Adaptive PID–PD Hybrid Control for Precise Motion of ROVs in Dynamic Environments
DOI:
https://doi.org/10.33019/jurnalecotipe.v12i2.4575Keywords:
Dynamic Marine Conditions, Marine Robotics, PD Controller, PID Controller, Remotely Operated Vehicles, Rotation Control, ROV Position Control, Underwater RoboticsAbstract
This study aims to develop and evaluate an Adaptive PID–PD Hybrid Control System to enhance the position and rotation control of a Remotely Operated Vehicle (ROV) in challenging sea conditions. In this study, two main stages were conducted. First, a dynamic model of the ROV was developed, encompassing translation for movement in three-dimensional space (x, y, z) and rotation for changes in orientation (roll, pitch, yaw). Second, the adaptive PID–PD hybrid controllers were implemented and evaluated on the ROV model to ensure stability and precision in motion control. Simulation results demonstrate that the proposed controller effectively maintains position with surge overshoot of 23.3%, sway of 1.67%, and heave of 47.17%. The settling time ranges from 41.53 to 107 seconds, indicating areas for further tuning. In terms of velocity response, surge velocity shows a high overshoot of 106.26%, while sway and heave velocities present smaller overshoots but require longer stabilization times. The integration of PID and PD in a hybrid adaptive framework yields improved inner-loop response and overall robustness. These findings highlight the potential of the adaptive hybrid controller to enhance stability, responsiveness, and operational effectiveness of ROVs in dynamic marine conditions.
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[1] Y. Chen, H. Zhang, W. Zou, H. Zhang, B. Zhou, and D. Xu, “Dynamic modeling and learning based path tracking control for ROV-based deep-sea mining vehicle,” Expert Syst. Appl., vol. 262, p. 125612, 2024, https://doi.org/10.1016/j.eswa.2024.125612
[2] Tran, N.-H., Le, M.-C., Ton, T., Le, T.-C., & Tran, T. (2020). ROV Stabilization Using an Adaptive Nonlinear Feedback Controller. In Lecture Notes in Computer Science, 144–155. https://doi.org/10.1007/978-3-030-62324- 1_13 .
[3] Sahili, J., Hamoud, A., & Jammoul, A. (2018). ROV Design Optimization: Effect on Stability and Drag Force. In 2018 6th RSI International Conference on Robotics and Mechatronics (IcRoM), 413–417. https://doi.org/10.1109/ICROM.2018.8657510
[4] Yang, Y., Yang, R., Qin, H., Li, R., & Ye, W. (2024). Research on Vision-Based ROV Underwater Positioning Method. In Proceedings of the 2024 5th International Conference on Geology, Mapping, and Remote Sensing (ICGMRS), 131–137. https://doi.org/10.1109/ICGMRS62107.2024.10581261
[5] Diamanti, E., Mentogiannis, V., Ødegård, Ø., & Koutsouflakis, G. (2025). Underwater drones as a low-cost, yet powerful tool for underwater archaeological mapping: Case studies from the Mediterranean. Journal of Computer Applications in Archaeology, 8(1), 10–24. https://doi.org/10.5334/jcaa.184
[6] Salah, S., et al. (2021). Design of lightweight, low-cost remotely operated underwater vehicle. In Proceedings of the ASME Design Engineering Technical Conference. https://doi.org/10.1115/DETC2021-70555 .
[7] McCulley, R. (2009). Almost disposable ROVs earning respect offshore. Offshore Engineer, 34(5). Retrieved from https://www.scopus.com/inward/record.uri?eid=2-s2.0- 67650723276&partnerID=40&md5=74848ea67f12dfc35ffe54ce9c7dae59
[8] Poretti, M., Benson, B., & Rauch, C. (2013). Design of modular camera tool for mini underwater ROVs. In OCEANS 2013 MTS/IEEE - San Diego: An Ocean in Common. https://www.scopus.com/inward/record.uri?eid=2- s2.0-84896368489&partnerID=40&md5=448b0974ee92f9e06c8ba20cd8641d6a
[9] Ravichandran, S., et al. (2022). Accelerated testing and results of underwater electric thrusters for mini observation class ROVs. In Oceans Conference Record (IEEE).
https://doi.org/10.1109/OCEANSChennai45887.2022.9775357 .
[10] Mansoor, A., Salih, T., & Abdullah, F. (2022). Speed Control of Separately Excited D.C. Motor using Self-Tuned Parameters of PID Controller. Tikrit Journal of Engineering Sciences, 20(1), 1–8. https://doi.org/10.25130/tjes.20.1.01 .
[11] Wu, X.-G., Wang, X.-D., Yu, T.-W., & Xie, X.-P. (2007). PID control on the current of electromagnetic clutch tuned by neural network. Dianji yu Kongzhi Xuebao/Electric Machines and Control, 11(4), 335–339. h t t p s : / / w w w . s c o p u s . c o m / i n w a r d / r e c o r d . u r i ? e i d = 2 - s 2 . 0 - 34547976761&partnerID=40&md5=b16f8f07ba1451e7972865fb176f4e5e
[12] Li, J., Zhang, L., Huang, X., Zhang, Q., & Wang, G. (2022). Cascade PID control algorithm for wind turbine blade mold temperature based on improved RBF neural network. Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 43(3), 330–335. https://doi.org/10.19912/j.0254-0096.tynxb.2020-0640 .
[13] He, D., Shi, F., Tan, S., & Deng, Q. (2020). Research on inverse kinematics algorithm of 6-DOF industrial robot based on RBF-PID. Journal of Physics: Conference Series, 1624, 042017. https://doi.org/10.1088/1742- 6596/1624/4/042017 .
[14] Qafko, T., et al. (2024). Design and control of an underwater remotely operated vehicle using thrust force vectors. In URTC 2024 - 2024 IEEE MIT Undergraduate Research Technology Conference, Proceedings. https://doi.org/10.1109/URTC65039.2024.10937653 .
[15] Ali, F. A., Aras, M. S. M., Azis, F. A., Sulaima, M. F., & Jaaffar, I. (2014). Design and development of auto depth control of Remotely Operated Vehicle using thruster system. Journal of Mechanical Engineering and Sciences, 7(1), 1141–1149. https://doi.org/10.15282/jmes.7.2014.13.0111 .
[16] Jayasundere, N. D., & Gunawickrama, S. (2016). Underwater ROV with fuzzy logic motion control. In 2016 IEEE International Conference on Information and Automation for Sustainability (ICIAfS), 1–6. https://doi.org/10.1109/ICIAFS.2016.7946564 .
[17] Xia, P., Zhou, T., Ye, Y., & Du, J. (2024). Human autonomy teaming for ROV shared control. Journal of Computing in Civil Engineering, 38, CPENG-5756. https://doi.org/10.1061/jccee5.cpeng-5756 .
[18] Tan, Y. H., Liu, X., & Chen, B. M. (2018). Hardware adaptation of a small commercial ROV for autonomous use. In 2017 Asian Control Conference, ASCC 2017, 1252–1257. https://doi.org/10.1109/ASCC.2017.8287350 .
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