllar, S., Aguayo, P., Fabregas, E., Curé, M., Dormido-Canto, S., & Farias, G. (2022). Deep learning exoplanets detection by combining real and synthetic data. PLOS ONE, 17(5). https://doi.org/10.1371/journal.pone.0268199

Ramirez, H., Velastin, S. A., Aguayo, P., Fabregas, E., & Farias, G. (2022). Human Activity Recognition by Sequences of Skeleton Features. Sensors, 22(11), 3991. https://doi.org/10.3390/s22113991

Ripoll, S., Bayarri, V., Muñoz, F., Ortega, R., Castillo, E., Latova, J., Herrera, J., Moreno-Salinas, D., & Martín, I. (2021). Hands Stencils in El Castillo Cave (Puente Viesgo, Cantabria, Spain): An Interdisciplinary Study. Proceedings of the Prehistoric Society, 87, 51–71. https://doi.org/10.1017/ppr.2021.11

Bañales, S., Dormido, R., & Duro, N. (2021). Smart meters time series clustering for demand response applications in the context of high penetration of renewable energy resources. Energies, 14, 3458. https://doi.org/10.3390/en14123458

Farias, G., Fabregas, E., Martínez, I., Vega, J., Dormido-Canto, S., & Vargas, H. (2021). Nuclear Fusion Pattern Recognition by Ensemble Learning. Complexity, 2021. https://doi.org/10.1155/2021/1207167

Ramirez, H., Velastin, S. A., Meza, I., Fabregas, E., Makris, D., & Farias, G. (2021). Fall detection and activity recognition using human skeleton features. IEEE Access, 9, 33532–33542. https://doi.org/10.1109/ACCESS.2021.3061626

Cajo, R., Guinaldo, M., Fabregas, E., Dormido, S., Plaza, D., De Keyser, R., & Ionescu, C. (2021). Distributed Formation Control for Multiagent Systems Using a Fractional-Order Proportional-Integral Structure. IEEE Transactions on Control Systems Technology. https://doi.org/10.1109/TCST.2021.3053541

González, S., Dormido-Canto, S., & Sánchez, J. (2020). Obtaining high preventive and resilience capacities infrastructure by industrial automation cells. International Journal of Critical Infrastructure Protection, 29, 100355. https://doi.org/10.1016/j.ijcip.2020.100355

Vega, J., Castro, R., Dormido-Canto, S., Rattá, G. A., & Ruíz, M. (2020). Automatic recognition of plasma relevant events: Implications for ITER. Fusion Engineering and Design, 156, 111638. https://doi.org/10.1016/j.fusengdes.2020.111638

Fabregas, E., Farias, G., Aranda-Escolástico, E., Garcia, G., Chaos, D., Dormido-Canto, S., & Dormido, S. (2020). Simulation and experimental results of a new control strategy for point stabilization of nonholonomic mobile robots. IEEE Transactions on Industrial Electronics, 67(8). https://doi.org/10.1109/TIE.2019.2935976

Farias, G., Fabregas, E., Dormido-Canto, S., Vega, J., & Vergara, S. (2020). Automatic recognition of anomalous patterns in discharges by recurrent neural networks. Fusion Engineering and Design, 154, 111495. https://doi.org/10.1016/j.fusengdes.2020.111495

Farias, G., Fabregas, E., Dormido-Canto, S., Vega, J., & Vergara, S. (2020). Automatic recognition of anomalous patterns in discharges by applying Deep Learning. Fusion Science and Technology, 76(8). https://doi.org/10.1080/15361055.2020.1820804

Farias, G., Fabregas, E., Torres, E., Bricas, G., Dormido-Canto, S., & Dormido, S. (2020). A Distributed Vision-Based Navigation System for Khepera IV Mobile Robots. Sensors, 20(18), 5409. https://doi.org/10.3390/s20185409

Farias, G., Garcia, G., Montenegro, G., Fabregas, E., Dormido-Canto, S., & Dormido, S. (2020). Reinforcement learning for position control problem of a mobile robot. IEEE Access, 8, 152941–152951. https://doi.org/10.1109/ACCESS.2020.3018026

Hernández del Olmo, F., Gaudioso, E., Duro, N., & Dormido, R. (2019). Machine Learning Weather Soft-Sensor for Advanced Control of Wastewater Treatment Plants. Sensors, 19(14), 3139.

Farias, G., Fabregas, E., Díaz-Barrera, A., Ponce, B., Castro, C., & Dormido-Canto, S. (2019). Automatic Control for the Production of Alginate by Azotobacter Vinelandii. IEEE Access, 7. https://doi.org/10.1109/ACCESS.2019.2954180

Moreno-Salinas, D., Moreno, R., Pereira, A., Aranda, J., & de la Cruz, J. M. (2019). Modelling of a surface marine vehicle with kernel ridge regression confidence machine. Applied Soft Computing, 76, 237–250. https://doi.org/10.1016/j.asoc.2018.12.002

Moreno, R., Moreno-Salinas, D., & Aranda, J. (2019). Black-Box Marine Vehicle Identification with Regression Techniques for Random Manoeuvres. Electronics, 8, 492.

Socas, R., Dormido, R., & Dormido, S. (2018). New Control Paradigms for Resources Saving: An Approach for Mobile Robots Navigation. Sensors, 18, 281.

Solano-Altamirano, J. M., Vázquez-Otero, A., Khikhlukha, D., Dormido, R., & Duro, N. (2017). Using Spherical-Harmonics Expansions for Optics Surface Reconstruction from Gradients. Sensors, 17(12), 2780. https://doi.org/10.3390/s17122780

Mur, A., Dormido, R., Duro, N., & Mercader, D. (2017). An unsupervised method to determine the optimal number of independent components. Expert Systems with Applications, 75, 56–62. https://doi.org/10.1016/j.eswa.2017.01.015