Nonlinear identification of a closed-loop semi-physical model for the vertical heave velocity of the BlueRov2 Heavy
DOI:
https://doi.org/10.17979/ja-cea.2026.47.13848Keywords:
nonlinear identification, filtering, semi-physical model, heave velocity, underwater vehicleAbstract
System identification is fundamental in control engineering, as it allows for predicting dynamic behavior and designing controllers. Multiple methods exist, both linear and nonlinear, based on physical principles or experimental data. This article proposes a closed-loop semi-physical model to characterize the linear velocity along the vertical axis of the BlueRov2 Heavy underwater vehicle. The model is based on physical principles that combine hydrodynamic drag and the thrust generated by the vertical thrusters. The model aims to predict the dynamic behavior of the heave velocity. The model has unknown parameters, which were estimated using Least-Squares (LS) with experimental data. The data were obtained after performing various experiments with the vehicle configured in Stabilize mode, sending Pseudo Random Binary Sequence (PRBS) signals to excite the actuators and collecting the linear heave velocity to estimate and validate the model. Finally, the proposed model shows good performance and predictive ability.
References
Alvarez, H., Lamanna, R., Vega, P., Revollar, S., 2009. Metodología para la obtención de modelos semifísicos de base fenomenológica aplicada a una sulfitadora de jugo de caña de azúcar. Revista Iberoamericana de Automática e Informática Industrial RIAI 6 (3), 10–20. DOI: 10.1016/S1697-7912(09)70260-2
Avila, J. P. J., Adamowski, J. C., 2011. Experimental evaluation of the hydrodynamic coefficients of a rov through morison’s equation. Ocean Engineering 38 (17), 2162–2170. DOI: 10.1016/j.oceaneng.2011.09.032
Castro, H., Scarpetta, J., 2005. A methodology for excitation systems identification. In: 2005 International Conference on Industrial Electronics and Control Applications. p. 6. DOI: 10.1109/ICIECA.2005.1644350
de Prada, C., Hose, D., Gutierrez, G., Pitarch, J. L., 2018. Developing greybox dynamic process models. IFAC-PapersOnLine 51 (2), 523–528, 9th Vienna International Conference on Mathematical Modelling. DOI: 10.1016/j.ifacol.2018.03.088
Díaz Martínez, J. M., Muñoz Mansilla, R., 2022. Diseño de experimentos y tratamiento de datos, apuntes de la asignatura: Identificación de sistemas.
Espinal, A., Cerrada, C., Chaos, D., Moreno-Salinas, D., 5 2026. Identificación no lineal de un modelo semifísico para el vehículo submarino bluerov2 heavy en 3 grados de libertad. In: Simposio CEA de Robótica, Bioingeniería, Visión por Computador y Automática Marina (RBVM) 2026. pp. 1–6. DOI: 10.64117/simposioscea.v2i2.220
Fossen, T. I., 2011. Handbook of Marine Craft Hydrodynamics and Motion Control. John Wiley & Sons, Ltd, United Kingdom. DOI: 10.1002/9781119994138
González-García, J., Narcizo-Nuci, N. A., García-Valdovinos, L. G., Salgado- Jiménez, T., Gómez-Espinosa, A., Cuan-Urquizo, E., Cabello, J. A. E., 2021. Model-Free High Order Sliding Mode Control with Finite-Time Tracking for Unmanned Underwater Vehicles. Applied Sciences 11, 1–21. DOI: 10.3390/app11041836
Herrero, E. R., Llata, J. R., Sainz, J. J., Velasco, F. J., Renteria, L. A., 2024a. Experiment design for model basin tests with a remotely operated vehicle. Ocean Engineering 307, 118215. DOI: 10.1016/j.oceaneng.2024.118215
Herrero, E. R., Llata, J. R., Sainz, J. J., Velasco, F. J., Torrijos, P. D., 2024b. Indirect inference approach for parameter estimation of non linear manoeuvring models of a rov based on model basin trials. Ships and Offshore Structures 19 (10), 1676–1683. DOI: 10.1080/17445302.2023.2275092
Jiang, M., Chen, C., Dong, Y., Zhang, L., Tan, L., 2025. Research on hydrodynamic characteristics and dynamics model of an open-frame rov moving near the wall. Ocean Engineering 320, 120358. DOI: 10.1016/j.oceaneng.2025.120358
l Piskur, P., Szymak, P., l Kot, R., Marchel, L., Naus, K., 07 2025. Why the fossen model is so popular for marine vehicles’ dynamic analysis? In: Proceedings of the 39 th ECMS International Conference on Modelling and Simulation ECMS 2025, June 24th-June 27th, 2025, Catania, Italy. pp. 545–550. DOI: 10.7148/2025-0545
Lack, S., Rentzow, E., Jeinsch, T., 2019. Experimental parameter identification for an open-frame rov: Comparison of towing tank tests and open wáter self-propelled tests. IFAC-PapersOnLine 52 (21), 271–276, 12th IFAC Conference on Control Applications in Marine Systems, Robotics, and Vehicles CAMS 2019. DOI: 10.1016/j.ifacol.2019.12.319
Mathworks.com, 2025. Elimine y visualice valores at´ıpicos en sus datos. Accessed: 29-05-2026.
Ortiz-Toro, C. A., Cerrada-Collado, C., Moreno-Salinas, D., Chaos-Garía, D., García-Suárez, K. L., Otero, P., Vidal-Pérez, J. M., Luque-Nieto, M. A., Vázquez, A. I., Fraile-Ardanuy, J. J., Negro-Valdecantos, V., Jimenez-
Yguacel, E., Aranda-Almansa, J., Zazo-Bello, S., Zufiria, P. J., Magdalena, L., Parras, J., Gutiérrez, A., 2024. NauSim: Un simulador de código abierto para el control, desarrollo y despliegue de drones submarinos. XLV Jornadas de Autom´atica, 1–6. DOI: 10.17979/ja-cea.2024.45.10895
Ortiz-Toro, C. A., Guti´errez, A., Chaos-García, D., Cerrada-Collado, C., Luque-Nieto, M. A., Clemente-Medina, M. C., 2025. Robótica Colaborativa Marina: Explorando Escenarios con NauSim y YOLO. XLVI Jornadas de Automática, 1–6. DOI: 10.17979/ja-cea.2025.46.12260
Oussar, Y., Dreyfus, G., 2001. How to be a gray box: dynamic semi-physical modeling. Neural Networks 14 (9), 1161–1172. DOI: 10.1016/S0893-6080(01)00096-X
Pearson, R., 2002. Outliers in process modeling and identification. IEEE Transactions on Control Systems Technology 10 (1), 55–63. DOI: 10.1109/87.974338
Ridao, P., Tiano, A., El-Fakdi, A., Carreras, M., Zirilli, A., 2004. On the identification of non-linear models of unmanned underwater vehicles. Control Engineering Practice 12 (12), 1483–1499, guidance and control of underwater vehicles. DOI: 10.1016/j.conengprac.2004.01.004
Schoukens, J., Ljung, L., 2019. Nonlinear system identification: A useroriented road map. IEEE Control Systems Magazine 39 (6), 28–99. DOI: 10.1109/MCS.2019.2938121
von Benzon, M., Sørensen, F., Liniger, J., Pedersen, S., Klemmensen, S., Schmidt, K., 2021. Integral Sliding Mode Control for a Marine Growth Removing ROV with Water Jet Disturbance. In: 2021 European Control Conference
(ECC). pp. 2265–2270. DOI: 10.23919/ECC54610.2021.9655050
Yang, X., Xing, Y., 2021. Tuning for robust and optimal dynamic positioning control in BlueROV2. IOP Conference Series: Materials Science and Engineering 1201, 1–18. DOI: 10.1088/1757-899X/1201/1/012015
Ziani-cherif, S., Lebret, G., 1997. On the identification of the nonlinear Dynamic model of an underwater r.o.v. IFAC Proceedings Volumes 30 (11), 651–656, iFAC Symposium on System Identification (SYSID’97), Kitakyushu, Fukuoka, Japan, 8-11 July 1997. DOI: 10.1016/S1474-6670(17)42919-3
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Alex Espinal, Cristina Cerrada, Dictino Chaos, David Moreno Salinas
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
